Keywords: Human Interfaces, Mechatronics Systems, Identification and Estimation
Abstract: In recently years, the number of the technical successors has been increasing because of the declining birthrate and aging populations. To solve the problem, the motion-copying system was developed, which can save and reproduce the human motion. However, there are the problems in the conventional motion-copying system. Those are the lack of operability and loss of touch sensation at the abstraction phase. Then, we focused on the force estimation by surface-EMG for abstracting force information. In this paper, we used the explainable AI to generate the force estimation model, although the black box AI has been used in the conventional research. That AI is called element description method. We conducted on some experiments and considered the meaning of the model by the explainable AI in this paper. Finally, we showed the superiority of the element description method in this paper.

Keywords: Human Interfaces
Abstract: For the acquisition of sports skills, it is important not only to support with visual information such as video information, but also through interactive support methods using somatosensory information. In this study, we focus on the sport of skateboarding and, develop a device to measure the center of pressure (COP) on the skateboard surface in order to support skill acquisition. This paper describes the fabrication of a skateboard system equipped with resistance pressure distribution sensors. Then, regarding the evaluation of the development system, we verified the measurement performance and the difference in the skateboard skill level when going straight. Experimental results showed that there was a difference in the magnitude of his COP blur during straight-ahead skateboarding between experienced and inexperienced skateboarders.

Keywords: Nonlinear Control, Safety, Environment and Eco-Systems, Human Interfaces
Abstract: Both visualization and control barrier functions (CBFs) have been actively studied to improve safety. However, there exists no system that uses CBFs and visualization. Hence in this study, we propose real-time visualization of collision risk using CBF. CBF is used to evaluate the safety against human operator input and to calculate the safety index. Using the safety index, the effectiveness of the system is discussed through experiments using actual equipment.

Keywords: Human Interfaces
Abstract: The skin shape of the body, which reflects the static and dynamic activities of body tissues, has been applied to motion estimation. Since the skin shape varies under limb pose and motion speed, it is necessary to combine sensors that capture the deformation with different sensitivities to cover a wide range and variety of deformations. In this study, we investigate the effectiveness of simultaneous measurement of distance and force between the sensor unit and the skin for joint angle estimation. Using the sensor unit in the experiment, we try to estimate the continuous wrist joint angle (an axis of palmar and dorsal flexion) under slow and fast speed conditions and free motion conditions. The experimental results indicate that the combined feature of distance and force achieves the highest accuracy in estimating continuous joint angles under all conditions.

Keywords: Identification and Estimation, Mechanical Systems Control
Abstract: In this paper, we try to estimate fault location by using parameter estimation via deep learning. We illustrate that one fourth-order system model can instantaneously be estimated from a set of input/output data, and that the response characteristics can be estimated when parameter values change by some failure.

Keywords: Identification and Estimation, Remote Sensing, Networked Sensor System
Abstract: This paper investigates the problem of sparse attack isolation and distributed secure state estimation (SSE) for remote sensor network in an attack-prone environment. The attack considered in the present paper is a variant of the sparse sensor attack model, and is characterized by the number of sensors clusters that can be compromised at each moment. By analyzing the worst-case scenario in the presence of the considered attack, an attack detection and isolation mechanism based on the weighted communication design is provided to block the spread of the attack across the observer network. Moreover, based on the attack isolation, a distributed SSE algorithm is constructed to ensure globally consistent state estimation. Finally, a numerical simulation is provided to validate the effectiveness of the proposed conditions and algorithm.

Keywords: Intelligent Systems, Transportation Systems, Identification and Estimation
Abstract: This paper presents a study on achieving accurate self-position and heading estimation for outdoor mobile robots through the combination of the Centimeter Level Augmentation Service (CLAS) and the moving baseline algorithm. CLAS is one of Precise Point Positioning (PPP)-Real-time Kinematic (RTK)-based positioning augmentation service, transmitted from Japan's Quasi-Zenith Satellite System (QZSS), which offers centimeter-level accuracy in positioning for Global Navigation Satellite System (GNSS). Unlike RTK GNSS, which requires a base-rover configuration and separate base-rover stations for transmitting GNSS correction information, CLAS is not restricted by the range of movement when applied to outdoor mobile robots. However, even if the mobile robot can be estimated the centimeter level positioning applying this method, the heading of the mobile robot cannot be estimated when it is stationary. To achieve stable measurement of the heading of the mobile robot, we apply a moving baseline algorithm, which uses two GNSS receivers, enabling a highly accurate estimation of the heading based on the relative difference of their GNSS positional information. Combining CLAS-based PPP-RTK and the moving baseline will realize highly accurate navigation for mobile robots. To validate the proposed method, we performed self-position and heading estimation using an actual robot and confirmed its effectiveness.

Keywords: Mechanical Measurement, Identification and Estimation
Abstract: This manuscript focuses on dynamic deformation of viscoelastic materials. Analysis of dynamic behavior of soft robots requires dynamic modeling of soft robot materials. We formulate dynamic deformation of viscoelastic materials via power laws. Model parameters in power laws are identified by numerically minimizing the error between measured and calculated stress--strain relationships. Additionally, we experimentally evaluate surface stickiness of viscoelastic materials.

Keywords: Mechanical Systems Control, Modeling, System Identification and Estimation, Mechatronics Systems
Abstract: The purpose of this paper is to analyze linear internal resonator and circular internal resonator. It is vital to explicitly consider spatio-temporal characteristics in order to realize that vibration is not transmitted to a specific position in a vibrating tool. Therefore, we performed vibration analysis using the spatio-temporal transfer function.

Keywords: Mechatronics Systems, Robotic and Automation Systems, Modeling, System Identification and Estimation
Abstract: In this study, utilizing a Monte Carlo method, we improve the rotational robustness of Normal Distribution Transform - Simultaneous Localization and Mapping (NDT-SLAM). NDT-SLAM can realize real-time SLAM by high-speed calculation, but the estimation may fail when the rotation speed is high. This research employs a global self-localization method using Markov Chain Monte Carlo (MCMC) Methods. It enables robust estimation even when the azimuth angle changes significantly between sampling periods, such as when the rotational angular velocity is fast. Experimental results using LiDAR point cloud data in the actual field confirmed that SLAM is feasible even when the angular change in self-pose is significant.

Keywords: Transportation Systems, Mechanical Systems Control, Safety, Environment and Eco-Systems
Abstract: We proposed the active suspension based on piecewise sampled-data control with finite-time settling function, termed vibration manipulation function. The difference between the position of the suspension base and the road surface profile was compensated in each manipulation by extending and retracting the actuator between the unsprung mass and the base. By obtaining road surface profile in advance, active suspension worked much efficiently. Under the feedforward control of the position of the suspension base along vibration manipulation function, we can mostly cease residual vibration of the sprung mass of a quarter-car model at the end of each manipulation at a step in simulation.

Keywords: Transportation Systems, Innovative Systems Approach for Realizing Smarter World, Adaptive and Optimal Control
Abstract: This study addresses the cooperative control of CAVs(Connected and Automated Vehicles) at Signal-free Intersection. The purpose is to reduce fuel consumption by crossing intersection without stopping as much as possible while ensuring safety. For this problem, We consider a two-stage control structure.The first stage is to calculate the merging time of each CAV by solving mixed integer linear programming (MILP). In the second stage, each CAV solves the optimal control problem and determines the input in time for the merging time. In this study, We propose an optimal control method using control barrier function considering more realistic scenario, and a speed regulation zone to cross the intersection at a pre-determined terminal speed. By using input corrections and trajectory tracking of speed and position, simulation results show that fuel consumption can be reduced while ensuring safety. Finally, compared to conventional research, the system achieves low fuel consumption, and demonstrating its superiority.

Keywords: Robotic and Automation Systems, Mechatronics Systems, Components and Devices
Abstract: As integration of multiple system on a singular chip become possible, Heterogeneous Multicore Processors (HMP) provide a way to have both general purpose cores running Linux and a real-time capable core on the same silicon, sharing memory and interfaces. This article presents the current state of the research, deployment and tests of the Robot Operating System 2 (ROS2) Data Distribution Service (DDS) communication system on abovementioned HMP processor, enabeling internal communication from Linux to the real time core running the Robot Operating System for microcontrollers (micro-ROS).

Keywords: Transportation Systems, Autonomous Decentralized Systems, Network System Integration
Abstract: In recent years, natural disasters such as earthquakes and typhoons have occurred frequently in Japan. In the case of a large-scale disaster, prompt and efficient rescue activities are required to protect the lives of the victims. In response to such natural disasters, the government and local governments formulate disaster prevention plans while considering the characteristics of each region to prepare for the occurrence of disasters. The authors reported a rescue transportation simulator and analytical solution to estimate transportation performance considered in the disaster prevention plan. In the simulator,  vehicle set was introduced. However, the analytical solution did not consider the set. The  vehicle set is necessary to efficient vehicle dispatch, because the fastest vehicle that can reach the next rescue location is selected from the set. In this paper, the analytical solution is modified to estimate the effect of the  vehicle set. Using these tools, the analyses are carried out for a simple problem to validate the modified analytical solution. In addition, the tools are applied to a condition of disaster prevention plan of a city, envisaging a Tokyo Inland Earthquake. Transportation capability for the injured people is quantitatively clarified under multiple scenarios. The user of those analytical tools can consider more effective measures of rescue operation.

Keywords: Transportation Systems, System Engineering, Adaptive and Optimal Control
Abstract: Developing smart parking management systems to minimize environmental impacts and maximize user comfort is highly demanding. Using emission-classified vehicle information, emerging computation, and communication technologies opens opportunities to provide practical solutions to achieve such goals. Considering the need for a future sustainable society with enhanced user comforts, this paper proposes a smart parking algorithm that optimally allocates the incoming vehicles to reduce overall emissions in closed parking facilities while providing comfort-incentive to the users of the emission-free vehicles. Specifically, upon arrival of a vehicle, the most suitable parking point is determined by minimizing an adaptive objective function that indirectly reflects anticipatory operation for overall performance maximization of the parking facility. The proposed system is simulated for managing a model car parking facilities, and the aspects related to CO2 emissions and user comforts are evaluated.

Keywords: Signal and/or Image Processing, Human Interfaces, Entertainment Systems
Abstract: Our final objective is to achieve a solution that avoids visible and unsightly barcodes by invisibly embedding within images 2D barcodes encoded with short-string digital information. This study proposes a deep photographic steganography that uses 2D barcodes and is robust to image perturbations caused by printing and scanning devices. We proposed model training using a distortion network to improve the restoration performance of the 2D barcodes. In addition, the invisibility of 2D barcodes in container images was improved by applying a low-contrast method to the 2D barcodes. The experimental results confirmed the effectiveness of the proposed method in terms of both invisibility and restoration performance.

Keywords: Signal and/or Image Processing
Abstract: The area of residual tumor is independent predictors of survival of cancer patients. In this study, we investigated an effective method for cancer area segmentation in HE stained images to calculate the area of tumor. In addition to prediction by U-Net, the proposed method combines removal of small noisy regions, region segmentation by superpixel, and patch classification by CNN to suppress false negatives and false positives. As a result, the proposed method obtained higher IoU score than comparison methods while maintaining higher precision and recall.

Keywords: Signal and/or Image Processing, Computational Intelligence, Factory Automation
Abstract: In this paper, we discuss an inspection method of defects that occur on the sides of ring parts as anomalous products. In a machine learning method of a defect inspection, defective parts images are shortage because the anomalous products are rare. And defects cannot be overlooked in the inspection of machine parts. To overcome these problems, we develop the inspection method of defects using EfficientGAN. We also introduce the Anomary Score to identify normal or anomalous image. As the experimental results, we can achieve the precision 99.36%.

Keywords: Signal and/or Image Processing
Abstract: Estimating a single tree leaf number using images captured in natural environments is a challenging task. In this study, we propose a method for single tree leaf number estimation in infrared images by combining regression and ordinal classification techniques. To evaluate the effectiveness of the proposed method, a 10-fold cross-validation experiment was conducted on a test dataset. The results demonstrated that the proposed method achieves a mean absolute percentage error (MAPE) of approximately 10%, indicating its high accuracy for single tree leaf number estimation in natural environments.

Keywords: Signal and/or Image Processing
Abstract: To manage fruit trees, leaf-to-fruit ratio, which is ratio of leaf number and fruit number, is important index. However, while there have been many attempts to count the number of fruits using deep learning, there have been few attempts to estimate the number of leaves. In order to reduce the runtime of the leaf count estimation method using orchard point cloud data, this study examines individual tree segmentation using the watershed method. At first, after projecting the point cloud onto the ground surface, an observed area is divided into blocks to find the highest point in the block and generate a tree height map. In the next, a watershed method is applied to the image to segment individual trees. Compared to the conventional method, the time reduction was 40% for data with a voxel size of 0.05 m and 98% for data with a voxel size of 0.01 m. In the future, we plan to develop noise reduction methods and seed value setting for watershed adapted to orchard characteristics.

Keywords: Sensors and Transducers, Signal and/or Image Processing
Abstract: One of the performances of an optical filter, particularly its ability to maintain a consistent spectral response across different angles of incidence, is critical for accurate and reliable measurement. In this paper, we present a comprehensive evaluation of the angle-insensitive performance of our own designed optical filter. Our approach involves measuring the hyperspectral cube of a green paper plate and quantifying the color difference between the center patch and edge path. We demonstrate the effectiveness of our methodology by evaluating the angle-insensitive performance of a fabricated optical filter and the proposed design method. Our results show that the proposed optical filter design approach exhibits a high degree of angle-insensitivity at the image edge. This research provides valuable insights into the design and optimization of optical filters for angle-insensitive applications.

Keywords: Adaptive and Optimal Control, Identification and Estimation
Abstract: In this research, we propose a method to estimate the algebraic Riccati equation (ARE) under the assumption that the system is unknown, but its state and input can be observed. The ARE is essential to solve the inverse linear quadratic regulator (ILQR) problem. The ILQR problem is a problem of finding the quadratic objective function optimized by the given linear time-invariant feedback system. The ILQR problem is easily solved by solving the linear matrix inequality including the ARE if the system model is readily available. However, the system is often unknown in biological system analysis, the main fields where the ILQR problem is expected to be applied. To solve this problem, we obtain an equation that is derived from the ARE but only requires trajectory data of the system and not the system model. We further provide two conditions for the equation to be equivalent to the original ARE. The advantage of our method compared to system identification is that prior information on the objective function can be used to reduce the data needed for ARE estimation. Numerical experiments are performed to support our claims.

Keywords: Adaptive and Optimal Control, Modeling, System Identification and Estimation, Identification and Estimation
Abstract: In this paper, we propose a data-driven control method for systems with nonlinear elements by introducing a kernel representation for nonlinear elements and combining a data-driven control approach. The proposed method mainly consists of two steps; the first step is to estimate parameterized nonlinear elements and the second step is the search for the optimal control input. The effectiveness of the proposed method is verified through simulation.

Keywords: Adaptive and Optimal Control, Power Systems Control
Abstract: In this paper, we propose a data-driven distributed and localized model predictive control (D3LMPC) using a one-step model predictive control (OMPC) and an accelerated alternating direction method of multipliers (A-ADMM) algorithm. The A-ADMM algorithm enables the reduction of the number of iterations using the Nesterov's accelerated gradient method. The OMPC is a special version of MPC with single horizon and enables the reduction of computational loads. Using the two methods, we show that the number of iterations and computational loads can be reduced in comparison with the original D3LMPC method. Simulations are carried out on a coupled synchronous generator model with four connected subsystems.

Keywords: Intelligent Control, Adaptive and Optimal Control
Abstract: The widespread use of Proportional-Integral-Derivative (PID) controllers in industry has spurred the development of various effective methods for tuning the PID gain. One such method is the PID parameter tuning based on Generalized Minimum Variance Control (GMV-PID), which has proven to be useful. However, since real-world systems exhibit individual differences in the form of modeling errors, a fine-tuning method for PID parameters is necessary after system implementation. In this study, a parameter tuning method for GMV-PID controllers is proposed that uses a database to store operational data. The proposed method updates the tunable parameter in the PID controller sequentially based on the database, enabling automatic fine-tuning of the PID controller after system implementation by adaptively tuning the parameter. Mathematical simulations were conducted to verify the effectiveness of the proposed method.

Keywords: Intelligent Control, Computer Aided Design, Intelligent Systems
Abstract: This paper focuses on the quantization of weight coefficients in trained neural networks. In order to reduce the loss of the input-output relationship of neural networks due to quantization error, we propose a noise-shaping quantizer characterized by training data. Then, we verify the effectiveness of the proposed method by applying it to the compaction of a neural network controller in a feedback control system.

Keywords: Remote Sensing, Signal and/or Image Processing
Abstract: Currently, the management of power lines requires a great deal of time and labor, additionally differences in the inspection skills of workers affect the diagnosis results. In recent years, three-dimensional point cloud data (3D-PCD), which has become easier to acquire, is getting used for management in order to solve these problems. However, the technique for automatic extraction and evaluation of power lines from the acquired data is not yet available, and we had been studying automatic tracking methods for power lines. In this study, we propose a novel method to find the connection points between power lines and power poles by extracting power poles from the PCD in order to determine the start and end points of power line tracking. We confirmed that the proposed method can extract power poles and power lines separately, and showed that it is effective for improving the performance of power line tracking.

Keywords: Nonlinear Control, Network System Integration, Robotic and Automation Systems
Abstract: The shepherding problem refers to guiding a group of agents (called sheep) to a specific destination using an external agent with repulsive forces (called shepherd). Although various movement algorithms for the shepherd have been explored in the literature, they do not consider any serious problems in existence and asymptotic dynamics. In contrast, for the shepherding swarm model, collisions are closely related to the bad issue. Therefore, this study looks for some conditions to prevent collisions of the shepherding swarm model. We first present our model of the dynamics of sheep agents and the interaction between sheep and shepherd agents. Then we introduce some sufficient conditions leading to the collision-free property of the sheep in the shepherding swarm model.

Keywords: Robotic and Automation Systems, Autonomous Decentralized Systems
Abstract: This study proposes a real-time action planning system for autonomous mobile robots, allowing them to request assistance from other robots when necessary. The system focuses on seaarch and uses a ground robot and a drone to search unknown areas. The drone creates a Occupancy Gird Map and transfers it to the ground robot for optimal path planning. The behavior tree used for autonomous robot search reactively selects actions to uncertain events by monitoring the state, which is grown using a reachability graph generated in advance by offline planning. The system allows robots to automatically generate tasks and decide which robot should perform them, optimizing battery consumption and avoiding unnecessary movements.

Keywords: Robotic and Automation Systems, Mechatronics Systems, Components and Devices
Abstract: Experimental multi-robot systems using mobile robots have been built in various configurations. Recently, systems equipped with hardware and software capable of handling high loads have been used, but they are only sometimes feasible due to high configuration costs. This study considers a system composed of microcontroller, wireless module, and optical motion capture system. This configuration method allows multi-robot experimental system to be realized using only classical and basic system integration methods such as microcontroller programming, TCPIP communication, and C programming. As an example of the application of the completed system, we confirm the effectiveness of the system by realizing a sheepdog system and platooning control.

Keywords: Robotic and Automation Systems, Network System Integration, Networked Sensor System
Abstract: This study tackles a control problem to robustify the multi-robot network connectivity in the existence of the gateway node. To avoid over-robustification which causes a restriction on robotic behavior, we consider controlling a component size connected to the gateway node after a single robot failure. We simplify the control problem to a problem of whether each robotic node can become an articulation node or not with preserving the network robustness. Then we detail a control method to preserve the robotic

Keywords: Robotic and Automation Systems, Networked Sensor System, Nonlinear Control
Abstract: This paper addresses the target pursuit task by multiple mobile robots equipped with visual sensors in an environment with spherical obstacles. First, we define a target as visible to a robot when feature points on the target are inside the robot's field of view and are not occluded by an obstacle. To formulate this visibility, we derive safe sets for maintaining the field of view and for avoiding occlusion. Next, in order to achieve visibility of the robot network, we propose two methods for online visibility determination based on the mixed integer programming and the dynamic average consensus algorithm. Finally, the effectiveness of the proposed method is verified by simulation.

Keywords: Sensors and Transducers, Factory Automation, Components and Devices
Abstract: We are developing inductive proximity sensors that support general ON/OFF output and IO-Link interface. In developing this product, we developed an IC for proximity sensors. The oscillation circuit developed with this IC has a small temperature characteristic and can be set to an oscillation amplitude proportional to the detection coil impedance from the state of close contact to the state where there is no detection target, and the proximity sensor that supports IO-Link communication can output a digital value according to the position of the detection target.

Keywords: Sensors and Transducers, Identification and Estimation, Medical and Welfare Systems
Abstract: Long-time routine ECG measurement is expected as a preventive　medical approach for cardiovascular diseases. Using　capacitance-coupled electrode arrays enables unconstrained,　non-contact, long-time measurement targeting the sleeping　period. In this study, Flexible Printed Circuit electrodes　with flexible elasticity that enables electrode placement more　in line with the body were developed, and capacitance　silhouette and ECG measurement were successfully performed.

Keywords: Sensors and Transducers, Identification and Estimation, Networked Sensor System
Abstract: In recent years, disasters caused by localized torrential rains of short duration due to linear precipitation belts have frequently occurred. Therefore, we are considering the early detection of localized heavy rainfall to the extent that a disaster occurs by sound information from a distant place, and as a preparation, we are trying to know the relationship between rain sound and rainfall. In this paper, we report on a prototype sensor for measuring the kinetic energy of raindrops using strain gauges, which is mounted on multiple sensor nodes.

Keywords: Sensors and Transducers, Intelligent Systems, Robotic and Automation Systems
Abstract: Shape sensing in continuum robots is a crucial aspect of their operation as it enables the robots to accurately perceive and respond to their environment. However, traditional sensors such as encoders or potentiometers are not well suited for these types of robots as they cannot conform to the robot's shape and are prone to damage. In this research, we investigate the problem of shape sensing in continuum robots using a new approach of a soft e-textile resistive sensor with multiple stacked layers. The e-textile, which can conform to the shape of the continuum robot body, employs a resistive material that changes its resistance in response to any deflection in the continuum robot. The characterization of the sensor, including hysteresis analysis and time response, is first presented. This is followed by an examination of the application of this e-textile sensor in estimating the curvature of a continuum robot using a feed-forward artificial neural network (ANN) to contribute to developing more robust and efficient shape-sensing techniques for continuum robots.

Keywords: Sensors and Transducers, Mechanical Measurement, Mechatronics Systems
Abstract: Elastomers, polymers, and human tissues are well-known viscoelastic materials whose behavior are hard to grasp. Several mathematical models, being linear and nonlinear, have been proposed to describe the elastic and viscous properties of viscoelastic materials. In this paper, we aim to characterize the dynamic properties of silicon rubber viscoelastic material with different mixing ratios. To this end, an experimental setup using a piezoelectric cantilever was used to apply force to the viscoelastic specimens, and an eddy current sensor was used to measure the displacement. We used the Standard Linear Solid (SLS) model and the hysteresis loop methods to formulate the relations between applied force, displacement, damping, and stiffness. Furthermore, an optimization approach was proposed to fnd the SLS model parameters by searching functions over the frequency domain. The obtained results agree with the related research. In addition, our approach differentiated between the tested specimens depending on damping and stiffness dynamic properties. The results have shown that the damping of the PDMS tested specimes decreases with increasing the frequency and the harder the elastomer the more damping it shows. Also, the stiffnesses of the SLS model increase by increasing the frequency and by increasing the hardness of the elastomer.

Keywords: Human Interfaces
Abstract: In recent web conference systems, it has become possible to express the user's gaze and attention through image processing. However, many users feel uncomfortable turning on the camera, and the sense of looking and listening worsens when the camera is turned off. Therefore, in this study, we investigated whether it is possible to improve the sense of gaze and listening by using thought bubbles even when the camera is off and there is no face information of the interlocutor. We have developed a video conferencing system that displays a pictogram image of a person with a thought bubble. The thought bubble displays the user's face image. In addition, it is possible to extract the words that are the focal points of the user's utterances and display them in a thought bubble. As a result, it was confirmed that the interlocutor's sense of being looked at was enhanced by the presence of a thought bubble even when the interlocutor shows pictogram images of people. This result also suggests that thought bubbles can effectively show an interlocutor's attention.

Keywords: Human Interfaces, Human-Machine Systems, Intelligent Systems
Abstract: Facial expressions are a vital part of nonverbal communication and are used to convey a wide range of emotions. Recent works have suggested that cultural and societal factors may influence how people express and interpret facial expressions of emotion. This study explores image features of facial expressions of the same emotion in two different cultures, Thai and Japanese, to identify features that are common and different among expressions across cultures. To achieve this goal, we collected facial expression samples from entertainment media in Thailand and Japan. The subspace techniques are applied to create feature spaces that represent facial expressions from these samples, and to extract image features that can reveal differences in facial expressions between pairs of emotions in both cultures. Our study finds evidence that suggests sufficient distinctions between expressions of some emotions in both cultures, particularly happy and disgust classes, while the characteristic of the surprise class is similar across Thai and Japanese samples.

Keywords: Human Interfaces, Intelligent Systems
Abstract: The development of remote learning environments is being promoted to provide equal opportunities for learning. However, some challenges exist with remote learning, such as difficulty in learners maintaining their concentration and the inability to determine how a learner state of being. In this study, the authors propose a new method to monitor learners'efforts in a remote class while avoiding communication loads, such as video images. The authors use OpenPose detection library to obtain the body skeletal coordinates of an individual learner's frontal Red-Green-Blue color (RGB) model video, including the learner's hands, and attempted to classify the learner's posture by pattern matching, and estimate the learner's writing behavior using wrist coordinates. Consequently, both posture classification and writing behavior estimation were possible with an accuracy of more than 80%, suggesting the possibility of perceiving a remote individual learner's poise without using video communication.

Keywords: Identification and Estimation, Sensors and Transducers, Human Interfaces
Abstract: In recent years, wireless devices have become smaller and more portable. In addition, it is thought that personal identification and authentication will be necessary when they are used as independent terminals similar to smartphones. In this study, we focus on a neck-mounted earphone and propose personal identification and authentication using the acoustic characteristics of the clavicle, taking advantage of the fact that the clavicle touches the device when it is worn. Active acoustic sensing was used to measure the acoustic characteristics of the clavicle and extract its acoustic features. The accuracy was 98.8%, and the EER was 4.0% in five persons.

Keywords: Micro and Nano Devices, Modeling, System Identification and Estimation
Abstract: The semiconductor market continues to expand and the importance of improving productivity in semiconductor manufacturing is increasing. In addition, with the increasing difficulty of process shrink, the importance of the plasma etching process has increased especially in recent semiconductor manufacturing, and it is important to improve the productivity of plasma etching equipment. To improve the productivity of plasma etching equipment, predictive maintenance (PdM) using sensor data of the system condition has recently been proposed in contrast to conventional periodic maintenance. In this paper, a feature extraction method based on sensor waveform component separation and a predictive maintenance approach using this method are proposed for the characteristic sensor data of plasma etching equipment, where the effects of disturbances caused by the process and multiple degradation factors can overlap, in order to realize PdM of plasma etching equipment. Simulation verification based on a case study of actual collected experimental data showed the effectiveness of the proposed method in terms of prediction accuracy.

Keywords: Modeling, System Identification and Estimation, Opto-Electronic Measurement
Abstract: Quantum entanglement states in continuous variable quantum teleportation can transfer any quantum state. However, errors occur in the quantum states before and after the transfer in scientific experiments because generating a perfect quantum entanglement is physically unattainable. This paper limits the quantum states transferred to squeezed coherent states and introduces a controller to classical information transfer in continuous variable quantum teleportation to improve transfer accuracy.

Keywords: Modeling, System Identification and Estimation, Identification and Estimation, Mechatronics Systems
Abstract: In this study, we attempt to estimate the time-varying wrist impedance in the peg-in-hole task. We employ a wearable impulsive perturbation generator called the snap motor, which has advantages such as little disruption to voluntary movement during task execution and no need for a force (torque) sensor for impedance estimation. The task phase is divided into some subphases, and the wrist impedance at each subphase is estimated. In addition to the measurement data such as wrist motion and electromyogram, we ask the participants about their intention of the task execution. The experiment was carried out with three healthy participants, and their wrist impedance depending on the task phase was estimated. The obtained wrist impedance of each participant was consistent with their EMG pattern and intention of motion control respectively.

Keywords: Modeling, System Identification and Estimation, Agricultural and Bio-Systems, Temperature Measurement
Abstract: Improving photosynthetic efficiency increases the yield of fruits and vegetables. Carbon dioxide exchange and transpiration from the stomata are indispensable for regulating the carbon dioxide and water required for photosynthesis. They are affected by the vapor pressure deficit (VPD) of the air around plants. In our previous research, we constructed a VPD control system using a fine mist cooling and an IoT system that measured CO2/H2O concentration at multiple points. We recorded temperature, humidity, VPD, carbon dioxide, and water content in a sunlight type plant factory. However, the time-series estimation of spatial data by spraying the fine mist, transpiring H2O, and absorbing CO2 have yet to be elucidated. Furthermore, although spatial data such as temperature, VPD, CO2 and H2O have been recorded in a plant factory, they have yet to be recorded during plant growth. Therefore, mathematical modeling of spatial data (VPD, CO2/H2O concentration, temperature, and PPFD (photosynthetic photon flux density)) is used to clarify the relationship between spatial data and plant growth. The objective is to estimate the parameters that maximize the amount of photosynthesis, and we construct a plant growth model of microenvironment in the artificial light type cultivation.

Keywords: System Engineering, Identification and Estimation, Robotic and Automation Systems
Abstract: Developing remote control and supervision technology can aid in addressing current and future safety issues at sea due to human errors resulting from one-person watchkeeping. This paper presents a remote assistance system that uses virtual reality (VR) to reduce the risk of human error and alleviate officers’ workload. The system provides a VR environment that replicates the ship's state and navigational instruments, with limited connectivity via satellite, enabling an operator at an office onshore to have a comprehensive understanding of the surroundings, as if they were on the navigational bridge. Two navigation experiences were used to evaluate the system, and the results demonstrate that the developed system is an effective support tool for double-checking purposes.

Keywords: Nonlinear Control, Adaptive and Optimal Control, Transportation Systems
Abstract: The trajectory tracking control problem is an important challenge to realizing an autopilot system for a marine vessel. In this study, we propose an adaptive controller design method for a marine vessel model to track a straight trajectory. A kinematic marine vessel model is not a differentially flat system; however, it is transformable into a differentially flat system. We utilize this character to design an adaptive controller. First, we design a differentially flat model by applying coordinates transformation to the marine vessel model. After that, we design an adaptive controller for the model with differentially flat properties. Finally, we transform the designed controller into the original model's controller. The effectiveness of the proposed method is confirmed by a computer simulation.

Keywords: Signal and/or Image Processing, Remote Sensing, Transportation Systems
Abstract: Traffic accidents are a serious problem. The number of fatal traffic accidents is highly correlated with the speed of danger recognition. Thus, we seek to monitor a wide range of traffic information using an altitude camera. The altitude-camera-images can be analyzed to estimate vehicle speed over a distance of 300--600 meters. However, it is difficult to accurately calculate the moving distance and speed of vehicles because altitude-camera-images are taken from a bird's-eye view. When estimating vehicle speed, the vehicle's position should be transformed into a nadir coordinate. In this paper, we propose a method of image registration for transforming the vehicle's position. In our method, broken-white-lanes are respectively extracted from an altitude-camera-images and an ortho-mosaic-image, and extraction results are used for image registration. As a result, we have transformed the object's position on the road in an altitude-camera-images into a nadir coordinate.

Keywords: System Engineering, Human-Machine Systems, Transportation Systems
Abstract: In recent years, smartphone walking has become a hot topic of discussion as a dangerous behavior of pedestrians, and understanding these behaviors is a crucial issue in reducing traffic accidents. However, analysis for smartphone walking targets only human cognition, and pedestrian decisions and motion have not been well analyzed. Therefore, in this paper, pedestrian simulators were constructed using a VR device to measure pedestrian decisions and motion. The pedestrian’s decision is represented by a logistic regression model, and the ambiguity of the decision is evaluated by information entropy based on this model. In addition, the pedestrian’s motion was analyzed based on statistics to investigate the impact of smartphone walking on their decisions and motion.

Keywords: Transportation Systems, Adaptive and Optimal Control, Network System Integration
Abstract: In a traditional single-lane intersection, a vehicle waiting for a safe turning often causes others to stop for a long time, triggering a traffic bottleneck with spillback congestion. This paper proposes a cyber-based vehicle coordination system for comfortable traffic flow in such a scenario with the necessity of a safe and smooth right turn. Specifically, considering the information of upcoming vehicles at an intersection, the coordination system solves an optimization problem to obtain the best timing for executing a right turn that minimizes the total delay of all vehicles. The proposed scheme is evaluated in a typical urban intersection, and the performances are compared with the traditional traffic.

Keywords: Transportation Systems, Signal and/or Image Processing
Abstract: The safety of the railways is maintained by regular maintenance of tracks, signals, and rolling stocks to keep them in good conditions. Notably, such maintenance is ensured using a manual inspection method that involves skilled maintainers, however automated inspection systems are only partially used. To maintain a good condition of railways, the development of the automated inspection systems is crucial. Herein, we focused on automatic surface defect detection of wheels because wheels are especially important components of the rolling stocks. We have already previously evaluated wheel tread profiles using laser instruments. However, in this research, to confirm the accuracy of the measurement equipment, we prepared special test pieces that include intentionally processed surface defects. Experiments were conducted using different materials, different passing speeds by employing laser sensors, and a machine vision technique to confirm the effectiveness of the proposed inspection system.

Keywords: Modeling, System Identification and Estimation, Robotic and Automation Systems
Abstract: Continuum robots, made from flexible materials with continuous backbones, have several advantages over traditional rigid robots. Some of them are the ability to navigate through narrow or confined spaces, adapt to irregular or changing environments, and perform tasks in proximity to humans. However, one of the challenges in using continuum robots is the difficulty in accurately estimating their state, such as their tip position and curvature. This is due to the complexity of their kinematics and the inherent uncertainty in their measurement and control. This paper proposes a moving horizon estimation (MHE) approach for estimating the robot’s state, including its tip position and shape parameters. Our approach involves minimizing the error between measurement samples from an IMU attached to the robot’s tip and the estimated state along the estimation horizon using an inline optimization problem. We demonstrate the effectiveness of our approach through simulation and experimental results. Our approach can potentially improve the accuracy and robustness of state estimation and control for continuum robots. It can be applied to various applications such as surgery, manufacturing, and inspection.

Keywords: Nonlinear Control, Robotic and Automation Systems, Mechanical Measurement
Abstract: The main objective of this research is to control the pneumatic vibration-isolation table according to the magnitude of the vibration using time and acceleration information to return the table to its original position quickly and accurately. As the pneumatic system is configured with an On-Off valve to let air flow in and out, the input is discretized by the quantizer, resulting in a steady-state deviation with irregular values. Therefore, depending on the circumstances, the deviation can be suppressed by chance, and the steady-state deviation can be significantly reduced by reproducing the input at this time each time. In a previous study, the magnitude of the impulse disturbance is identified by the magnitude of the acceleration, and a method of feedforward input is proposed based on the pressure value. In this paper, after identifying the disturbance by acceleration, the compatibility with the pressure signal is verified by performing feedforward input after a specific time has elapsed.

Keywords: Robotic and Automation Systems
Abstract: This paper presents a method for controlling the position and stiffness of a 2-DOF robot arm driven by three pairs of antagonistic actuators, which mimics the musculoskeletal system of human limbs. In this study, we propose a new method of solving the distribution problem of the musculoskeletal-inspired robot arm based on a direct sum decomposition of the actuator force space. The proposed solution allows to control the stiffness separately from the position, thus simplifying controller design. We then design a position and stiffness controller. The control law consists of a PD feedback position controller and a feedforward stiffness controller in joint space that are designed independently from each other. The proposed controller can asymptotically stabilize the equilibrium point of the closed-loop system and does not require a force sensor for stiffness control. Simulation results prove the effectiveness of the proposed solution and controller.

Keywords: Robotic and Automation Systems, Mechanical Systems Control, Mechatronics Systems
Abstract: In order to improve the safety of robots, many attempts have been made to make soft robots using rubber or resin. Since a multibody system including viscoelastic bodies is a stiff system, stable analysis is difficult with ordinary explicit numerical integration. In this study, we develop an approximate analysis method that can analyze the system including viscoelastic bodies at high speed and stably by combining the approximate rigid link model, the recursive dynamics algorithm, the linear viscoelastic model and the implicit numerical integration method. In this paper, we especially examine the case of using the generalized Maxwell model and investigate the effect of introducing nonlinear springs.

Keywords: Robotic and Automation Systems, Mechatronics Systems, Modeling, System Identification and Estimation
Abstract: Soft growing robots are promising for a variety of applications, such as navigating and inspecting confined and challenging environments. These robots can elongate up to tens of meters and have morphological adaptation and tip-extension capabilities. However, evaluating their performance across various design aspects or environmental conditions can be difficult due to their long manufacturing times. In this paper, we present a computationally efficient dynamics model derived using the Euler-Lagrange equation for a class of soft growing robots known as "vine robots." alongside a PD feedback control with gravity compensation. We have performed simulation experiments to validate both the dynamics model and the PD feedback control. The results of these experiments can provide valuable insights for future model-based feedback control design and simulation-based performance evaluation.

Keywords: Power Systems Control
Abstract: In recent years, stationary storage batteries have gained popularity among consumers for self-consumption of renewable energy. Understanding the operating status of these storage batteries is useful for general power transmission and distribution companies when planning to utilize the spare capacity of storage battery groups for the appropriate operation of the power transmission and distribution network. In this study, we propose a method for estimating the capacity and operating state of each battery energy storage system on the consumer side using only net load data from smart meters. Data-driven and model-based approaches were combined using past research surveys, and the k-means clustering method was used as a data-driven approach to estimate the photovoltaic and battery capacity. A Kalman filter-based load and battery state estimation method was proposed as a model-based approach. A numerical example using actual Japanese electricity market data was examined, and the effectiveness of the proposed method was confirmed.

Keywords: Power Systems Control, Modeling, System Identification and Estimation
Abstract: This paper deal with a stability analysis for a load frequency control (LFC) system including Demand Response (DR). To analyze system stability, LFC system is formulated to facilitate the application of passivity theory, and the passivity and passivity-short of the system are analyzed. At first, we express LFC system decomposing into a network system and area systems. Specifically, area systems include DR that occurs time-varying communication delay. Then, passivity analysis is applied to each system. As a result, we can clarify the area systems are output strictly passive if certain inequalities are satisfied, and the network system is passive. Simulation results show that the frequency deviation converges to a constant value under the derived inequality condition.

Keywords: Power Systems Control, Process Control, Mechanical Systems Control
Abstract: This research is concerned with the power generation control of ocean thermal energy conversion (OTEC) plant using hybrid cycle. As the manipulated variables, flow rates of warm seawater and cold seawater are selected. The control system is constructed by using a dynamic model. A method to design proportional integral (PI) controllers by adjusting the flow rates of warm seawater and cold seawater is proposed. The usefulness of the proposed control system was confirmed by numerical simulation.

Keywords: Power Systems Control, Safety, Environment and Eco-Systems, Information Management Systems
Abstract: This paper investigates the benefits of model prediction in a hybrid power system, which comprises solar cells, and a proton exchange membrane fuel cell (PEMFC). The PEMFC is a backup power, providing auxiliary power when necessary. We applied experimental data to build a MATLAB Simscape ElectricalTM model that could simulate system responses, where we found hydrogen consumption might be reduced by foreseeing the solar and load data. Therefore, we applied machine learning techniques to develop two prediction models that can foretell solar radiation and load responses with an accuracy of 96.34% and 93.35%, respectively. We then integrated the prediction models with the hybrid power system. The results showed that model predictions could prevent unnecessary hydrogen consumption and reduce system costs by 40.38% compared to the original system configuration. We also designed an experiment to show the feasibility of integrating these prediction models with the hybrid power system. The results demonstrated the benefits of model prediction for the hybrid power system.

Keywords: Power Systems Control, Social Systems
Abstract: This paper proposes an optimal battery management methodology in microgrids. Every microgrid gives other microgrids a fair deal of electric power based on Generalized Nash Bargaining Solution, which is a kind of optimal solutions of a fair trade in game theory. In this paper, we use a method of scenario optimization in order to take optimal and safe estimates for generations from renewable energy sources. First, many scenarios of the amount of generation are prepared. Then, we calculate the total cost of microgrids for each scenario and find the highest cost. We determine the strategy which corresponds to the highest-cost-scenario as each microgrid's final strategy. Through this method, the number of violations of the limitations of the batteries and the extra cost caused by those violations has been reduced. Power flow in networks which connect each microgrid and an electric power company is also considered.

Keywords: Power Systems Control, Transportation Systems, Social Systems
Abstract: Ancillary services are attracting attention as a means of stabilizing electric power. Participation in this service using an EMS and the onboard storage batteries of Electric vehicles (EVs) is expected to improve efficiency. However, there are many points regarding the exchange of money in cooperative control, and in particular, the method of distributing rewards for participation in the service has yet to be studied. In this paper, we propose a method for determining rewards based on the contribution level when participating in services through cooperative control. First, a charging and discharging control method for service participation is formulated, and a Lagrange multiplier for money is derived from the duality problem. Furthermore, the amount of reward distribution from the Lagrange multiplier is considered in the viewpoint of contribution. The actual rewards are clarified by simulation, and the validity of the method is demonstrated.

Keywords: Agricultural and Bio-Systems, Modeling, System Identification and Estimation, Signal and/or Image Processing
Abstract: We must evaluate the fish schooling behavior under the various light wavelength for the sustainable fisheries. Then, we have constructed the well-controlled fishing method in which the measurement system needs the acquire physical quantities from the collective swimming behavior. In this study, we succeeded in obtaining a large number of fish behavior trajectory. In the experiment, we proposed and implemented a collective algorithm to interpolate the losing fish body images in order to solve the problem that lost images of fish. It is shown to be capable of continuously tracking collective swimming behavior of fish.

Keywords: Agricultural and Bio-Systems, Power Systems Control
Abstract: This study aims to predict and control the temperature and humidity environment in a sunlight plant factory using computational fluid dynamics (CFD) analysis. In a typical CFD analysis, the boundary and initial conditions are determined before the analysis commences, making it impossible to change the conditions depending on the status of the results during the analysis. In this study, however, we developed a method that can respond flexibly to changes in conditions during analysis by linking it with external programs. Furthermore, we also developed a method that combines CFD analysis and feed back control method. This method is highly flexible and facilitates easy modification of control laws. Using this method, we conducted an analysis of a modeled sunlight type plant factory and are reporting our findings here.

Keywords: Agricultural and Bio-Systems, Robotic and Automation Systems, Mechatronics Systems
Abstract: This paper presents a novel design for a parallel mechanism-based manipulator explicitly developed for the harvesting of sweet peppers. The experimental machine was driven horizontally using a 3-DOF spatial translation parallel delta mechanism. This manipulator design aims to increase the speed of manipulation, thereby increasing the speed of harvesting. This design guarantees the safety of the plants because it approaches the fruit horizontally. A prototype for testing the efficacy of the manipulator in real-time has been developed. The manipulation of the links was governed by MATLAB position controlling, and Depth and RGB images were utilized to determine the location of the sweet pepper. Lastly, the results demonstrate that this manipulator can respond adequately. In addition, when the distance to the object is smaller than 400mm, the system approaches the target over 1 [m/s].

Keywords: Agricultural and Bio-Systems, Robotic and Automation Systems, System Engineering
Abstract: Farm industrialists have been forced to shift towards an automated approach in order to improve the agricultural operations. This study presents a new feasible and efficient path planning method based on traveling salesman problem that considers the collecting behavior of the fallen fruits with some additional optimization. An implementation into a two-wheeled differential robot is executed in order to demonstrate and verify its capabilities. We use street marker cones as target objects to represent tree trunks which are then recognized by using a RGB-D camera. The robot is able to obtain each cone’s position to generate optimal collecting motion trajectory. Further optimization, including backward motion behavior is implemented on top of the path planning process. Optimal routes could be generated experimentally in a short processing time and optimized collecting motion could save the operation time depending on the arrangement of the trees.

Keywords: Biological and Physiological Engineering, Simulation of Large Systems, Agricultural and Bio-Systems
Abstract: Structural sensitivity analysis is a steady-state analysis method used in large-scale nonlinear biological systems. This method requires an inverse matrix calculation of a particular matrix derived from the reaction rate vector and the stoichiometric matrix. In this paper, we propose a novel method for structural sensitivity analysis that performs inverse matrix calculations using step responses.

Keywords: Robotic and Automation Systems, Agricultural and Bio-Systems, Signal and/or Image Processing
Abstract: Thinning is an important part of pear cultivation to improve quality, but farmers themselves do not know how many flower buds they have thinned. For this reason, we developed a pear detection system that simultaneously records RTK-GNSS and video images. In addition, an autonomous robot in a pear farm was built to automate the pear detection system. The results of object detection of pears showed that flower bud detection yielded 3958 objects detection results compared to 2842 actual results, and fruit detection yielded 1171 objects detection results compared to 1616 actual results. The maximum path following error was 0.29 m. These results indicate that automatic measurement by a robot in a pear orchard is feasible, and that it is possible to estimate the initial yield.

Keywords: Computational Intelligence, Social Systems, Innovative Systems Approach for Realizing Smarter World
Abstract: This paper utilizes the graph theory with scene image to model the social relationship between the target and the surrounding pedestrians or environment for multi-pedestrian trajectory prediction. Most methods of trajectory prediction only consider the relationship of relative distance between the target and the surrounding pedestrians to describe the social relationship, however, this kind of methods does not correspond to the real situation. The social relationship digraph is proposed to divide the surrounding area of a target pedestrian into blind zone and visible zone according to the moving direction of considered target pedestrian. Since the target pedestrian may not see the surrounding pedestrians in the blind zone, the social features of the surrounding pedestrians in the blind zone will be penalized to reduce redundant and false social information during prediction by the graph convolutional network. The proposed multi-pedestrian trajectory prediction method, which has been tested in several datasets, presents better prediction performance than other related works.

Keywords: Robotic and Automation Systems, Social Systems
Abstract: In tunnel inspections, it is important to determine whether cracks and other deformations are caused by external forces. Therefore, point clouds at two different periods are compared to determine if any deformation has occurred and register these point clouds. In mobile mapping systems using global navigation satellite system (GNSS)/inertial measurement unit (IMU) navigation, tunnel point clouds are distorted due to accumulated errors. Therefore, it is not possible to compare the acquired raw point clouds with each other. Previously, point clouds were aligned manually, but this was time-consuming and expensive. In this work, we propose a positioning correction technique based on scan matching according to tunnel features and describe the evaluation results. The evaluation experiment showed the proposed method's effectiveness, reducing the average error from 0.834 m to 0.063 m.

Keywords: Social Systems, Intelligent Systems, Human-Machine Systems
Abstract: In this paper, we present a novel artificial intelligence (AI) application for depression detection, using ad- vanced transformer networks to analyse interviews with patients. By incorporating simulated data to enhance traditional datasets, we overcome limitations in data protection and privacy, consequently improving the model’s performance. Our methodology employs BERT-based models, GPT-3.5, and ChatGPT-4, demonstrating state-of-the-art results in detecting depression from linguistic patterns and contextual information, that significantly outperforms previous approaches. Utilising the DAIC-WOZ and Extended-DAIC datasets, our study showcases the potential of the proposed application in revolutionising mental health care through early depression detection and intervention. Empirical results from various experiments highlight the efficacy of our approach and its suitability for real-world implementation. Furthermore, we acknowledge the ethical, legal, and social implications of AI in mental health diagnostics. Ultimately, our study underscores the transformative potential of AI in mental health diagnostics, paving the way for innovative solutions that can facilitate early intervention and improve patient outcomes.

Keywords: Social Systems, Nonlinear Control
Abstract: In this paper, we derive the dynamics of cap-and-trade mechanism between firms considering corporate values associated with the carbon dioxide emission reduction. The relationship between the initial emission allowances and total reductions, and the necessary condition to achieve carbon neutrality are shown by the equilibrium state analysis. In the simplest case with 2 agents, the dynamics of the cap-and-trade mechanism are expressed as a piecewise nonlinear system, and the analysis is facilitated by nonlinear coordinate transformation and dimensionality reduction. Finally, we derive a stability condition for the piecewise linearized system and show a couple of types of possible behaviors of the firms in numerical examples.

Keywords: Ubiquitous Healthcare, Biological and Physiological Engineering, Sensors and Transducers
Abstract: Improving the accuracy and precision of light spectroscopy-based non-invasive methods for analyzing glucose in urine samples is critical to enabling comfortable, affordable, and robust approaches to diagnosing diabetes. In this paper, we study the feasibility of using spiral microfluidics in studying the separation efficiency in urine simulations. Our results through computational simulations and hardware experiments with sub-micron microfluidics show: (1) the reasonable separation of glucose/urea at 72% glucose separation efficiency, (2) the possibility of relating flow rate and glucose/urea concentration in a closed mathematical form by using Genetic Programming machinery, and (3) the feasibility to render the quasi-linear pattern/relation between glucose concentration and absorbance, which is potential to aid in providing higher/targeted concentrations of glucose for other non-invasive testing approaches, e.g., light spectroscopy.

Keywords: Ubiquitous Healthcare, Human Interfaces, Integrative Biophysical Engineering and Informatics
Abstract: We focus on ground reaction force (GRF) and center of pressure (CoP) from human walking motion data and develop a wearable device to measure them. The most common methods for measuring GRF and CoP are force plates and motion capture systems, but these are expensive and limited to the laboratory. Many wearable devices for measuring GRF and CoP have already been studied, but some of them use thick sensors, which may affect the response. Therefore, in this study, we use FSR (Force Sensing Resistors), which is thin and inexpensive. Many devices using FSR have already been studied, but they only attach FSR to the insole and cannot directly obtain information about the environment. We propose a wearable device in which FSRs are attached to both insoles and outsoles. In addition, the low sampling frequency was compensated for using spline interpolation. Experimental results showed high accuracy.

Keywords: Nonlinear Control, Robust Control, Safety, Environment and Eco-Systems
Abstract: This paper provides an interactive shape memory alloy (SMA) actuator-based nonlinear fault tolerant control(FTC) for the flexible arm with an active compensating unit. In control system structure, two SMA wires in parallel are unified an interactive actuator to govern the arm vibration displacement. SMA actuator-based nonlinear FTC system is designed by using operator-theoretic approach. Meanwhile, multiple feedback loops (MFLs) with an active compensation unit is to obtain the desired tracking performance, which the compensation unit is to eliminate the effect of non-invertible hysteresis factor from SMA actuator. The robust stability of the designed control system can be guaranteed with robust stabilization condition. When the unknown fault behavior of the actuator occurs, the fault tolerant characteristics can ensure the safety and reliability of the control system. Finally, the simulation cases verify the effectiveness of the proposed scheme under the normal and faulty states of the actuator. The results show that even if the one-sided actuator loses the input signal, the designed control system can still remain stable the arm vibration displacement, as well as has a good fault-tolerant characteristics for actuator faults. The proposed method not only can quickly the vibration suppression with less time but also with lower input energy. The effectiveness and reliability of the SMA actuator-based FTC system is confirmed in case of actuator faults.

Keywords: Nonlinear Control, Robust Control, Social Systems
Abstract: This paper addresses control design for mitigating the spread of infectious diseases among humans using vaccination, isolation, and contact regulation. This paper focuses on the robustness for disturbances perturbing all population classes in their full range and pursues effective feedback control using the number of recovered individuals. The proposed design is based on nonlinear control theory in which we use a Lyapunov function solely to achieve input-to-state stability semi-globally in the state space and globally in the disturbance spaces. To this end, the total population in the Lyapunov functions constructed by preceding studies is replaced by the recovered population. This paper illustrates how useful an entirely logarithmic Lyapunov function is to address all disturbances without restricting their magnitude.

Keywords: Robust Control
Abstract: This paper presents an improved admissibility analysis of singular time-delay system. The redundant matrix variables are diminished by the state decomposition approach that divides the singular time-delay system into differential equations and algebraic equations which results in the two parts of state vectors. Then, to obtain less conservative admissibility criterion, Lyapunov Krasovskii functional(LKF) that contains the state and its derivative term in double integral is constructed. Furthermore, additional state vectors are included to fully exploit system information. The admissibility criterion is formulated in linear matrix inequality and the effectiveness of the result is verified with some numerical examples in the literature.

Keywords: Robust Control, Adaptive and Optimal Control, Intelligent Systems
Abstract: A frequency-domain characterization of the solution to an Output feedback control, which have been formulated and solved by the present authors, is discussed. In the output feedback control the optimal state feedback law is supported to be determined in terms of minimum covariance matrix of the state vector. Without costing the control power, the problem is made well-posed by assuming state observation noise that effectively suppresses the control power. An inequality condition similar to the well-known circle criterion is derived as a necessary and sufficient condition for a state feedback law to be the solution to some output feedback control of the modified form.

Keywords: Robust Control, Intelligent Control
Abstract: This article presents the methods of identifying uncertain plants used for stability-certified reinforcement learning (RL). The uncertain plant is the interconnection of a perturbation and a nominal plant represented by a state-space model. By assuming that the perturbation is bounded, two types of methods are proposed to identify the uncertain plant. The first one is an optimization-based approach proposed for known nonlinear systems. The state-space model is given by solving an optimization problem of seeking matrices satisfying the bounded condition. The second method is a learning-based approach proposed for unknown systems. The state-space model is estimated by interacting with environments, which means that the second method is suitable for conjunction with stability-certified RL. In the numerical experiments, the identified uncertain models are used for stability analysis of feedback systems with a neural network controller. The results show that both feedback systems provide enough stability with similar regions of attractions (ROAs). This means that the learning-based method enables us to discuss the stability of neural network controllers even for unknown systems.

Keywords: Robust Control, Nonlinear Control
Abstract: In this note, we investigate the stability of feedback systems with idempotent nonlinearities. For the stability analysis of nonlinear feedback systems, the powerful framework of integral quadratic constraint (IQC) has been frequently employed where the core of this framework is capturing the behavior of nonlinearities by multipliers. However, the multipliers only grasp the rough behavior of nonlinearities such as slope-restriction and hence cannot distinguish each nonlinearity. To get around this difficulty, we focus on the fact that some nonlinearities frequently dealt with in relevant studies satisfy ``idempotence.'' By actively using the idempotent property, we show that we can augment the original nonlinear feedback system and hence enlarge the size (freedom) of the multipliers in IQC-based stability analysis. We finally illustrate the effectiveness of the new stability analysis condition by numerical examples.

Keywords: System Engineering
Abstract: The power generation from renewable energy sources, which is being promoted for mass adoption due to environmental issues, is affected by weather conditions, and therefore, it is necessary to predict the amount of power generation. In this study, we propose an algorithm for BEMS that takes into account the uncertainty of solar power generation using Tube-Based MPC, which is a type of robust MPC. We confirm through simulations that the algorithm is more robust against forecast errors by comparing it with a conventional method.

Keywords: Electrophysiology and Kinesiology, Virtual Reality Systems, Biological and Physiological Engineering
Abstract: This work aims to design a system capable of systematically assessing first-person and bird's-eye perspective conversion skills using an HMD, as well as to investigate the association between this ability and depth perception. It is hypothesized that the ability to turn first-person information into a bird's-eye view is crucial for making quick, appropriate judgements. An experiment was conducted with 12 experienced and 12 novice football players. They viewed randomly positioned player objects in a virtual football environment from a first-person viewpoint and then rebuilt them from a bird's-eye perspective. The individual's depth perception was also evaluated. Experienced players were able to rebuild the placements of player objects with greater precision than novice players, but there was no significant difference in depth perception. On trials involving 10 to 16 items, the experienced group had a markedly decreased completion time. However, there was no link between the results and depth perception. This suggests that those who are adept at transforming a first-person viewpoint into a bird's-eye view may not necessarily have great depth perception. Future research could explore these variables to gain a more comprehensive understanding of the relationship between viewpoint transformation and depth perception.

Keywords: Virtual Reality Systems, Human Interfaces
Abstract: In the current Motion-Less VR system, the skeleton that constitutes the joints is mechanically fixed to restrain motion in the real body. However, this method has a disadvantage: the skin sensations are constantly inputted at the fixed point. In this paper, we propose a method to restrain the motion of a real body using muscle electrical stimulation. Evaluation experiments of the proposed method showed that the method was effective in restraining the motion of the real body to a certain degree.

Keywords: Virtual Reality Systems, Human Interfaces, Human-Machine Systems
Abstract: This paper studies a design method of a virtual coupling (VC) including fractional derivatives for a haptic interface used in virtual reality technology. In the previous research, parameters of fractional derivatives in the VC were optimized, concerning the passivity property of measured real objects. However, as the sampling rate was fixed to a single value and the characteristics of discretization were restricted, it was difficult to match the passivity in a wide range of frequencies. For this issue, this paper proposed to use discretization with several different sampling rates for fractional derivatives, by combining the discretization terms with the low and high rates, the proposed method can realize adequate passivity through the wide range of frequency. Finally, free fall experiments and human tapping experiments are performed and the results show that the proposed method can generate better behavior than the previous method in a physical repulsion and a more similar haptic expression to a real object in a human tapping motion.

Keywords: Virtual Reality Systems, Human Interfaces, Modeling, System Identification and Estimation
Abstract: Motion-Less VR is a VR system that enables the control of a virtual body without requiring actual body motion. The system suppresses the motion of the actual body by immobilizing the body, measures the user's intention to move the body using sensors, and generates the movement of the virtual body using link-segment mode for visual presentation on an HMD. The current system does not allow users to perform the motion as users intend. One of the reasons for this is that the parameters used in the link-segment model of the virtual body, such as mass, a moment of inertia, and the viscoelasticity of joints, are not the original values of users. Therefore, we performed a personal adaptation of these parameters for each user and evaluated the effect of personalization on the motion control in this system. The results confirm that personalization may be effective in improving motor control.

Keywords: Virtual Reality Systems, Medical and Welfare Systems, Mechatronics Systems
Abstract: We are developing a hybrid device with active and passive features by combining two mechanisms: a soft actuator using air pressure and a brake using electro-adhesive gel. The goal is to realize effective rehabilitation by implementing this device that applies force sensation display technology, which is one of the VR (Virtual Reality) technologies. To guide the development of a hybrid force-display glove, this paper examines the results of controlling the internal pressure of a balloon actuator, which is intended to be used as an active element in a hybrid force-display glove, using a finger posture angle calculation with a bending sensor. As a result, the internal pressure could be controlled in response to the posture angle. However, It turned out necessary to reduce the sinking of the finger due to balloon softness and the instantaneous bounce of the finger due to rapid balloon inflation.

Keywords: Virtual Reality Systems, Robotic and Automation Systems, Simulation of Large Systems
Abstract: This paper describes a study on building a digital twin environment using point cloud data for mobile robots. A digital twin environment for mobile robots is a method to reproduce almost the same environment in a simulation space as if it were a twin, using data from an actual natural environment such as public roads. In fact, in the development of mobile robots, experiments on public roads are conducted, however, they are incredibly time-consuming and labor-intensive, so it would be helpful if a realistic simulation environment could be created. This study focuses on building a digital twin environment using point-cloud-data for mobile robots. In order to verify the effectiveness of this approach, we constructed the environment using data from a real robot that has been driven. The navigation of the mobile robot was performed in the constructed simulation environment, and it was possible to realize a navigation run in the driving environment that was almost the same as the run of the actual mobile robot.

Keywords: Electrophysiology and Kinesiology, Virtual Reality Systems, Biological and Physiological Engineering
Abstract: In this study, we developed a system to evaluate catching aptitude and conducted experiments involving athletes from both the open and closed skill domains. The study participants were classified into two groups: a high-skill group consisting of individuals with exceptional catching proficiency in open-skill ball sports and a low-skill group comprising those without catching training in closed-skill sports. The objective of this study was to ascertain the efficacy of a VR simulator as an instrument for discerning disparities in catching performance between two groups. The high-skill group exhibited superior rearward-catching capabilities and precise predictions of landing points compared with the low-skill group. These results suggest that a simulated catch system can be an effective means of measuring catch proficiency.

Keywords: Intelligent Control, Adaptive and Optimal Control
Abstract: The bipartite output regulation problem for a class of heterogeneous multi-agent systems with actuator bias faults is studied in this paper, where the dynamics of followers are completely unknown. To tackle such a problem, a kind of fixed-time distributed observers is proposed to learn the leader's dynamics and state. Then, a class of off-policy learning algorithms is developed based on the designed fixed-time observers to construct model-free fault-tolerant control schemes. It has been proved that the bipartite output regulation problem can be solved by the proposed fixed-time observer-based model-free fault-tolerant control protocols under some suitable conditions. Finally, the effectiveness of the presented theoretical results is demonstrated through performing numerical simulations.

Keywords: Intelligent Control, Adaptive and Optimal Control, Mechanical Systems Control
Abstract: This paper presents safe coverage control algorithms for multi-agent systems with time-varying uncertainties. This covers the multi-agent control problems like coverage control with obstacle avoidance. The coverage control prob-lem is concerned with allocating agents within an area of interest to optimize a coverage metric. An optimized allocationis achieved through centroidal Voronoi tesselation (CVT) coverage controller is constructed to realize the CVT. The obstacle avoidance problem requires a decentralized control strategy that guarantees collision-free maneuvers in an unknown environment. A control barrier function (CBF) based controller is developed to ensure collision avoidance taking into account the actuator fault, which would seriously affect the system performance. To verify the validity of the proposed controllers, simulator has been constructed under the python environment. The CBF based controllers have been verified under simulations.

Keywords: Intelligent Control, Network System Integration
Abstract: Leader-followers synchronization in networks of continuous-time Takagi-Sugeno (T-S) fuzzy multi-agent systems on a undirected graph containing a spanning tree is considered. Both state and output feedback controllers are designed. On the design of output feedback synchronization controllers, it is also shown that a property like a separation principle of linear systems is satisfied for synchronization in networks of T-S fuzzy multi-agent systems.

Keywords: Intelligent Control, Nonlinear Control, Modeling, System Identification and Estimation
Abstract: In recent years, the number of cases using neural networks for control methods such as MPC (Model predictive control) is increasing. By using a neural network, learning for modeling can be easily performed using target input/output data. However, such learning has the problem such as the learning result is a black box. In contrast, there is a method called PINNs (Physics-informed neural networks) that constrains the learning result by the governing equation. There are many examples in which this method treats time and position as continuous. Although there are few examples in discrete systems that are suitable for providing control methods such as MPC. Therefore, in this paper, we proposed a discrete-time PINN and performed learning and simulation for a double pendulum with complex time evolution. When we verified the prediction performance of time evolution using the trained model, we confirmed that there is a possibility to build the PINNs model for a complicated nonlinear system.

Keywords: Intelligent Control, Nonlinear Control, Process Control
Abstract: Data-driven control including V-Tiger has been actively studied in recent years. V-Tiger can predict the feedback loop response, but is sensitive to noise. Therefore, this paper introduces High-order ARX model identification and Confidence interval analysis to predict confidence interval of stability margins of control system designed by V-Tiger. The effectiveness is verified using pneumatic artificial muscle.

Keywords: Intelligent Control, Process Control
Abstract: Recently, with advancements in technology, modern factories have embraced advanced process control algorithms. There are several user-friendly simulated manufacturing environments, in which PID, Model Predictive Control and deep reinforcement learning (RL) algorithms can be used. The established dynamics models in these environments are of high-fidelity. However, RL algorithms can hardly learn a desirable control policy because of the simply defined reward function. This paper proposes a new reward function specifically for RL algorithms in a continuous stirred tank reactor simulation environment. Furthermore, this paper compares the experimental results using the existing reward function and the proposed reward function.

Keywords: Intelligent Systems, Adaptive and Optimal Control
Abstract: Multi-objective reinforcement learning (MORL) for robot motion learning is a challenging problem not only because of the scarcity of the data but also of the high-dimensional and continuous state and action spaces. Most existing MORL algorithms are inadequate in this regard. However, in single-objective reinforcement learning, policy-based algorithms have solved the problem of high-dimensional and continuous state and action spaces. Among such algorithms is policy improvement with path integral (PI²), which has been successful in robot motion learning. PI² is similar to evolution strategies (ES), and multi-objective optimization is a hot topic in ES algorithms. This paper proposes a MORL algorithm based on PI² and multi-objective ES, which can handle the problem related to robot motion learning. The effectiveness is shown via numerical simulations.

Keywords: Signal and/or Image Processing, Intelligent Systems, Transportation Systems
Abstract: In this study, we develop a step detection sensor system using a depth camera to realize a half-drone wheeled inverted pendulum that can climbing up/down steps. By detecting steps, we aim to accurately determine the timing to switch from movement control in a two-dimensional plane to step-climbing control. As the result, it can suppress the amount of overshooting after climbing over a step and perform static step-climbing. In this paper, we developed a detection system to recognize the ground and the step from 3D point cloud data obtained by the depth camera. The usefulness of the step detection system was verified using the half-drone wheeled inverted pendulum.

Keywords: Guidance and Flight Control, Mechatronics Systems, Robotic and Automation Systems
Abstract: This study shows how to prevent the rank deficiency in the thrust allocation matrix by giving each rotor of a 2-DOF tiltable coaxial rotor a difference in rotational speed to generate counter-torque. In addition, in order to avoid a singular attitude at a pitch angle of 90 degrees when moving along a wall, we propose a method of expressing the attitude angle of the UAV as a quaternion and controlling translational movement while maintaining the singular attitude and controlling the force through impedance control. The usefulness of this method is verified by simulating wall running in an environment that includes a wall model.

Keywords: Robotic and Automation Systems, Modeling, System Identification and Estimation, Transportation Systems
Abstract: This paper exposes the attempt to control a half-drone wheeled inverted pendulum during a climbing step movement. To balance the robot during the different step of the process, the robot relies on different command structures. The design of each command structure relies on LQR computation and phase portrait. Results are evaluated on the Coppelia software.

Keywords: Robotic and Automation Systems, Mechatronics Systems, Mechanical Systems Control
Abstract: For the mobile robot to move to the target position, it is necessary to safely avoid collisions with surrounding objects. In this study, we propose a new dynamic obstacle avoidance algorithm for mobile robots using AR markers and cameras. The proposed method predicts the trajectory from the change in the position information of the dynamic obstacle, and controls the velocity of the mobile robot so that the mobile robot keeps a certain distance from the dynamic obstacle and avoids collision. Simulation and experiments demonstrate the effectiveness of the proposed method.

Keywords: Biological and Physiological Engineering, Robotic and Automation Systems, Intelligent Control
Abstract: This study examined a method to control the transition of CPG periods by using the input signal of the feedback term, assuming the generation of gait of a leg-type robot. The CPG waveforms were stabilized by adjusting the input waveforms based on the original CPG waveforms in the numerical simulation. The more continuous the input signal is, the more stable the synchronization is. Next, the limit value for synchronization that allows periodic transitions was confirmed. The transition range is considered to cover the range used in robot gait. However, we found that the range of synchronization is wider during the transition, and that there is a condition in which synchronization is lost after a while when checking the signal at the pause. This result verifies and clarifies the range in which synchronization is possible even when the periodic transition is paused. In contrast, we verified the limit value for fixed-period input and compared it with the range of possible periodic transitions even after a pause and confirmed the existence of an effect on synchronization by periodic transitions. This shows the effectiveness of the method and clarifies the relationship between the responses.

Keywords: Integrative Biophysical Engineering and Informatics, Signal and/or Image Processing, Analytical Measurement
Abstract: Many aspects of the swimming characteristics of underwater living thing have not been elucidated. In particular, focusing on high-speed swimming like that of dolphins, this research proposes a new method for estimating the propulsive force of dolphin, with the aim of contributing to the development of propulsion mechanisms for underwater dolphin robot. A marker-less tracking tool is used to place multiple labels on a video of dolphins swimming, and tracking analysis is performed. All the coordinate information of the label of each frame is output in csv format for the tracked analysis results. For the estimation, the tail fin of a dolphin is regarded as an oscillating wing, and the two-point hinges oscillating wing theory is adopted to consider the force acting on the body of dolphin as the two-point hinges. By tracking analysis, we prepare the parameters necessary for propulsive force estimation, apply them to the vibrating wing theory, and obtain the propulsive force generated by th dolphin in the video.

Keywords: Autonomous Decentralized Systems
Abstract: In the formation flight of multiple UAVs, it is desirable to move autonomously and decentrally using the information obtained from the surrounding UAVs without a control tower. Therefore, this study adopts leader-follower control based on line-of-sight (LOS) guidance as a control method for formation flight. In leader-follower control using LOS, each follower can determine its control inputs based on the leader's position and velocity information. On the other hand, with the conventional control method, there is a possibility that the followers may collide with each other depending on the leader's movements. In this paper, we implement an algorithm to avoid this mutual collision and verify its operation by simulation.

Keywords: Multivariable Control
Abstract: The issue of this article is data-driven approach to systems and control. Particularly, we focus on data informativity based controller design for dissipative systems. Here, we provide a necessary and sufficient condition that only input-output data must satisfy to make a system dissipative. The key techniques of the main result are well known realization method for state space representation and our recent results on synthesis of dissipative systems in the data informativity framwork from the view point of algebraic approach.

Keywords: Multivariable Control, Adaptive and Optimal Control, Robust Control
Abstract: This short note proposes a generalization of 2DOF (two-degree-of-freedom) structure for tracking control, to the case where the target output for tracking is different from the measurement output. We generate an error signal for feedback from the measured output signal, thereby maintaining a good separation property between feedback and feedforward control designs, as is well known in the 2DOF structure.

Keywords: Multivariable Control, Computer Aided Design, Mechanical Systems Control
Abstract: Control design for multivariable systems is challenging because all transmission paths are usually affected simultaneously. Therefore, disturbance response decoupling (DRD) was developed to keep specific transmission paths fixed while improving others. However, improving system responses simultaneously and independently has yet to be discussed. This paper proposes a novel control theorem called multiple input disturbance decoupling (MIDD) to answer this question. We first simplify the DRD theorem as the input disturbance decoupling (IDD) lemma, which allows independent modification of input responses. We then develop the MIDD theorem, where multiple IDD designs can be integrated to shape all input responses simultaneously as the individual IDD designs. Finally, we apply the MIDD control to a quarter-car model and demonstrate its effects through simulation and experiments.

Keywords: Process Automation, Process Control, Components and Devices
Abstract: With the advancement of artificial intelligence (AI), modern industrial fault diagnosis has become a prominent area of research. Among them, PCA-based fault diagnosis has been widely applied across various industrial domains. However, the rapid progress in the industrial sector has revealed limitations of PCA in handling dynamic and time-varying data, rendering it unsuitable for deployment in industrial process control applications. The progress in machine learning and artificial intelligence has paved the way for the appropriate extension of traditional methods, expanding their practical applications in the real world. This paper presents an optimized adaptive iterative sparse PCA (OAISPCA) approach. By iteratively updating the sparse penalty term through an interior point-based method, adaptive sparsity is introduced into the original PCA method, thereby enhancing model interpretability and fault diagnosis accuracy. The effectiveness and advantages of this method are validated through its application to real-world industrial control valve data. The results demonstrate that OAISPCA significantly improves performance metrics such as fault detection rate (FDR) and false alarm rate (FAR).

Keywords: Multivariable Control, Network System Integration, Nonlinear Control
Abstract: In this paper, we propose a leader-follower consensus control method using state feedback gains and servo compensators for continuous time multi-agent systems with saturation nonlinearities. The consensus control method is that the leader follows reference inputs and the followers follow states of the leader without using the reference inputs. We point out that the proposed method based on the generalized sector approach can be recast as a convex optimization problem subject to linear matrix inequalities (LMIs) in order to increase the convergence speed of the consensus corresponding to an integral quadratic performance level. We clarify that our proposed LMI-based synthesis for the multi-agent servo systems is definitely helpful through numerical experiments.

Keywords: Robust Control, Multivariable Control, Computer Aided Design
Abstract: In this paper, linear-quadratic (LQ) mean-field social control for a class of stochastic systems with delay inputs are discussed. After defining a stabilization control problem based on the state feedback strategy, the problem of minimizing the upper bound of the cost function is solved using Karush-Kuhn-Tucker (KKT) conditions. The results show that the required strategy set can be obtained by solving stochastic cross-coupled matrix equations (SCCMEs). As a main contribution, Newton’s method is applied to SCCMEs, and quadratic convergence can be proven under the appropriate initial conditions. Finally, to demonstrate the effectiveness and usefulness of the proposed methodology, an academic numerical example with many decision-makers is considered.

Keywords: Process Control, Computational Intelligence, Simulation of Large Systems
Abstract: The geothermal power plants in Japan have a low plant capacity factor. In the geothermal power plant under study, a problem is that the pressure of the steam production wells frequently drops suddenly. The plant operators have recovered the steam production well to a stable state through the valve operation based on their experience when the well is unstable. However, the same operation, such as opening a valve, may result in a decrease in reservoir pressure which can be accelerated depending on the reservoir recharge conditions. The objective of this study was to examine wellhead valves operation to prevent sudden pressure drop. This study developed a machine learning (ML) model to predict time-series of steam enthalpy from inputs such as valve openings using Temporal Fusion Transformer (TFT) architecture. The ML model was confirmed to function as a simulator to predict the behavior of the steam enthalpy when the valve openings are varied. The ML model was also able to detect the rapid enthalpy decrease from 25 hours before the happened. Furthermore, we confirmed that the ML model can sequentially evaluate whether changing the valve openings stabilized the reservoir conditions. Future studies should validate and extend these findings from diverse perspectives.

Keywords: Mechatronics Systems, Robotic and Automation Systems, Mechanical Systems Control
Abstract: This study developed a four arms robot that unifies wheel-legged tripedal mobility, wheeled mobility, and quadarms manipulation, and this paper proposes a control framework integrating a motion generator, trajectory modification method for the angle, velocity, and acceleration constraints, and angle controller considering the torque saturation. For the mobilities and manipulation, the four arms have different mechanics and roles. The three DOF front arm has an active wheel used for the wheel-legs tripedal walking and wheel driving with passive wheels attached to the torso. The three DOF rear arms are series elastic arms used for the wheel-legs tripedal walking and the object grasping during the wheel driving. The two DOF upper arm is not used for the mobilities and used only for the manipulation.

Keywords: Medical and Welfare Systems, Signal and/or Image Processing
Abstract: Cardiovascular diseases are one of the leading causes of mortality. Advances in technology have improved the monitoring of patients. However, these devices are still sensitive to noise from movement, therefore it is important to understand how the movement affects electrocardiographic recordings. In this research, three devices were tested. The signal-to-noise ratio (SNR) was used to determine the quality of the ECG recordings from each device. The Vitalgram system was the only device to present a positive average SNR value for EMA while the subjects were running. In Apandi’s research the performance of several heartbeat detection algorithms was tested. Using Apandi’s research data and the SNR values from this research, the performance of these algorithms on recordings from these devices was estimated.

Keywords: Mechanical Systems Control, Human-Machine Systems, Nonlinear Control
Abstract: The paper proposes a bilateral system for the metal spinning process. The bilateral system has leader and follower systems composed of parallel link robots. Due to the structure of the bilateral system, it is necessary to design the controller in the workspace. The paper builds a nonlinear Kalman filter to estimate the motion information in the workspace from the joint space. The nonlinear Kalman filter is designed based on the nonlinear state-space equations represented by a neural network model. The paper shows the effectiveness of the proposed bilateral system with the simulation result.

Keywords: Electrophysiology and Kinesiology, Identification and Estimation, Medical and Welfare Systems
Abstract: There are a variety of models that have been proposed to represent the relationship between surface electromyographic potentials and ankle joint torque during isometric contraction. However, this model is not valid under isokinetic contraction. This study proposes a model in which the muscle contraction torque coefficient is a function of ankle joint angular velocity. The validity of the proposed model was verified by an experiment to evaluate the error between the measured ankle joint torque and the estimated ankle joint torque from the model.

Keywords: Robotic and Automation Systems, Mechatronics Systems
Abstract: There is a big demand on dexterous robots to replace human labors in the field of industry or welfare. The improvement of dexterity of a robot can be achieved by increasing the degree-of-freedom (DOF) of the robot. A parallel robot, which has a platform supported by multiple arms, is one realization of a high-DOF robot in a compact mechanism. However, it suffers from its small workspace caused by the singularity unique to it called static singularity, where the robot cannot generate force in a specific direction at the platform. In this paper, a static analysis of a five-bar planar parallel robot based on the decomposition of a force transmission matrix relating the input and output force is proposed. Additionally, this study shows how the actuation redundancy solves it. A local index evaluating the distance from the static singularity is introduced. Numerical studies are shown to compare the cases with/without the actuation redundancy and the evaluation is based on the local index in a workspace.

Keywords: Guidance and Flight Control, Adaptive and Optimal Control
Abstract: It is an important but difficult problem that the autonomous landing control of a quadcopter to a slope such as a deck of a ship. Model Predictive Control is a method for avoiding obstacles and controlling complex trajectories. In particular, the landing surface on a slope is subject to turbulence due to wave motion, so a wide range of inputs is required to achieve the desired performance. In this study, we solve the optimization problem in the Model Predictive Control by using the Monte Carlo method to achieve a landing to a static slope as a preliminary step on an oscillating surface. Numerical simulations were performed to confirm the behavior of the quadcopter in attempting to adjust to the slope angle and for deceleration.

Keywords: Signal and/or Image Processing, Identification and Estimation, Human-Machine Systems
Abstract: Surface Electromyogram (sEMG) is used for identification and/or estimation of human motions, because it is an electric signal that has muscle activities and is easy to measure noninvasively. The authors have been proposed a human motion angle prediction method using a neural network and feature-extraction-processed sEMG obtained in real time. In this paper, a method using whitening and feature extraction (FE) for multi-channel sEMG and a neural network as a prediction model is proposed. Experimental data were measured by a self-made system. sEMG sensors were attached on the biceps brachii (ch 1 to ch 4) and the triceps brachii (ch 5 to ch 8). A method to realize real time FE usin EMD of EMG and the way to realize whitening are described. Then, a prediction model combining with whitening and FE is proposed. Effectiveness of the proposed method is shown by the estimation results compared with the past proposed method and compared with the multi-channel inputs without whitening.

Keywords: Computational Intelligence
Abstract: Deep Learning has a hierarchical network architecture to represent the complicated feature of input patterns. In the previous research, the adaptive structure learning method of Deep Belief Network (Adaptive DBN) was developed, which can discover an optimal number of hidden neurons for given input data in a Restricted Boltzmann Machine (RBM) by neuron generation-annihilation algorithm, and can obtain appropriate number of hidden layers in DBN. In this paper, a new segmentation method using the Adaptive DBN was developed to extract lung tumor from 3D CT images. In the experiment, 156 cases collected by an open dataset in NSCLC Radiogenomics was used to evaluate our model. As a result, our model showed 0.884 dice coefficient for the test data, which was higher value than the 3D U-Net implemented on MONAI.

Keywords: Computational Intelligence, Intelligent Systems, Modeling, System Identification and Estimation
Abstract: Surrogate-assisted multiobjective evolutionary algorithms (SAMOEAs) are a promising approach for solving expensive multiobjective optimization problems (EMOPs), wherein the number of function evaluations is extremely restricted due to expensive-to-evaluate objective functions. However, most SAEAs are not well-scaled to high-dimensional problems because the accuracy of surrogate models degrades as the problem dimension increases. This paper proposes a dimensionality reduction-based SAEA, which involves the following two strategies to address high-dimensional EMOPs. First, mapping high-dimensional training samples to a low-dimensional space in building surrogate models can boost the accuracy of surrogate models. Second, compared to approximation-based surrogate models, reliable classification-based models can be obtained under a few training samples. Accordingly, the proposed algorithm is designed to integrate a dimensionality reduction technique into an existing classification-based SAEA, MCEA/D. It builds classification models in low-dimensional spaces and then utilizes these models to estimate good solutions without expensive function evaluations. Experimental results statistically confirm that the proposed algorithm derives state-of-the-art performance in many experimental cases.

Keywords: Computational Intelligence, Intelligent Systems, System Engineering
Abstract: Uncertainty quantification plays a crucial role in reduction of uncertainties during optimization and decision making, however, it is not solved yet in deep learning. Bayesian network is often used for uncertainty estimation but is only applicable to cases with a small number of parameters because the prior probability of the parameters is needed. On the other hand, while some non-Bayesian models have solved the parameter limitation problem, they often fail to separate different sources of uncertainties. In order to address these issues, we propose the Reduce Bias Stochastic Differential Equation Network (RB-SDENet) by adding a stochastic term to the existing ODE network, which enables us to capture epistemic uncertainty through the variance of random motion. And the probabilistic distribution of output can represent the aleatoric uncertainty for the model. Additionally, we ensured the stability of the model through the mathematical analysis of uniqueness.

Keywords: Computational Intelligence, Signal and/or Image Processing, Intelligent Systems
Abstract: Speech is the most direct method of human communication with a high level of efficiency, which contains a lot of information about the speaker’s feelings. The ability to recognize and distinguish between different emotions with sentences is a necessary component in intelligent applications of human-computer interaction (HCI). For the purpose of creating a more natural and intuitive way of communication between humans and automation control systems, emotional expressions conveyed through signal forms need to be recognized and processed accordingly. In this paper, the authors propose to appropriately apply parallel Deep Learning SENet, CNN block, and Transformer with Multi-head Attention method to effectively distinguish the features of different emotional states in the user voice recording data. The speech record samples from an open-source RAVDESS dataset were applied to assess the performance of the training model during the research. The highest results of the proposed model have achieved 82.67% of average accuracy on the test set.

Keywords: Computational Intelligence, System Engineering
Abstract: Metaheuristic algorithms require constraint handling techniques to solve constrained optimization problems. Our recent focus has been on multi-objective-based constraint handling, using constraint violation as an additional objective function. We extended Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) to handle constrained single-objective optimization and proposed MOEA/D with adaptive weight adjustment. To aggregate the objective function values and constraint violation quantities, scalarization functions are used with different weight vectors. However, when the scales of the objective function and constraint violation differ significantly, normalization is needed to improve the search's robustness. This paper indicates that excessive fluctuation in reference points of normalization leads to reduced search performance. Therefore, we propose a switching normalization method that updates/stops the reference points of normalization depending on the search situation. Finally, numerical experiments show that the proposed method enhances the robustness and performance of the search.

Keywords: Intelligent Systems, Computational Intelligence, Analytical Measurement
Abstract: In process plants, continuous anomalies can make operations unstable. However, the detection of continuous anomalies is more difficult than the detection of abrupt anomalies. In this study, we investigated the application of clustering analysis technique for the detection of continuous anomalies and developed a quantitative index for their evaluation. We then analyzed several plant operation data sets by using this index and demonstrated its effectiveness.

Keywords: Manufacturing Systems, Intelligent Systems, System Engineering
Abstract: We propose a new formalization for reactive scheduling. The formalization is based on a static view of the dynamic scheduling problem. The proposed formalization is able to show the optimal solution to the problem including schedule changes. Therefore, this model can be used to determine the performance of a solution with respect to the optimal solution. It may also lead to the proposal of new solution methods.