Keywords:
Abstract: In order to meet customer needs and requirements enterprises today form value creation networks among multiple enterprises and across multiple nations. Tight cooperation only succeeds if the involved enterprises share information. Such information may describe customer requirements, working processes or the delivered good (like intermediate products and components). Cost reduction and optimization in such international value adding networks can be achieved only if semantic interoperability is achieved. Interoperability among various enterprises and across nations can be based only on international standards. The Digital Factory Framework (DFF) (IEC 62832) provides a fundamental concept for sharing information among enterprises. It describes an approach that covers the life cycle of a production system from basic engineering to decommissioning. While the standard provides fundamental concepts and definitions the actual implementation needs to be based on standards which define data exchange formats like BMEcat, Asset Administration Shell (IEC 63278), Automation ML (IEC 62714), FDT (IEC 62453), FDI (IEC 2769) and OPC UA (IEC 62541). The information shared across a value creation network basically has 2 directions: Product requirement information is transmitted from customer to supplier of the final product and accordingly to the providers of product materials and components. Product description information flows from providers of product materials and components towards the supplier of the final product and to the end customer. Such product description information includes information about the delivered goods and may as well contain data from the production process (e.g. production conditions that influence product quality). Quality data of intermediate products may be used to optimize the following production steps and to meet the overall quality requirements of the product. An equipment supplier will have to be able to support the supply chain (when the equipment is the product) as well as to support exchange of information from the use of the equipment (when the equipment is used to produce another product). This contribution focuses on the flow of information towards the end customer and explores how semantic interoperability can be implemented and what it means for an equipment supplier. It is discussed which fundamental common requirements defined by the DFF apply to the different data models, how different data formats are used in the system life cycle and how semantic interoperability can be achieved between the different data models.

Keywords: Signal and/or Image Processing, Analytical Measurement, Identification and Estimation
Abstract: Carbon fiber reinforced plastic (CFRP) laminate composite structures have been used increasingly in aerospace and automobile sectors. Anisotropy of elasticity in CFRP, however, shows the prominent directivity of wave propagation governed by the fiber directions. Due to this anisotropic behavior, it is difficult to define the location of defects by using the arriving time of reflected signals. In this article, the elastodynamic response of anisotropic laminate composite structures subjected to a force loading is evaluated based on the integral representations in terms of Green’s function on Lp space. Unlike to the conventional migration method, the representation using Green’s function on Lp space maintains information about source and gives a quantitative near- and far-field analysis of generated waves. Several numerical analysis evaluate the differences the conventional migration techniques and the proposed wave-frontal inversion method with using the Green’s function on L^p space.

Keywords: Signal and/or Image Processing, Identification and Estimation, Opto-Electronic Measurement
Abstract: Magnetic Resonance Electrical Properties Tomography (MREPT) is a non-invasive technique for imaging electrical properties (EPs) inside the human body. % by noninvasive measurement. An issue of MREPT is that it takes a long measurement time to obtain high resolution EP maps required for medical diagnosis. In this paper, we propose a method to interpolate the amplitude of the magnetic field which requires long measurement time. For the interpolated field to satisfy the physical constraint of the magnetic field, the proposed method uses a reproducing kernel derived by the orthogonal bases of the Helmholtz equation. Compared to interpolation using a Gaussian kernel, the derived kernel does not need to tune a parameter. Effectiveness of the proposed methods was validated by numerical simulations, in which the proposed method reconstructed the EP maps in high resolution from the low resolution measurement data more accurately than using the Gaussian kernel.

Keywords: Identification and Estimation, Analytical Measurement
Abstract: Society 5.0 is characterized by the sophisticated integration of cyberspace with physical space, that is, cyber-physical systems (CPS), which are integrations of computation and physical processes. Embedded computers and networks monitor and control the physical processes, usually with feedback loops. Nishimura & the author have been applying category theory to describe an SoS architecture that is crucial to develop and operate an object SoS and to achieve sustainability. This paper introduces a universal formulation of measurement and sensing technologies based on the framework of category theory.

Keywords: Signal and/or Image Processing, Sensors and Transducers
Abstract: We are developing a new type of displacement sensor that is image-based, capable of measuring changes in 6DOF (3D position and orientation) of an object simultaneously, and is compact and low-cost. This displacement sensor measures the 6DOF of an object using images obtained by a monocular vision system. To confirm the usefulness of the proposed method, experimental measurements were conducted using a simple and inexpensive optical system. In this experiment, we were able to accurately measure changes of about 0.25 mm in displacement and 0.1 deg in inclination of the object at a distance of a few centimeters, and thus confirming the usefulness of the proposed method.

Keywords: Transportation Systems, Power Systems Control
Abstract: In order to find out the performance of intake air heating for low temperature cold start of diesel electric power unit, a thermal model of diesel engine intake system is established, the intake air temperature for low temperature cold start and the required intake air heating amount under different low temperature environments are determined, the heater matching is completed, and the heating time in different low temperature environments is estimated through energy consumption test. At the end of the paper, the matching and selection results of the intake grille are verified by the bench test of the diesel electric power unit, and the characteristics of the diesel electric power unit cold start at low temperature are explained.

Keywords: Adaptive and Optimal Control, Mechanical Systems Control, Power Systems Control
Abstract: In order to alleviate the energy crisis and environmental pollution problems, the electrification of the vehicle powertrain is a trend in the development of the future vehicle. Based on the key parameters of the vehicle powertrain system in the process of driving, this paper comprehensively analyzes the economic performance of the hybrid electric vehicle (HEV) powertrain system, and optimizes the torque design under the constraint condition of power performance. To solve this optimization problem, a novel second-order neurodynamic algorithm is proposed. In particular, the exponential convergence to the optimal solution is also considered in this paper. A numerical simulation of vehicle powertrain system is given, which shows the efficiency and global convergence of the proposed neurodynamic algorithm.

Keywords: Modeling, System Identification and Estimation, System Engineering, Robotic and Automation Systems
Abstract: With the rapid development of information technology, industrial equipment gradually develops in the direction of intelligentization, integration, and systematization. However, with the continuous updating and iteration of industrial equipment, the previous fault diagnosis methods can not be fully adapted to the current industrial equipment. This paper presents a fault diagnosis model based on a long short-term memory network (LSTM) for dedicated equipment fault diagnosis. First, the data is preprocessed according to the mechanism of the equipment. Then, the convolutional neural network (CNN) and LSTM are used to extract spatial and temporal features of the data, and Convolutional Block Attention Module (CBAM) mechanism combines the channel attention mechanism and spatial attention mechanism, which can better reflect the characteristics of the data. In this paper, the data collected by the dedicated equipment’s hardware in the loop platform are used to verify the model and compare the fault diagnosis model proposed in this paper with other neural network models. The results show that this method has higher accuracy.

Keywords: Robust Control, Nonlinear Control, Modeling, System Identification and Estimation
Abstract: To achieve accurate and rapid servo control of automotive electronic throttle while suppressing the overshoot phenomenon, a sliding mode control method based on reference governor (RG-SMC) is developed. A tracking differentiator, which serves as a reference governor, is fully utilized to smooth the reference trajectory. Meanwhile, the angular velocity of the throttle plate is also estimated by the tracking differentiator to suppress measurement noise. The simulation analysis verifies the excellent performance of the proposed RG-SMC in terms of control accuracy and rapidity as well as suppressing overshoot.

Keywords: Adaptive and Optimal Control, Mechanical Systems Control, Modeling, System Identification and Estimation
Abstract: The safety and comfort of autonomous vehicles are currently important research directions. As an evaluation indicator of vehicle comfort during driving, how to reduce the probability of motion sickness among passengers inside the vehicle has become a key research topic in the field of autonomous vehicles. This article proposes a novel method that considers the vertical stability of the vehicle and reduces the incidence of carsickness based on the active suspension of the vehicle. Active suspension, as a core part of the vehicle chassis-by-wire, plays a role in reducing ground roughness excitation and enhancing vehicle handling stability. Firstly, a dynamic model of the vehicle's active suspension was established based on the actual vehicle, and then an adaptive fuzzy PID algorithm was designed to optimize the performance indicators of the active suspension, such as body acceleration and suspension dynamic deflection. A quantitative model of the motion sickness mechanism was also established. By comparing different algorithms, it is shown that the proposed method can more effectively reduce the incidence of motion sickness among passengers in the vehicle. This control method can effectively improve vehicle comfort and contribute to the promotion and application of autonomous vehicles.

Keywords: Nonlinear Control, Adaptive and Optimal Control, Modeling, System Identification and Estimation
Abstract: Reasonable control of air flow rate plays an important role in the performance and life extension of polymer electrolyte membrane fuel cell (PEMFC). However, the complexity and coupling of the PEMFC make the control of the gas supply subsystem extremely difficult. Based on the simplified control model, a high-order fully actuated (HOFA) control scheme is proposed to address the nonlinear issues of the gas supply subsystem in PEMFC. The strict-feedback nonlinear system of PEMFC can be equivalently transformed into the HOFA model. A nonlinear adaptive tracking controller based on HOFA system is proposed, which is robust against the system disturbance. Finally, simulations are conducted to demonstrate the accurate steady-state tracking performance and strong robustness to disturbance of the proposed control method.

Keywords: Biological and Physiological Engineering, Components and Devices, Safety, Environment and Eco-Systems
Abstract: In the study of contact safety evaluation between the robot system and humans, a human dummy consisting of built-in sensors is a solution to obtain the internal physical field. A design of a finger dummy is proposed and fabricated based on the dimension and mechanical properties of human fingers. The thicknesses of the soft tissue are measured by applying an ultrasound device to determine the unknown dimensions of the phalanx. The coefficient of friction and viscoelasticity of the soft tissue dummy are investigated to approximate the human finger. Several unique surface treatment methods are applied to adjust the coefficient of friction. The viscoelasticity of dummy samples improved from a palm dummy is evaluated by obtaining the strain-stress relationship. These mechanical properties are effectively optimized by comparing the measurement results between the dummy samples and the human finger.

Keywords: Computational Intelligence, Signal and/or Image Processing, Integrative Biophysical Engineering and Informatics
Abstract: Monkeypox is an uncommon viral infection leading to skin eruptions resembling smallpox. Recent monkeypox outbreaks demonstrate the persistent danger presented by this virus. Accurate and timely diagnosis of monkeypox is important for the effective treatment and prevention of outbreaks. In this study, we propose an integration of feature selection algorithms for the deep features approach for the classification of monkeypox skin lesions. The deep pre-trained models (ResNet50, GoogleNet, and InceptionNetV3) are fine-tuned at initial stage. After that, deep model-based features are extracted and filtered by the feature selection algorithms. Finally, the selected features are then classified using traditional classifiers. The obtained results show that the classification selected of deep features achieved high performance and outperformed the original version of the pre-trained model. The highest performance metrics belongs to the case of ResNet50-based features and Grey Wolf Optimization giving 96.8%, 95.3%, 98.0%, and 96.5% in terms of accuracy, precision, sensitivity, and F1-score, respectively.

Keywords: Process Control, Modeling, System Identification and Estimation, Biological and Physiological Engineering
Abstract: Biopharmaceuticals are used in the fields of oncology and autoimmune diseases, and the market has expanded drastically in recent years. In the biopharmaceuticals production system, animal cells must be used to efficiently express antibodies. However, from a control perspective, the cell culture process must address the choice of batch or continuous production processes, the exponential growth of cells with large delays, and the realization of an operation that ultimately yields the maximum amount of antibody. To address this issue, a digital twin model of the cell culture process is required. Since the metabolic mechanism is not enough understood in biopharmaceutical production, a physical model based on principle cannot adequately represent the process, and a hybrid model combined with a physical model and data-driven model is required. In this paper, we propose a production system for digitalization of biopharmaceutical production in future. As the first step toward digitalization, we report the construction of a data acquisition system for modeling in a perfusion cell culture system.

Keywords: Sensors and Transducers, Identification and Estimation, Medical and Welfare Systems
Abstract: We develop a new hand sensor device that prevents sensor malfunction owing to bending of the palm and corrects the output value considering the hardness of the palm. From the load and posture information on the hand measured using this sensor, we attempt to estimate the measured electromyography (EMG) value, that is the muscle action potential of the lumbar region measured using the myoelectric potential sensor using deep learning. The estimated value and EMG are in good agreement in the actual measurement by the vertical movement of the luggage.

Keywords: Guidance and Flight Control
Abstract: This paper proposes an equilateral tetrahedron formation configuration initialization strategy for space-based gravitational wave observatory (GWO) near a libration point in the Sun-Earth circular-restricted three-body problem (CRTBP). In order to observe continuously gravitational waves (GWs), a stable equilateral tetrahedron formation configuration is required. For this purpose, the output regulation theory is applied. Using the tracking aspect of the theory, an equilateral tetrahedron formation is realized. Finally, the Sun-Earth CRTBP and the Lagrange point L_1 are considered to show the effectiveness of the control method.

Keywords: Guidance and Flight Control, Robotic and Automation Systems
Abstract: The demand for swarm technology has been rapidly rising since a swarm of robots can overcome the ability of large single robot. The heterogeneous group of swarms are applicable and robust for various missions and disturbances which will make the system to achieve higher performance. In this paper, we propose a set of control law and evaluation technique to separate the swarm with heterogeneous vehicles into groups of balanced number vehicles with different abilities. The results show that the proposed control law was able to separate the swarm into balanced group without using centralized system.

Keywords: Guidance and Flight Control
Abstract: Further development of unmanned aircraft is expected under the revision of related guidelines in Japan, and research on this field is rather flourishing. Proportional navigation, which is a guidance law for moving vehicles, is one of the well-known guidance laws that are expected to be utilized in various fields for aerial vehicles. Biased proportional navigation, which is derived based on proportional navigation, is often used as an specified angle-constained guidance, whereas compensated proportional navigation is used as a guidance law to capture the target while adapting the speed change. In this study, we apply the velocity compensation to a rigid body guidance and control problem for a small multicopter unmanned aerial vehicle (UAV), and investigate the efficacy of vertical landing guidance and control for the UAV through landing simulations while considering the velocity change and specified angle approach.

Keywords: Analytical Measurement, Identification and Estimation, System Engineering
Abstract: An approximate orbital elements ( state vector ) analytic model for Earth-based range measurements is presented and is used to derive a representative analytic approximation for differenced Doppler measurements. The analytical models are tasked to investigate the ability of these data types to estimate spacecraft geocentric angular motion, the station’s clock and frequency offsets, and signal-path calibration errors over a period of a few days, in the presence of systematic station location and transmission media calibration errors. Sensitivity analysis suggest that a few delay calibration errors are the dominant systematic error source in most of the tracking scenarios investigated; as expected, the differenced Doppler data were found to be much more sensitive to some calibration errors than difference d range. In this paper, it is described sensitibity analysis for orbit estimation by the analytical model.

Keywords: Relationality-Oriented Systems Design, Social Systems, System Engineering
Abstract: This research regards the local community as a composition of three elements, "Hito," "Mono," and "Koto," and the relationships that connect them, and has sought ways to revitalize the local community by putting them into a system. Specifically, based on a community system design called the Gift & Circulation model, we considered the impact of individual factors on the community by giving the model the individual's gender, age, role, and so on. We have been researching two axes: theoretical experiments using simulations and field experiments using applications. In last year's new development, we focused on the "activity rate" of the experiment participants based on the results of the field research. We considered the correlation between the regional activity rate and the stability of the model. However, it still needs to be determined what factors determine this activity rate. Therefore, this time, we searched for the activity rate, and why it causes differences in community activities even if the activity rate is the same based on the distribution of egoistic and altruistic people in the region. At the same time, we also consider an algorithm for increasing altruistic people in this paper. Modern people easily clear the physiological needs in the hierarchical desires advocated by Maslow, but the increase in social and self-actualization needs is remarkable. At the root of these desires is Eusytheia, which means peace and harmony in the human heart. In this paper, we consider

Keywords: Intelligent Systems, Computational Intelligence, Transportation Systems
Abstract: This study proposes a deep reinforcement learning mechanism to obtain cooperative driving control of autonomous vehicles at a roundabout, one of the intersections without signal control. This study introduces three new mechanisms to the previous model that enable learning the cooperative control: (i) gradual learning by changing the new vehicle departure interval, (ii) utilization of information about the vehicles' destination, and (iii) additional penalty for approaching walls and other vehicles. We conducted simulation experiments to investigate the effectiveness of the proposed methods. The experimental results showed that the proposed methods enable the acquisition of cooperative vehicle control that can safely navigate a roundabout while reducing the collision rate.

Keywords: Relationality-Oriented Systems Design, Social Systems, Intelligent Systems
Abstract: The COVID-19 pandemic has led to increased isolation and loneliness among older adults, who may find it challenging to stay motivated to engage in physical activity such as walking. To address this issue, this study proposes a human-centric approach to technology that incorporates mechanisms to promote self-motivated behavioral changes. Specifically, the study introduces a new step ranking system that allocates points differently depending on the individual and situation. This system aims to promote equitable interaction between older and younger individuals and encourage regular physical activity and socialization among older adults. The proposed system takes into account the psychology and consciousness of individuals and aims to provide an attractive and engaging incentive to motivate older adults to engage in regular physical activity and communicate with others. The multi-agent-based simulation conducted in the study supports the effectiveness of the proposed step ranking system in improving social activity and promoting self-motivated behavioral changes. Overall, the proposed system has the potential to mitigate the negative impacts of COVID-19 on the mental health and well-being of older adults. By promoting equitable interaction between individuals of different ages and physical conditions, the system can encourage older adults to engage in physical activity and socialization, ultimately promoting better health outcomes and reducing social isolation.

Keywords: Relationality-Oriented Systems Design
Abstract: We aim to create a platform where people can have a new reading experience different from that by animating books as living matter. Based on the concept that reading is communication between people and books, we postulate not that reading is a one-directional act to interpret and understand the contents of a book but that reading is bi-directional interaction between them to enable an individual reader to grow. For that purpose, we propose to animate books and readers’ reading notes as agents and to create an ecological environment consisting of such agents where people could experience imaginative and stimulative interactions with such agents as proxies of books and readers’ reading notes. Furthermore, this paper describes a simulation design to verify the proposal’s effectiveness in advance.

Keywords: Social Systems
Abstract: We have been working on simulations for community system design introducing relationality assets that people in a community generate through interactions with other people, “Mono,” and “Koto,” and modeling their gift and circulation in the community. In simulations, agents as models of residents generate behaviors related to community-based activities and change their behaviors based on the gift and circulation model of relationality assets. However, due to the current simulation model that employs a non-realistic parameter-based behavioral generation and change model, we could not achieve plausible dynamics between agents and community-based activities. This paper proposes a new simulation model that enables dynamic and situated be-havioral changes in people in community-based activities.

Keywords: Adaptive and Optimal Control, Robotic and Automation Systems
Abstract: Coverage path planning (CPP) of a cleaning robot, ground inspection robot, etc. needs to cover the entire target working area. Due to the limited capacity of the battery of the robot, an energy-optimal solution is expected for the CPP problem. This paper presents a method for improving the online path planning approach called Turn-away Starting Point (TASP). The robot improves energy-efficiency in an unknown environment by the optimal trajectory generation method for short running time. Furthermore, energy consumption is measured to compare with offline CPP. The occupancy grid map is used to real-time display of the motion where the real robot performs the coverage motion experimentally.

Keywords: Robotic and Automation Systems
Abstract: Motion planning for obstacle avoidance is one of the essential capabilities for autonomous navigation by mobile robots. We have thus far proposed a motion planner based on CNN with an LSTM block through mediated perception. As a result, a mobile robot based on the motion planner was enabled to avoid a walking person as a dynamic obstacle. In this paper, the robot further plans different avoidance motions depending on the velocity of the dynamic obstacle. For this challenge, an obstacle state classifier based on CNN is used ahead of the motion planner. A depth-difference image generated from two depth images is used as the input to the classifier. A classified state that indicates the velocity of the obstacle is fed as the input to the following motion planner. Finally, navigation experiments show that the robot based on the motion planner with the obstacle state input is able to plan different avoidance motions for a person walking slowly or fast through the obstacle state classifier.

Keywords: Robotic and Automation Systems
Abstract: In recent years, civil engineering and construction structures such as bridges and tunnels are aging, and periodic inspections are becoming necessary. Therefore, robotics is expected to inspect bridges more efficiently and safely, and robots for inspection of civil engineering and construction structures are widely researched. In this study, we propose a combination of a propeller mechanism and an EPM (Electro Permanent Magnet) wheel to allow the robot to move on bridges of different materials. On concrete and other parts, the robot is driven by a propeller. When it detects that the bridge material is iron, the propeller is turned off and moved by the magnetic force of the EPM wheel.

Keywords: Robotic and Automation Systems, Intelligent Control, Computational Intelligence
Abstract: This paper presents an autonomous floor navigation control system for a mobile robot that uses elevator button recognition with deep learning. The proposed system utilizes a deep neural network to recognize elevator buttons, enabling the robot to operate elevators independently and navigate between floors. The system is trained on a large dataset of button images, allowing for accurate recognition of elevator buttons. Additionally, the robot is equipped with sensors to detect and avoid obstacles, ensuring safe movement. The proposed system is tested in a real-world environment and demonstrated high accuracy and reliability in navigating between floors. The results show that the system can be used successfully to transport goods between floors in a timely and efficient manner, making it a promising solution for inter-floor transportation in multi-level buildings, where autonomous floor navigation is required.

Keywords: Robotic and Automation Systems, Mechanical Systems Control, Mechatronics Systems
Abstract: This paper aims to achieve the trajectory-tracking of an autonomous wheeled mobile robot (AWMR) using the proposed PD controller. At first, a complete model of the AWMR is established incorporating kinematics, dynamics and actuator models. Then, a desired circular trajectory is planned to be tracked. The motion control is attained via the proposed proportional and derivative controller (PD). To investigate the feasibility and robustness of the proposed controller, simulations and experiments are conducted under two different conditions. First case is an initial point of the robot INSIDE the desired trajectory and second case is an initial point OUTSIDE the desired trajectory. The results show that the implemented PD controller leads to excellent control performance under simulations and experiments even in the presence of frictional torques.

Keywords: Discrete Event Systems
Abstract: Control of complex networks such as gene regulatory networks is one of the fundamental problems in control theory. A Boolean network (BN) is one of the mathematical models in complex networks, and represents the dynamic behavior by Boolean functions. In this paper, a solution method for the finite-time control problem of BNs is proposed using a binary decision diagram (BDD). In this problem, we find all combinations of the initial state and the control input sequence such that a certain control specification is satisfied. The use of BDDs enables us to solve this problem for large-scale BNs. First, after the outline of BNs and BDDs is explained, the problem studied in this paper is given. Next, a solution method using BDDs is proposed.

Keywords: Modeling, System Identification and Estimation
Abstract: This paper proposes an input and output signal recovery algorithm for unknown nonlinear systems. The proposed algorithm assumes that an unknown nonlinear system can be approximated with k piecewise affine models and recovers input and output signals by applying a matrix shrinkage algorithm to Hankel matrices of piecewise affine models. In the algorithm k-means clustering minimizes distances defined by right singular vectors and partitions Hankel-like matrices into k clusters.

Keywords: Social Systems, Nonlinear Control, Modeling, System Identification and Estimation
Abstract: In this paper, we study the problem of optimally aggregating individuals' private knowledge in social influence networks by designing their interpersonal influence structures based on their opinions. Individuals interact their opinions on an unknown truth in round by round discussion with their initial opinions in each round being independent random variables associated with their expertise. We propose a mechanism to design the relative interaction matrix with sparse property according to their expressed opinions. We prove that with this mechanism, individuals' opinions achieve consensus and the collective opinion achieves its optimum as the number of the discussion rounds increases.

Keywords: Nonlinear Control, Mechanical Systems Control
Abstract: This study proposes a nonlinear system control method that can cope with time delays and disturbances that commonly appear in practical systems. The proposed method is based on an optimal control method based on a trajectory database generated by integrating Hamilton's equation in reverse. By combining state predictive control and a disturbance observer, the method effectively copes with time delays and disturbances. The proposed method is applied to an experimental quadcopter, and its effectiveness is particularly pronounced during flipping operations, where nonlinearities are strong and the impact of disturbances and time delays is significant.

Keywords: Identification and Estimation, Nonlinear Control, Mechanical Systems Control
Abstract: In this paper, we verify a nonlinear system identification method that extends the subspace state-space identification using deep learning and model predictive control based on the obtained model on a real system. In applying this series of methods to a real system, the challenge is to generate informative input/output data and to decide the dimension of state for identification. To reduce computation time for model predictive control have also become issues. Therefore, this paper proposes a solution to these issues and demonstrates its effectiveness by applying it to an experimental front-wheel steering vehicle.

Keywords: Sensors and Transducers, Mechanical Measurement, Standard of Measurement
Abstract: In recent years, MEMS sensors have been used for observing small pressure fluctuations due to their improved performance. However, as these sensors are often used in environments with varying temperatures, it is crucial to know their temperature dependence in addition to their response performance. In this study, we conducted a comparative evaluation of Bosch Sensortec's MEMS barometric pressure sensors, widely employed in various applications. Firstly, the sensors were placed in a thermostatic chamber to evaluate their temperature coefficients. Then, their response performance was evaluated by mounting them onto a linear actuator and subjecting them to vertical movement. Striking a balance between response performance and noise reduction, an IIR filter was employed, and the output response was examined using different filter coefficients.

Keywords: Identification and Estimation, Sensors and Transducers, Signal and/or Image Processing
Abstract: This study contributes to develop the virtual surgical training simulator with chiseling a hard tissue using a chisel and mallet. For increasing a sense of reality in the simulator, it is required to model precisely the actual chiseling motion. Thus it is necessary to measure the actual chiseling motion. In this study, we develop the state estimation system of chiseling motion using the sensor fusion technology with LiDAR camera and IMU sensor. The posture angles and accelerations of the chisel can be detected by IMU sensor, and the displacement and velocity of the chisel can be detected by LiDAR camera. These detected signals are integrated systematically by the extended Kalman filter approach for estimating precisely the displacement and the velocity of the chisel. The efficacy of the developed estimation approach of chiseling motion was verified by the experimets.

Keywords: Standard of Measurement, Mechanical Measurement, Sensors and Transducers
Abstract: We developed a rotary-motion type microforce generating machine for establishing an essential microforce measurement traceability. Referring to the principle of the Kibble balance, microforce can be generated using electromagnetic force. Repeatability evaluation of a microforce measuring device using the microforce generating machine was performed as an indispensable part of uncertainty evaluation of microforce measurement. Relative repeatability of ten measurements using 200 mN transducer at 10 mN and 20 mN force step reached to 10^-4 order despite of a mismatch between capacity and force steps.

Keywords: Modeling, System Identification and Estimation
Abstract: In recent years, model-based development has been attracting attention in various fields and it is expected to shorten development time for products. In particular, a model that takes into account the effects of friction in various parts are necessary for a table drive unit of a machine tool, which requires high positioning accuracy. In this study, a model of a moving table driven by a ball screw was developed with friction model, an experimental method is proposed to identify the model parameters such as the spring constant and the friction of each part in detail. Then, the validity of the model was evaluated by comparing experiments and simulations.

Keywords: Mechanical Measurement
Abstract: The feed drive system for machine tool consists of rolling elements such as ball screw and linear guideways. It is well known that in the　positioning of linear guideways and ball screw using steel ball rolling, the feed drive system has nonlinear spring characteristics. This phenomenon is deteriorating the accuracy of the machine tool. In this study, we have manufactured a feed drive system using rolling linear guideways as the guide and ball screw as the actuator. We measured the responses and torque (means driving friction in this paper) to some microscopic displacement for the feed drive system. This paper presents the friction behavior transition of microscopic displacement.

Keywords:
Abstract: Artificial intelligence (AI) technology has made remarkable strides, yet challenges persist in enabling robots to perform diverse tasks using a single hand. Our research proposes a groundbreaking approach called "deep predictive learning," which draws inspiration from predictive coding in neuroscience to overcome these challenges. In this plenary talk, I will unveil the remarkable outcomes of our robotics research employing deep predictive learning. Through compelling examples, I will demonstrate how this model empowers robots to surpass limitations and accomplish complex tasks. Moreover, I will showcase successful collaborations with multiple industry partners, highlighting the transformative potential of joint research endeavors. I also present an overview of our Moonshot project, "AIREC," a cutting-edge smart robot supported by the Japan Cabinet Office. This project represents a visionary leap forward, leveraging deep predictive learning and state-of-the-art engineering to redefine the possibilities of robotic intelligence.

Keywords: Intelligent Systems, Intelligent Control, Robotic and Automation Systems
Abstract: The purpose of the research is to apply reinforcement learning to the temperature control of a refrigeration system as well as reducing the power consumption. The suggested approach has two kinds of agents, and they control the compressor and the expansion valve at the same time. An exact model of a refrigeration system is configured based on the Model-Based Development method, and the corresponding simulator is used for generating various kinds of training data for reinforcement learning. Through some experiments, we verify the efficiency of reinforcement learning approach, and it can achieve maximally a 9.54% reduction in power consumption while having almost the same ability to control the temperature. As future work, the accuracy of temperature control should be improved, and the suggested approach should be applied to a wide variety of control requirements.

Keywords: Robotic and Automation Systems, Autonomous Decentralized Systems, Transportation Systems
Abstract: This study proposes a cooperative transportation system, which uses multiple autonomous mobile robots with different wheel types cooperating together to transport a rigid object. The system uses a leader-follower formation control strategy, by using the non-holonomic leading the way while the holonomic AMRs follow. The object is assumed as a constraint between the robots, and the cooperation is tested using a designed destination point, in which each follower robot receives commands from the leader sent through the laptop. To walk straight, all robots receive the same command, but for rotating, leader robot must evaluate the command for the follower robots by the designed method. The Robot Operating System (ROS) is used for the development of the robots and for standard communication. The proposed method is validated through simulation tasks using autonomous mobile robots with different wheel types. The results of the experiments have resulted and supported that holonomic and non-holonomic robots being able to cooperate with each other’s in transportation.

Keywords: Intelligent Systems, Signal and/or Image Processing, Computational Intelligence
Abstract: Earthquake detection is crucial for seismologists to study the Earth's crust and provide early warning systems to mitigate earthquake disasters. In recent years, deep learning techniques such as Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks have been applied to detect earthquakes from seismic signals with promising results. In this paper, we present a comparative study between CNN and LSTM networks for earthquake detection using a dataset of seismic waveforms. Before inputting the signals into the models, the seismic data were preprocessed using the Hilbert transform and Butterworth filter before being fed into the models. The performance of the models was evaluated using metrics such as accuracy, precision, recall, and F1-score.

Keywords: Transportation Systems, Adaptive and Optimal Control
Abstract: Railway level crossing often exhibits long queues and spillbacks due to the temporary closure of the railroad gate or when many vehicles arrive simultaneously. Existing research deals with traffic congestion issues at level crossings through architectural upgrades, traffic signal control, and other safety analysis. We propose an optimal vehicle control method to address the problem without infrastructure changes. Specifically, we plan vehicles' optimal trajectory to arrive from a suitable distance to smoothly reach and stop at the railway crossing at a designed time to reduce queuing and idling at the level crossing stop line. An extended data-driven model is used to predict the natural arrival timing at the crossing line, which is used as the prediction horizon of the optimal vehicle control problem, ensuring a safe gap with the preceding vehicle. Our optimal control method can prioritize safety constraints, showing improved fuel efficiency and reduced idling and traffic spillovers at our chosen study area compared to traditional driving methods in existing scenarios.

Keywords: Robotic and Automation Systems, Human-Machine Systems, Human Interfaces
Abstract: This research aims to develop an adaptable and advanced human-robot interaction system for collaborative mobile robots. A delta manipulator with a series elastic actuator is designed as a collaborative medium between humans and mobile robots. The design of the delta manipulator as a human-robot interaction interface and its kinematics are presented. Three control strategies for translational motion and two control strategies for rotational motion are studied and discussed based on their advantages and disadvantages, depending on specific application requirements. This design approach enables the creation of a comprehensive controller system that can effectively command the mobile robot to perform a wide range of movements and maneuvers, enhancing its overall performance and versatility. The resulting system efficiently accomplishes complex tasks in various scenarios, making it a valuable tool for a range of applications.

Keywords: Nonlinear Control, Robust Control, Adaptive and Optimal Control
Abstract: This paper provides the efficient design of robust time-synchronized control for disturbed Euler-Lagrange systems. The original design method required that the parameters were decided individually, but how to choose suitable parameters has not been given so far. The proposed design is formulated as LMI criteria that lead to the standard super-twisting algorithm. The new criteria reduce the design effort significantly. The simulation on two-link manipulators demonstrates the effectiveness of the proposed design.

Keywords: Adaptive and Optimal Control, Robust Control
Abstract: This study is concerned with a control system design method with frequency response data named a finite number of frequency responses (FNFR) model. In this paper a numerical descent direction is introduced and an iterative method for solving the control problem is proposed with it. Our approach searches controllers from the outside of feasible regions of considering control problem. Hence one feature of our method is that any controller can be used as initial point. The efficiency of our method is shown by numerical examples.

Keywords: Adaptive and Optimal Control, Modeling, System Identification and Estimation, Multivariable Control
Abstract: This study provides a secure design method for networked control systems. Since the encrypted controller is determined directly from encrypted control data, both the controller data and the process data are protected from eavesdropping.

Keywords: Adaptive and Optimal Control, Nonlinear Control, Robust Control
Abstract: The previous work has presented an event-triggered self-repairing control system (ETSRC) that utilizes a detector and an auxiliary signal to detect sensor failures within a prespecified time. Since a dynamic detector (detection filter) was beside the controller, data from the controller to the plant always were sent. This paper presents a new ETSRC in which the detector is introduced to the plant side to reduce the number of two-way data transmissions.

Keywords: Adaptive and Optimal Control, Intelligent Systems
Abstract: This paper concerns an adaptive linear quadratic control for discrete-time linear systems through reinforcement learning, using actor-critic structure based on a policy iteration algorithm to achieve optimal control performance. Whereas the existing policy iteration algorithm with actor-critic structures focuses on deterministic cases, the paper extends the existing approach to the case where the stochastic disturbances are present. The main features of the proposed method is to introduce the expectation of influence of stochastic disturbance into the policy evaluation, and employ recursive least squares method with a forgetting factor in order to deal with large number of data. Simulation results demonstrate the effectiveness of the proposed algorithm in controlling discrete-time linear systems in the presence of stochastic disturbances. The proposed control has the potential to contribute to the development of optimal control strategies for real-world applications where stochastic disturbances are present.

Keywords: Autonomous Decentralized Systems, Relationality-Oriented Systems Design, Modeling, System Identification and Estimation
Abstract: In this study, we aim to classify various types of multi-agent systems, such as groups of animals, moving robots, and so on, based on their trajectory data. Generally, the number of agents varies between different systems, making it difficult to use the data as a direct input for a neural network classifier. To solve this problem, we develop a regression model whose dimension of parameters is constant despite the number of agents and use the parameters of the model as input data of a neural network classifier.

Keywords: Adaptive and Optimal Control
Abstract: Adaptive output feedback control based on ASPR properties of the system with an adaptive predictive control as a feedforward input has been proposed for linear continuous-time systems. The designed control system can guarantee stability and keep robust and higher control performance with input limitations even though the systems are uncertain. This paper proposes an adaptive predictive control strategy, which maintains the stability of the control system without imposing the input limitation. In the proposed method, we can obtain a stable control system for uncertain systems by estimating the unknown parameters. The stability of the proposed method is analyzed and its effectiveness is confirmed through numerical simulations.

Keywords: System Engineering, Intelligent Systems
Abstract: K-nearest neighbor method, Kalman filter, and Data-Oriented Smart Adaptive Control have been proposed as methods for automatic detection of control performance degradation. However, these schemes may not be applicable when the data dimension is high, or the model accuracy is low, and human detection is more accurate in such cases. In this study, the detection of control performance degradation more quickly and accurately using CNN is considered for time series data. Then, the effectiveness of the proposed scheme is confirmed by numerical examples.

Keywords: Modeling, System Identification and Estimation, Identification and Estimation
Abstract: We have proposed a method for converting finite-length time series data converging to a steady-state value into the frequency domain. However, its frequency resolution depends on the data length, and the length may not be sufficient to obtain its frequency characteristics when it is short. This paper gives a method to improve the frequency resolution.

Keywords: Adaptive and Optimal Control, Modeling, System Identification and Estimation, Nonlinear Control
Abstract: This paper presents a novel method for detecting communication anomalies in event-triggered LQI control systems using a neural network (NN). In this method, the NN predicts triggering times, and communication anomalies can be detected based on an error between actual and predicted triggering times. Furthermore, this paper demonstrates the effectiveness of the proposed method by comparing it with our previous detection method through numerical simulations.

Keywords: Components and Devices, Advanced Computics
Abstract: To realize the digital transformation of the manufacturing industry, it is necessary to utilize the large amount of information generated in the field as data. Edge computing reduces the burden on cloud system resources and addresses bandwidth limitations and latency issues by processing data in the field and sending only valuable data to cloud systems. Edge computing systems require more sophisticated components at the field to be able to effectively perform processing, storage, and data collection. To support this, Toshiba Infrastructure Systems & Solutions Corporation has developed the slim type industrial computer FA2100TX model 700 which uses a high-performance CPU architecture for improved processing performance.

Keywords: Process Automation, Factory Automation, Process Control
Abstract: This paper describes the concept, architecture, components, features, and advantages of Software Defined DCS (Distributed Control System), which is attracting attention in the field of industrial process control system in response to the trend toward DX (Digital Transformation). Existing DCS uses hardware-based distributed control system, but there are increasing needs to utilize on-site data, improve real-time performance, and monitor and control in remote environment to realize DX. The needs for digitalization in the field are increasing, and to meet these needs, Toshiba Infrastructure Systems & Solutions Co. has released a new product, the Unified Controller Vm Series typeL. Software Defined DCS (hereinafter referred to as SD-DCS) virtualizes the dedicated hardware and firmware portions of existing DCS, and integrates controller and computer functions. It features reliability, support for information model, and the ability to be inherited from existing system. It is also compatible with cloud engineering environment, making it possible to meet customer needs for remote monitoring and control at low cost. By providing SD-DCS to society, we promote the realization of DX for our customers.

Keywords: Manufacturing Systems, Process Automation, Factory Automation
Abstract: We report a feasibility study of realizing carbon neutral society by smart industry energy management systems. We describe the purpose of this proposal and approach. The approach consists of 1) Creating the information models of energy consumption data for each equipment in the plant, 2) Utilizing data cooperative platform, 3) Creating a testbed by independent organization, and 4) Proposing the interface of the information models as international standard. Then we introduce requirement and proposed solutions.

Keywords: Manufacturing Systems, Process Automation, Factory Automation
Abstract: We have been conducting the research of device data application on trusted data platform Gaia-X for decarbonization in industry and developing the proving test system. We already developed the MES study part of the proving test system as phase1. For phase2, we report a preparation study of latest FDT technology implementation which is called FDT Unified Environment (UE). Firstly, FDT UE architecture relating with ISA95 level is discussed. Then, architecture of FDT UE implementation for both FA and PA side of the proving test system is introduced. We categorize the FDT UE use cases to analyze the actual plant floor use cases, for decarbonization in industry using the trusted data platform Gaia-X.

Keywords: Safety, Environment and Eco-Systems, Innovative Systems Approach for Realizing Smarter World, Manufacturing Systems
Abstract: MONODZUKURI in Japan continues to evolve through technological innovation and DX, and will contribute to the realization of a more sustainable future based on GX (Green Transformation). By combining Japanese manufacturing, which has strengths such as craftsmanship, kaizen, and high quality, with digital technologies such as IoT and AI, MONODZUKURI evolves and is suitable for a diversifying social environment. MONODZUKURI requires many innovations and technologies such as AI, Safety & Security, Edge Computing, IoT, Carbon Neutral and Bigdata. These technologies support the industrial fields such as automobiles, steel, and chemistry, and the control, drive, and measurement that govern the sites. Thus, many Working Groups in ISO/IEC are discussing these issues, and developing many standards. Of course, International Standardizing Committee (ISC) of SICE studies and contributes these activities. This paper would describe the latest status of standardizations related to MONODZUKURI and show the activities of ISC of SICE.

Keywords: Process Automation, Factory Automation, Network System Integration
Abstract: In this paper, the development history and overview of the “J-CLICS based on Attack tree analysis” (hereafter “new JCLICS”) is presented. The new JCLICS is a security self-assessment tool for industrial control system (ICS) users developed by the SICE/JEITA/JEMIMA Security Joint Working Group. It consists of a checklist of 19 items and an explanatory document, allowing users to easily check the implementation status of security measures for four major attack paths (namely, network, wireless LAN, bring-your-own-device, and physical access). The new J-CLICS is currently under development with the goal of being released by the end of fiscal year 2022.

Keywords: Safety, Environment and Eco-Systems, Network System Integration, System Engineering
Abstract: It is an emergent issue that countermeasures against cyber-attacks on operational technology (OT) systems such as critical infrastructures and control systems. The principal of the countermeasures is based on a risk analysis is performed for each asset to be protected in the OT system. And appropriate risk mitigation measures are prepared to reduce the risk to an acceptable level. The risk is determined by the damage caused by the attack and the probability of its occurrence. Thus, risk reduction measures include attack avoidance, probability reduction, damage control, and quick recovery, only IT security technology is often discussed today. We can get effective security measures by appropriately combining various risk reduction measures, not only IT security. This paper considers the classification and arrangement of security risk mitigation measures for effective OT security solution construction.

Keywords: Manufacturing Systems, SCADA and Network Systems, Information Management Systems
Abstract: Cyberattacks targeted for industrial control systems (ICS) are increasing in recent years, while vulnerabilities in ICS still tend to be left unmitigated to avoid the unexpected downtime due to the deployment of security measures. To solve the issue, we are developing the digital twin technology named Security Digital Twin (SDT) to evaluate the negative impact caused by security measures. In this paper, the modelling method to reproduce production and business processes by Petri-Nets is proposed, and then implemented to SDT. Finally, we demonstrate that security measures can be planned with the business continuity ensured, using a case study with a hypothetical manufacturing factory.

Keywords: Robotic and Automation Systems, Human Interfaces, Rescue Systems
Abstract: In this work, a robot semi-autonomous control method has been developed to support the sequence of processes whereby teleoperation robots used in decommissioning work travel to their work area and undertake their designated tasks, the aim being to complete work more quickly by reducing operator workloads. The proposed method combines a traveling control, learning-based object recognition, and manipulator positioning control. The operator only needs to start and stop robot operation and decide whether particular tasks need to be performed. The control method was implemented on the prototype of a teleoperation system using a hydraulic robot and trialed on the sort of radioactive waste removal work that would be required in practice. A comparison of the time taken to perform tasks autonomously and by an operator using manual operation found that use of the proposed method could shorten work times by approximately 25%.

Keywords: Identification and Estimation, Mechanical Measurement, Mechatronics Systems
Abstract: This article proposes a method with a serial manipulator calibration technique using the linearized differential finite screw method. In previous research, many studies about calibration using end-effector tracking devices have been car-ried out. However, those devices are hard to apply every calibration required manipulator because of the budget and installation problems. Furthermore, the calibration techniques studied require continuous end-effector trajectory, which forces us to use the tracking devices such as laser trackers. In this research, a novel linearized finite screw deviation model was designed to calculate the error of each axis of the manipulator from the non-continuous points trajectory of the end-effector. In the simulation using seven degrees of freedom manipulator, the calibration performance of the error using the proposed method is confirmed, and validate the proposed method with the simulation

Keywords: Robotic and Automation Systems, System Engineering, Transportation Systems
Abstract: The development of autonomous vehicles is expected to have a positive impact on society as a whole, such as improving the mobility convenience of the transportation disadvantaged, reducing the cost of traffic congestion, and reducing traffic accidents. For the safe operation of such autonomous vehicles, this paper attaches dual lidar to the bumper of the vehicle and acquires the inertial information of the vehicle from the ECU inside the vehicle to localize the position of the vehicle and generate a 3D point cloud map around the vehicle.

Keywords: Robotic and Automation Systems, Intelligent Control, Adaptive and Optimal Control
Abstract: This paper proposes an algorithm that uses for decision-making and control in Autonomous Mobile Robots (AMR) and performs in a virtual environment for simulation. In the decision-making stage, the algorithm uses the Velocity Obstacle (VO) and Artificial Potential Field (APF) methods to select the optimal velocity for avoiding collision and reaching the goal point in real-time. It additionally computes fitness that helps eliminates rapid changes in velocity. In control, the PID controller moves the robot along the velocity determined in the decision-making stage. The PID gain is updated by the gradient descent method to find the optimal gains. Proper brake torque is applied for the robot moves smoothly according to velocity previously determined. This parameter, α affects chance of avoidance obstacles, however it increase the travel time in experiment. The travel time averagely increase 9.54% at every α 0.1. When comparing the smallest and largest periods, the larger period resulted in a 29.9% decrease in control error. The results also showed that using the proposed PID controller resulted in a 13.6% decrease in control error compared to using a fixed PID controller.

Keywords: Robotic and Automation Systems
Abstract: We aimed to realize smooth passing by between robots and people by a simple method in a limited environment such as a corridor in a building. In order for a robot to pass by with a person smoothly without collision, it must be able to recognize the movement of a person coming from the front of it and change its course according to the situation. Therefore, in this study, we consider the smooth passing by between a mobile robot and a person, and set the goal to acquire a simple method that recognizes the movement of a person coming from the front and changes the course according to his/her movement. In this paper, we report on our developed robot system which can smoothly pass by with humans based on the above ideas. And additionally, we describe the results of discussion about the points that should be taken into consideration in order to realize smooth passing between mobile robots and humans in the narrow space like corridors of buildings.

Keywords: Intelligent Systems, Signal and/or Image Processing, Transportation Systems
Abstract: In this study, we demonstrate semi-supervised vehicle detection based on domain adaptation according to the camera viewpoint. Since it is difficult to collect a large amount of data for training, datasets for object detection such as COCO and Pascal VOC are pre-trained and provided as a model. The presented dataset is primarily composed of images captured at eye level, which can result in differences in detection performance depending on changes in camera viewpoint. The collected drone data consists mostly of vehicles captured while filming roads with a drone. Additionally, the captured images show the top surface of the vehicle from a bird's eye view, which differs from images captured at eye level. The teacher-student framework is widely studied for improving the effective performance in semi-supervised object detection. The teacher model is trained using annotated drone data, while the student model generates pseudo-labels in the absence of annotation information. These pseudo-labels are generated using a model trained on COCO or Pascal VOC datasets from different viewpoints than the drone. Using the Efficient Teacher model employed in SSOD, the study adapts drone-view data captured from a bird's eye perspective to improve learning performance. Transfer learning with data trained on COCO-standard and VOC datasets in the experiment shows improved results compared to previous experiments.

Keywords: Innovative Systems Approach for Realizing Smarter World, Human-Machine Systems, Medical and Welfare Systems
Abstract: As the global aging trend intensifies, the health of older people has become a focal point for governments and international organizations. Posture state detection is particularly critical in elderly health management, but the current detection technology's accuracy is still insufficient to meet application requirements. This paper proposes an improved method based on feature engineering to enhance the accuracy of posture state detection for older people. This method combines simulated data and automatic feature extraction techniques to strengthen machine learning algorithms' learning ability to capture motion features from cameras. With this innovative approach, we can lower the entry barrier for machine learning technology, enabling more people to utilize machine learning techniques to solve practical problems. Additionally, this solution effectively reduces the risk of privacy leakage for elderly individuals. This research is dedicated to improving the accuracy and security of posture state detection for older people, protecting their privacy, and promoting their health and well-being. Through this innovative method, we hope to contribute to elderly health management and address the challenges the global aging population brings.

Keywords: Innovative Systems Approach for Realizing Smarter World, Social Systems, Robotic and Automation Systems
Abstract: This study introduces fundamental development of a new database of activities of daily living (ADL) for the purpose of supporting independent care for the elderly or disabilities with adaptable AI-enable robots. The main concept of AI-robots is briefly illustrated. According to the concept of AI-robots, a simple framework to deal with ADL in aspect of both subjective and objective is demonstrated to achieve goal-oriented care support. The patient centric support is expected to prevent excessive care by the AI-robots. In order to perform the care support, the activities or motions defined as Doing-ADL that elderly people usually perform are digitalized as motion data. A method of utilizing a database system that accumulates such motion data is conceptually shown. Furthermore, the operation of the system as a digital platform for inclusive social care is proposed from the viewpoint of co-creation among care recipients, care workers and the AI-enabled robots.

Keywords: Medical and Welfare Systems, Innovative Systems Approach for Realizing Smarter World, Social Systems
Abstract: In a survey, we asked caregivers to detail those points in a daily care routine (the “morning scenario”) where care recipients required assistance (“assistive points”) depending on their level of need. The caregivers were also asked to think about how future caregiving robots might assist with these care tasks. Based on the responses, we discuss key points of support and convey expectations for future care robots and care services in the field of caregiving.

Keywords: Safety, Environment and Eco-Systems, Medical and Welfare Systems
Abstract: To accelerate the acceptance and dissemination of robot technology, it is important to demonstrate robots’ performances in research facilities that can be adapted to the diverse living conditions of the elderly. In this study, we used a living laboratory that simulated life in an ordinary house or care home, and, in this environment, tested a ceiling-suspended fall impact reduction system (FIRS) on subjects to ensure their safety in the event of a fall. The FIRS detects downward acceleration in the event of a fall and automatically applies a brake, allowing the subject to fall slowly and gently. The ceiling rails of the FIRS were installed in each room of the indoor space and along the flow lines of the steps, rough terrain and ramps in the outdoor space, allowing the subjects access to almost all areas of the living laboratory. We first measured the acceleration in a dummy human during a simulated fall with and without FIRS, and found that the acceleration was markedly reduced by FIRS. Next, we tested three human subjects wearing FIRS and found the acceleration during each fall to be low and comparable to that of the dummy with FIRS. The development of a living laboratory with ceiling-suspended FIRS may have the potential to reduce the risk of trauma due to falls and to provide not only a safe but also challenging environment in which to perform activities during the daily life of older people.

Keywords: Identification and Estimation, Medical and Welfare Systems, Ubiquitous Healthcare
Abstract: Japan is currently facing a super-aging society, and the need for preventive healthcare is increasing. However, there is a shortage of caregivers who can provide appropriate advice to elderly persons during exercise. So, there has been researches on a health promotion support system that can assess the suitability exercise movements and provide improvement advice. However, conventional studies mostly use joint angles as indicators to evaluate exercise movements, and there are few studies that evaluate the rhythm of exercise movements. Rhythm can be an indicator of declining physical function in the elderly and can also provide users of the system with the enjoyment of moving their bodies. In this paper, we propose a method for evaluating the rhythm of exercise movements using a smart device. In this system, a recurrent neural network is used for posture recognition, and the obtained output waveform is evaluated for rhythm by applying autocorrelation function.

Keywords: Human-Machine Systems, Social Systems, Intelligent Systems
Abstract: Self-help groups are one way to cope with mental illness. Here, people in similar circumstances come together to provide peer support and help each other. However, some people are not comfortable using such groups. Therefore, it is necessary to investigate the possibility of using robots or other means of support. There are two types of identity: social identity and personal identity. Personal identity is defined as a kind of personality. Social identity is like a persona, a profile, such as a job or position. So far, we have suggested implementing personalities as chatbot identities and adapting the communication method to the user. However, using personalities alone would result in bland content. Therefore, we implement social identity in chatbots and use the chatbot's personal information to enable the chatbot to speak in a way that is sympathetic to the user.

Keywords: Human Interfaces, Human-Machine Systems, Virtual Reality Systems
Abstract: With the growth of the use of drones especially in populated areas, Beyond the Visual Line of Sight (BVLOS) operation is expected as a challenge for drone operation. The layout of the Ground Control System (GCS) interface and the drone camera screen via display devices are anticipated to be crucial to the performance of the BVLOS operation. Moreover, the camera perspectives may influence the behavior of operators as the situation. In this study, participants (n=29) in a variety of situations involving multiple takeoff and landing sites, obstacles, and weather were grouped according to the display devices and camera perspectives used. The result shows the Head Mounted Display (HMD) is physically uncomfortable with the possibility of VR sickness, which is more prevalent with the first-person view than the third-person view, but it crashes less and has a straighter flight path. Landing in a narrow area has a high crash rate but is safer with HMD.

Keywords: Medical and Welfare Systems
Abstract: We propose a stochastic resonance (SR) circuit using LVDS, a differential input buffer in FPGAs, and report the results of its application to surface electromyography (sEMG) measurement. The proposed SR circuit obtained highly correlated waveforms with more than 0.9 of the correlation coefficients and the coefficient of determination for sinusoidal voltage with an amplitude of 1 mV. Furthermore, sEMG was measured as an application to biological signal measurement. The proposed circuit obtained highly correlated waveforms of more than 0.9 of the correlation coefficients with those acquired with the instrumentation amplifier and USB oscilloscope. These results suggest a novel stochastic AD conversion scheme using LVDS and its potential application to biological signal measurement.

Keywords: Medical and Welfare Systems
Abstract: A functional electrical stimulation device that considers the time lag between the application of functional electrical stimulation to the subject muscle and the onset of muscle contraction is proposed to suppress lateral knee joint sway during walking, which is a cause of knee osteoarthritis pain. The proposed device uses a distance sensor at the heel of the shoe to detect the distance to the ground corresponding to approximately 0.2 [s] before heel contact, and applies electrical stimulation boosted by a boost circuit to the particular knee muscles. In other words, the aim is to detect approximately 0.2 [s] before heel contact at each step and to implement electrical stimulation in the interval between the end of the swing phase and the middle of the stance phase to transform the knee into a desirable gait motion. To confirm the effectiveness of this device, wearing device were conducted on six healthy subjects wearing the knee osteoarthritis orthosis, and changes in knee joint internal rotation angle and external knee joint internal moment, walking speed, cadence, one-leg support time, and stride length were measured with a floor reaction force meter and three-dimensional movement analysis device. It was found that the internal rotation angle of the knee joint and internal moment of the external knee joint were improved by applying electrical stimulation to the muscles before heel contact, and the effectiveness of this method was confirmed.

Keywords: Medical and Welfare Systems, Analytical Measurement, Embodied-Brain Systems Science
Abstract: The purpose of this paper is to evaluate the impact of metacognitive training. Metacognition refers to the cognitive process by which an individual can understand their own cognitive abilities. By enhancing metacognition, individuals can improve problem-solving skills by gaining an objective perception of themselves, making better decisions about learning strategies, and regulating their own thinking processes. Therefore, metacognitive training is anticipated to be an effective intervention for individuals experiencing learning disabilities and mental disorders. This study utilized an original task that combined dynamic rotation (known for its effectiveness in metacognitive training during learning), mental rotation (known for its effectiveness in psychological metacognition), an illustration memory task, and a story prediction task (both known as clinic-based metacognitive training). The effects of this training on learning were examined using the Metacognitive Awareness Inventory (MAI) scale, which was designed to measure metacognitive abilities during learning.

Keywords: Medical and Welfare Systems, Human-Machine Systems, Robotic and Automation Systems
Abstract: Humans have a periodicity in which their body temperature falls during sleep and rises upon awakening. Shift workers can also modify the periodicity of their body temperature to some extent even if their work hours change. The Van der Pol equation is a mathematical model that can simulate this periodicity and disturbance responsiveness. In this paper, the authors conducted a simulation of the mathematical model and an experiment on body temperature. As a result, the simulation results show the periodicity and disturbance responsiveness, and the actual experiment shows that the body temperature can be reproduced within a certain range.

Keywords: Medical and Welfare Systems, System Engineering, Networked Sensor System
Abstract: The assessment of gait for walker users is critical for evaluating their functional abilities and in developing rehabilitation plans. In this study, we present a novel gait analysis system that utilizes a fisheye camera affixed to the walker and deep learning techniques to assess the whole full-body posture of the user. Pose estimation from a fisheye camera image using deep learning permits the analysis of the whole body of a user while using a walker, which has been difficult until now. The proposed system also estimates the walking speed and stride length multimodally by incorporating both pose estimation results from camera images and encoder data from the walker. The multilayer perceptron, which accepts both the pose estimated keypoints data and encoder data as inputs, facilitates the multimodal estimation of the walking speed and stride length. In this study, we introduce a proposed system and evaluate its estimation capabilities by leveraging conventional 3D human pose estimation models using a 3D position measurement apparatus as grand truth. Additionally, we evaluated the proficiency of the system in terms of analyzing the walking speed and stride length. Our research is distinct from previous works in computer vision since we evaluate estimation accuracy within the practical context of a camera-equipped walker and conduct multimodal gait analysis using both images and walker encoder information.

Keywords: Signal and/or Image Processing, Medical and Welfare Systems, Embodied-Brain Systems Science
Abstract: Metacognition refers to knowledge about the cognitive process and related concepts and is an essential ability for learning and problem solving. That is why detecting metacognition is helpful for evaluating materials that promote metacognitive skills. However, there is no established method for detecting metacognition. In this study, we attempted to detect metacognition by analyzing the Hurst exponent of differenced EEG signals during a metacognitive task. Furthermore, independent component analysis (ICA) was applied as a preprocessing step to remove noise caused by eye movements. Finally, we measured the EEG signals of participants undergoing metacognitive training designed for the treatment of psychosis. The goal of the training was to promote metacognition. As a result, we observed an increase in the Hurst exponent and high-frequency gamma-band component of the EEG signal before answer modification. Since metacognition allows us to modify our problem-solving strategies, the increase in the Hurst exponent suggests the occurrence of metacognition.

Keywords: Social Systems, Medical and Welfare Systems, Modeling, System Identification and Estimation
Abstract: The global outbreak of COVID-19, first reported in late 2019, has caused a devastating pandemic with over 700 million cumulative cases worldwide, posing a critical threat to humanity. This paper develops a region-structured SEIR model to simulate the transmission of COVID-19, taking into consideration regional population distributions and cross-regional population mobility. Instead of directly identifying the parameters of the model, the Nelder-Mead (NM) method is used to obtain the optimal parameters by estimating them to reduce the computationally difficult. Finally, this model was used to estimate and simulate the parameters of infection in Hokkaido area.

Keywords: Robotic and Automation Systems, Biological and Physiological Engineering
Abstract: In this study, we measured the odor source localization behavior of an adult male silkmoth in indoor and outdoor environments using an animal-in-the-loop system in which an insect remotely controls the robot. The complexity differs greatly between indoors and outdoors because the odor is carried by the wind and diffuses into the space; therefore, the direction of the wind is unpredictable in the outdoor environment, making it difficult to localize the odor source. However, we found that the silkmoth makes it possible to localize odor sources regardless of whether indoors or outdoors. The trajectory showed that the silkmoth enter the odor plume by moving in the crosswind direction in the early stages of the search when the odor was the scarce situation.

Keywords: Autonomous Decentralized Systems, Intelligent Systems, Robotic and Automation Systems
Abstract: Hexapod robots have high traversability over wheeled robots on rough terrain. On uneven terrain, the legs of hexapods have to deal with multiple policies: collision avoidance with obstacles and other parts of frames, keeping joint limits, reaching the destination, and so on. This paper proposes several local controls for legs in the swing phase, with a range sensor installed on the foot and linear position sensors equipped around the tibia. We integrate them with Riemannian Motion Policies (RMPs) and incorporate them into Follow-the-Contact-Point (FCP) gait control. Experiments show how the proposed control method works while a hexapod robot walks through terrain with a step.

Keywords: Autonomous Decentralized Systems, Nonlinear Control, Identification and Estimation
Abstract: Shepherding is a typical collective behavior arising from heterogeneous interactions between swarms and individuals of other species. Understanding the herding model by which a few shepherds command a sheep flock can lead to guide robot groups and enable control of artificial objects that indirectly guide swarms. Most previous studies have proposed empirical guidance models based on human observation and analyzed the navigation performance for group models in simulations. Thus few research attempts have been made to reproduce the models for real shepherds. In this study, we aim to estimate a minimal navigation model of the shepherd resembling the behaviors of shepherds by using system identification based on positioning data acquired during actual herding. For this purpose, we adopted the nonlinear system identification method GMDH (group method of data handling). Using the method, we constructed estimation functions by natural selection from as many input variables as possible to determine the factors influencing the estimation target.

Keywords: Autonomous Decentralized Systems, Social Systems
Abstract: This study aims to understand control mechanisms underlying interpersonal coordination in ballroom dancing. We propose an agent pair model to understand the mechanism that the amount of steps increases when dancers dance in pairs compared to when they dance solo, i.e., the pair assist effect. In the proposed model, the agents support each other through holds on their arms, enabling them to take a back-arched body posture that allows the agent to realize a larger leg stride, which would be unstable if the agents danced alone. Furthermore, each agent adjusts its leg motion based on the compressive force generated by the hold, thereby generating a cooperative motion that suppresses the variation of the hold force due to discrepancies among agents. The simulation results suggest that decentralized motion coordination based on the load via the hold between agents is important in cooperative movements that involve physical contact and utilize each other, as seen in ballroom dancing.

Keywords: Autonomous Decentralized Systems, System Engineering, Intelligent Systems
Abstract: Animals can move in complex natural environments for survival. Such adaptive movements are realized through the interplay between navigation and locomotor capabilities. However, most studies on animal navigation have focused on the path selection mechanisms, and the role of sensory inputs in their locomotor movements for deciding navigation strategies has not been considered enough. In this study, we focus on the active sensing mechanism of centipedes which use antennal and body bending motion for spatial exploration. We will introduce a mathematical model that may reproduce this behavior.

Keywords: Nonlinear Control
Abstract: Some implicit Lyapunov function methods have been proposed to stabilize multiple-integrator systems. In this paper, we extend the previous implicit-Lyapunov-function methods to general nonlinear systems with symmetry under feedbacks. We introduce a notion of symmetry under feedbacks for nonlinear systems. For the systems with the symmetry, a construction method of parametric control Lyapunov function (parametric CLF) is proposed, where the CLF is deformed by the parameter of the symmetry. Moreover, we regard the parameter as a function of the CLF, which derives an implicit CLF design. The obtained implicit function becomes a CLF under a sufficient condition that the implicit function can be solved uniquely.

Keywords: Nonlinear Control, Adaptive and Optimal Control
Abstract: In recent years, autonomous driving technology has been developed rapidly for various purposes. To enable that, trajectory tracking, which has been studied by many researchers, is an essential control problem. Researchers showed the effectiveness of that in various ways like tracking the control Lyapunov function by actual experiments. This paper considers modeling errors for everyone to get the same result. So, we apply an adaptive controller. In this paper, we confirm the effectiveness of our method through an actual experiment on a straight trajectory.

Keywords: Nonlinear Control, Autonomous Decentralized Systems, Modeling, System Identification and Estimation
Abstract: In this paper, we discuss a synchronization-based distributed predictor for Lur’e-type systems with asynchronously measured outputs.

Anticipating synchronization is a leader-follower synchronization in which the follower system synchronizes to the future value of the leader system by introducing a time delay in the feedback. Therefore, this synchronization scheme can be considered as a state predictor for nonlinear systems. The anticipating synchronization problem is extended to a class of sampled-data nonlinear systems, and some distributed versions of the state predictor based on anticipating synchronization using synchronous/asynchronous sampled measurements are also proposed. Although the interconnections between sub-predictors are continuous time couplings in these extensions, the data exchanges between the sub-predictors should be sampled data couplings in a practical situation where the communication is realized with wireless communication devices.

So, the distributed predictor proposed here consists of a network of N sub-predictors with sampled data couplings between sub-predictors. Based on the stability of the origin of the prediction error dynamics, we derive a sufficient condition for the distributed predictor to work well. Then we derive a design method of the feedback gain matrices and the consensus gain matrices to achieve the state prediction.

Finally, we show the validity of the proposed design method by a numerical example.

Keywords: Nonlinear Control, Human-Machine Systems, Innovative Systems Approach for Realizing Smarter World
Abstract: The assist control of stability is helpful in power-assist problems. First, we describe the relationship between continuous inputs for asymptotic stability and a quadratic pointwise minimum. This relationship implies a condition for the non existence of the assist control of stability. We then consider the realizability of control Lyapunov function-based asymptotic stability assist control. We define and demonstrate asymptotic stability assist control through an example that illustrates its effectiveness. In addition, we reveal class of systems that has no asymptotic stability assist control.

Keywords: Nonlinear Control, Mechanical Systems Control, Robotic and Automation Systems
Abstract: This paper has presented a new path-following feedback control law enabling the motion of a five-axle, three-steering articulated-vehicle system to be specified by the shape of three paths along which manipulation points defined on the system, e.g., three joints, are caused to move. It has also presented a new path-planning method enabling the shape of the three paths to be deformed adapting to geometrical constraints derived from external and internal states, e.g., the degree of interference with obstacles and the degree of alignment of two carriers combined for transportation of large and heavy structural objects. The validity of the control law and the path-planning method has been verified in computer simulations in which a performance index defined from the geometrical constraints is optimized, e.g., in which the articulated-vehicle system passes between two obstacles without collision while maintaining a straight-bed carrier configuration throughout transportation operations.

Keywords: Nonlinear Control, Mechatronics Systems
Abstract: This paper investigates the influence of the link length of hopping robot on the control performance of the robot attitude by simulation in order to improve the stability of the robot. The simulation model is a bipide hopping robot with springs and closed link mechanism. The springs are attached to the closed link legs horizontally, and the hopping motion is realized by opening and closing the link legs. The robot's body has an inertial rotor, which improves the stability of attitude control. Attitude stabilization is conducted in combination with the swinging control of the legs and inertial rotor control. The mathematical model of the robot is derived separately for the state where the robot is on the ground and in the air by Lagrangian equation of motion. In order to realize the hopping motion, the periodic energy storage and release of the spring are used and the control input to the closed link of the leg is calculated using the vibration phase of the spring. The robot attitude control for stable locomotion control is designed by integral-type optimum servo with LQR method. This controller has a wide stability margin and robustness against modeling errors. Simulation analyses are conducted using robot models with three different leg link lengths by Simscape Multibody in MATLAB/Simulink. Guideline for designing link length of hopping locomotion control on an actual robot is discussed.