Keywords: Control Applications, Robotics and Motion Control, Nonlinear Control
Abstract: This paper presents a control strategy for a wheeled mobile robot with variable-pitch blades which make it highly mobile over irregular terrain. In our previous work, a mathematical model with respect to pitching motion of the robot necessary to climb a stair was developed, and a servo controller for the pitching motion was proposed under the assumption that the desired lift or down force was available as a control input. In this paper, taking the actuator dynamics into account, the controller is redesigned by applying the backstepping method to guarantee the asymptotic stability constructing a Lyapunov function, and its effectiveness is shown by numerical simulation.

Keywords: Robotics and Motion Control
Abstract: Passive walkers which can walk stably down a shallow slope without actuators show that exploiting the passive dynamics leads to efficient walking. In this paper, a simple planar biped robot with a torso are considered. We investigated level-ground walking based on the passive dynamics by using a torso and swing-leg control with hip series elastic actuators. The series elastic actuator comprised springs in series with a motor. Numerical simulations showed that the walking speed increases with the desired torso angle and the walking stability is mainly determined by the motor control gain. The simulations demonstrated that the biped robot with the series elastic actuator can walk stably at various speeds by torso and swing-leg control.

Keywords: Mechatronics, Robotics and Motion Control, Nonlinear Control
Abstract: An intermediate control is introduced to mass measurement system using relay feedback of velocity to stabilize the trajectory. In the original system, the velocity of the object was fed back through a relay with hysteresis, and the mass of the object was determined by measuring the period of an induced limit cycle. It could determine the mass of the object rather accurately. However, the trajectory of the object easily drifted because only the velocity was fed back and there was no restoring force. To generate restoring force, a spring element was added. The drift became smaller but still occorred. It caused the trajectory of the object to fluctuate. To eliminate such fluctuation, an intermediate control is introduced to stabilize the trajectory. The operation of the intermediate control is analyzed to prove the convergence of the trajectory.

Keywords: Nonlinear Control, Linear Systems, Filtering
Abstract: The stabilization of a magnetic suspension system is achieved by using only a nonlinear integrator without other element. The proportional-derivative (PD) feedback is the simplest control method for the magnetic suspension system. The proportional element gives restoring force, and the derivative element gives damping to the system. However, the derivative feedback element needs to be carefully designed because unnecessary high-frequency signals generate an adverse effect. Meanwhile, installing a first-order-reset element (FORE) has been proposed to reduce the vibration. The element is a first-order low-path filter (LPF) with reset functions. This paper proposes to stabilize a magnetic suspension system with an FORE only. However, the magnetic suspension system cannot be stabilized by the basic FORE. Therefore, the FORE is modified as to the reset conditions. A magnetic suspension system is stabilized by the modified FORE. The characteristics of the stabilized magnetic suspension system are studied experimentally.

Keywords: Mechatronics
Abstract: This paper presents a new type of bearing-less motor. A unique feature of this bearing-less motor is an operation without the utilization of permanent magnets. The rotor magnetized by a current of a noncontact power supply, which consists of a bridge rectifier circuit and coils. In previously report, the levitation is archived through attractive forces generated by inclinations on the edges of the rotor and the stator. Hence, this paper shows FEM analyses of the levitation and rotation control of a bearingless motor with non-contact power supply. In addition, the design descriptions of a new rotor improvement for achieving the target rotation performance is given.

Keywords: Mechatronics, Control Applications, Robotics and Motion Control
Abstract: A vibration isolation device with an active dynamic vibration absorber is developed to remove vibration induced by a cryopump. Cryopump is used to make high-vacuum and low-temperature environments for precise measurement. However, it induces vibrations with multiple frequencies, which may deteriorate measurement accuracy. This study focuses on removing the vibration of low frequencies because conventional vibration isolation devices for cryopump can hardly remove the vibration of lower frequencies. In the developed vibration isolation device, an active vibration absorber is used to remove the vibration efficiently in at low frequencies. In this report, the design concept and structure of the fabricated apparatus are described.

Keywords: Complex Systems and Networks, Control Applications
Abstract: This paper focuses on the control design and stability analysis of an awareness Susceptible-Exposed-Infected-Vigilant (SEIV) epidemic system which has two infectious states over arbitrary directed networks. A state feedback controller is firstly applied to the generalized SEIV model with human awareness, and explores the medical treatment usage against the epidemic propagation. After applying the control scheme into the epidemic system, the epidemic threshold condition is found to guarantee the exponential stability of the system. Simulation results are illustrated to verify the threshold condition as well as the performance of the control design which is able to reduce the epidemic outbreak and effectively inhibiting the epidemic dissemination.

Keywords: Complex Systems and Networks, Intelligent and Learning Control, Predictive Control
Abstract: In spite of the rapid development of computer network, congestion control becomes an increasingly important problem due to an enormous increase of traffic. Active queue management (AQM) is an effective congestion control approach in the sense that it can be reduced by discarding packets in the buffer of the routers before congestion occurs. In this paper, for the predictive congestion control, long short-term memory (LSTM) that is well known as the most popular recurrent neural network is applied to compensate for the delay for TCP network. Taking into account of the identification of TCP dynamic system, it is shown that the impact of network latency can be reduced and the proposed control scheme stabilizes the router queue length better than other well-known AQM algorithms.

Keywords: Decentralized Control, Complex Systems and Networks, Transportation Systems
Abstract: In this paper, we consider the problem of urban traffic control over networks. The primary objective of our designed strategy is to determine traffic signal offset and active (green) time for each route to reduce delay and the number of stops. The dynamics is modeled in discrete time to formulate an optimization problem. By applying the results of consensus and economic dispatch problem (EDP), traffic flows are computed in the sense of minimizing the queue lengths and avoiding congestion at all intersections of the network. The computed traffic flows are used as parameters in the traffic signal optimization algorithm.

Keywords: Optimal Control and Optimization, Complex Systems and Networks
Abstract: This study provides a simulation and management method for an economy described by big bookkeeping data. Since general equilibrium models and statistics of basic economics could not describe and control these microstates, to utilize microdata, we developed an agent-based model which describes states of every agent in the bookkeeping system. We control our model with centralized mode analysis: it represents multi scenarios of growth path, and also search critical economic situations solving Turnpike dynamic optimization with simulated annealing. This model links microdata of enterprises, households, or a government to economic simulations and management.

Keywords: Networked Control Systems, Distributed Parameter Systems, Identification and Estimation
Abstract: A novel distributed algorithm designed for weighted average consensus is presented. This algorithm is developed based on the well-known Belief Propagation (BP) algorithm for statistical learning. For a connected network without loops, the algorithm will converge in finite number of iteration and produces a correct average consensus value for every node in the network. For a network with loops, we convert the weighted average problem into an optimization problem with a relaxation factor whose solution approaches to the weighted average with appropriate relaxation factor. A modified algorithm is also proposed for loopy networks and consensus will be reached asymptotically with low computation complexity and fast convergence rate.

Keywords: Networked Control Systems, Linear Systems, Fault Detection
Abstract: The security of Cyber-physical systems has been a hot topic in recent years. There are two main focuses in this area: Firstly, what kind of attacks can avoid detection, i.e., the stealthiness of attacks. Secondly, what kind of systems can stay stable under stealthy attacks, i.e., the invulnerability of systems. In this paper, we will give a detailed characterization for stealthy attacks and detection criterion for such attacks. We will also study conditions for the vulnerability of a stochastic linear system under stealthy attacks.

Keywords: Decentralized Control, Power Systems and Power Electronics, Optimal Control and Optimization
Abstract: With increasing penetrations of distributed energy resources into the power system, maintaining system reliability and economy has been an important issue. In order to maintain the supply-demand balance, demand response (DR) requests customers to reduce their power demands and offer financial incentives. An accelerated alternating direction method of multipliers (ADMM) has been proposed as an effective method for solving DC optimal power flow (DC-OPF) problems with DR. However, the accelerated ADMM partially needs centralized calculation to accelerate a distributed ADMM algorithm, and therefore, loses some advantages of distributed algorithms such as high reliability against failure. To cope with this difficulty, this paper proposes a fully-distributed accelerated ADMM by combining the so-called push-sum algorithm, and illustrates its effectiveness through simulation results.

Keywords: Distributed Parameter Systems, Observer Design, System Theory
Abstract: This paper deals with a finite-dimensional feedback stabilization of distributed parameter systems of parabolic type with non-self-adjoint system operator. When the system operator is self-adjoint as well studied in the previous literature, a finite dimensional feedback stabilizer with a prescribed exponential decay rate can be constructed. It is shown that, even in the case of a non-self-adjoint operator, a similar design method can be applied under some additional assumptions. The controller contains finite-dimensional observers which can estimate the ill-behaved modes of the plant even under the effect of spillovers.

Keywords: Game Theory, Complex Systems and Networks, Robotics and Motion Control
Abstract: As a significant direction of multi-agent system research, the investigation of multi-agent coverage control has attracted increasing attention recent years. The solutions of this problem is related with achieving the maximum coverage of the specific environment while maintaining connectivity. From the perspective of game theory which can characterize the problem of cooperation and conflicts, the coverage control can be regarded as the process of continuous game. Here, a fully distributed and scalable control algorithm is proposed for achieving the coverage control. Each agent can only use the information from neighboring agents within her communication range. And importantly, she does not need to know all the environmental information in advance. Simulations show that the resulted networks are well connected and effective coverage can be realized. Analytical results of the coverage achieved by symmetrically tiled network configurations and other algorithms are provided to evaluate the performance of our algorithm.

Keywords: System Theory
Abstract: This paper is concerned with the methods for solving continuous coupled Lyapunov matrix equations. First, based on the existing algorithms with latest estimation, a weighted explicit iterative algorithms is developed for solving the considered matrix equations. Second, it is shown that under zero initial conditions the sequence generated by the constructed algorithm are monotonically converge to the unique positive de nite solutions of the coupled Lyapunov matrix equations. In addition, some convergence results are presented for the algorithms with any initial conditions. Finally, a numerical example is provided to illustrate the e ectiveness of the presented algorithms.

Keywords: System Theory, Linear Systems, LMIs
Abstract: This paper investigates the finite-region contractive stability problem for the discrete-time two-dimensional (2-D) systems in Fornasini-Marchesini (FM) model. First, motivated by 1-D systems, the concepts of finite-region stability and finite-region contractive stability are introduced for 2-D systems. Then, sufficient conditions for the finite-region stability and finite-region contractive stability of 2-D FM system are derived based on the Lyapunov functionals, respectively. Finally, two numerical examples are presented to show the effectiveness of the proposed results.

Keywords: Optimal Control and Optimization, Robust Control, Flexible Structures
Abstract: This paper considers position and attitude control of flexible space structures. It is assumed that sensors and actuators are collocated in structures. The purpose of this paper is to propose a control method by a controller compensating for gain reduction and phase lag in a loop transfer function using only displacement output. We show that the proposed controller makes a closed-loop system not only robustly stable against uncertainty of characteristic parameters such as mass, damping, and stiffness, but also optimal for a quadratic cost function. Finally, numerical examples are presented to show that the proposed method realizes robust stability and has effectiveness on vibration suppression by optimal control.

Keywords: Control Applications, Transportation Systems, Optimal Control and Optimization
Abstract: Low Frequency Vibrations have increased significantly in railway car-bodies designed for high-speed railway operations due to the dominant effect of flexural vibration of the car-body caused by weight reduction of railway vehicles to satisfy speed requirements and energy efficiency. To reduce such low frequency vibration a twin pronged approach is proposed. Firstly, a 1/12 scaled double shell hanging car body model, consisting of an inner shell mechanically hanged within an outer shell, is utilized as a structural damping measure. Secondly, a Piezo-electric Patch Configuration (PPC) is bonded to the inner shell floor plate and coupled to a tuned multi-modal shunt circuit. The tuned shunt circuit absorbs and dissipates the flexural vibration strain energy of multiple modes on the car-body floor and significantly damps low frequency vibrations of car-body floor. Finite Element Modelling (FEM) of the proposed car-body structure, modal analysis and damped and undamped harmonic response of car-body was simulated using ANSYS 17.1.

Keywords: Flexible Structures, Robotics and Motion Control, Control Applications
Abstract: In this paper, a flexible marine riser with varying length under the effects of ocean currents is investigated. The governing equations of the riser together with the drillship are developed using the extended Hamilton’s principle. An approximated model using a modified Galerkin method is derived. The dynamical analysis of the system is performed with the approximated model developed. In addition, a boundary control is developed and implemented to suppress the transverse vibrations of the riser. Finally, the simulation results are shown to verify the vibration behavior of the system as well as the effectiveness of the proposed control algorithm.

Keywords: Signal Processing, Adaptive Control and Tuning, Control Applications
Abstract: In active noise control (ANC) systems, it is important to estimate the control filter and the secondary-path filter simultaneously since the secondary path can be changed by changing the position of the loudspeaker in real time. However, it is very difficult to estimate two unknown filters at the same time since the estimation errors of the two filters can affect the each estimation. In this paper, a stepsize controller was proposed to improve the convergence stability and noise reduction ability. The stepsize controller assumes that the errors in the estimation of the secondary path are large measurement noises in terms of estimation of the control filter and adjusts the stepsize of the control filter until the measurement noises are reduced. It can provide the stable ANC systems since the estimation of the control filter is automatically controlled according to the estimation of the secondary-path filter. The proposed ANC system was also applied to the scheduled-stepsize algorithm [1]. The simulation results show stable estimations of the filters and improved noises reduction levels.

Keywords: Signal Processing, Adaptive Control and Tuning, Identification and Estimation
Abstract: In this paper, we proposes an active acoustic noise cancellation algorithm which actively cancel out the acoustic noise using a variable step-size normalized least mean square (NLMS) adaptive filter. One of the difficulties of active noise cancellation (ANC) system is that the system has a very long echo tails. So, the FIR filter coefficients are very long. Because the ANC system is also accepts electric signals through a microphone, the ANC system is very sensitive to noise. The Huber function is applied to prevent wrong filter coefficients update by impulsive noise. The Huber function uses the error signal as it is when the error signal is within a certain range. If the error signal is outside a certain range, this function does not update the coefficients. The variable step-size which obtained by mean square deviation (MSD) analysis, speeds up the convergence speed of the algorithm and makes the steady-state error smaller. Simulation results show that the proposed algorithm has much better performance than other algorithm in noisy environment.

Keywords: Control Applications, Intelligent and Learning Control, Nonlinear Control
Abstract: In this study, a nonlinear, intelligent and robust controller with a simple algorithm has been applied to the air-conditioning system. The hybrid control algorithm is based on Fuzzy Cognitive Map (FCM) method which uses the Generalized Predictive Control (GPC) method controller to define the initial weights of FCM controller. The proposed controller performance proved that the Fuzzy Cognitive Map-Generalized Predictive Control controller is suitable for Multiple-Input and Multiple-Output nonlinear system of an air-conditioning system and an optimum thermal comfort condition was obtained using the proposed control algorithm. Finally, the Fuzzy Cognitive Map-Generalized Predictive Control controller shows a successful results and applicable control design approach to the Nonlinear Multiple-Input and Multiple-Output air-conditioning system. This system managed to achieve desired temperature at 700 seconds with 0% error and desired humidity at 900 seconds with 5% error from 50% humidity.

Keywords: Control Applications, Intelligent and Learning Control, Nonlinear Control
Abstract: Although the wind power generation technology has gained tremendous development in recent years, how to reduce important component loads of wind turbines is still a hot topic for the researchers in control communities due to the randomness and intermittence of wind speed. In this study, an effective wind speed estimation (EWSE) and prediction based feedforward feedback pitch control scheme for wind turbines is presented. First, both EWSE and prediction models are developed through support vector regression (SVR), the training of which is conducted by utilizing data acquired through the existing supervisory control and data acquisition (SCADA) systems. Further, optimization of SVR parameters is completed by the particle swarm optimization (PSO) algorithm, and smoothness of the estimated wind speeds is guaranteed by employing a low-pass filter. Thereafter, a proportional-integral-differential (PID) based feedforward feedback control scheme is designed to obtain the control goals of generator power regulation as well as loads mitigation by combining the EWSE and prediction models. Finally, comparative simulations between the novel feedforward feedback control scheme and traditional pure feedback controller are conducted on GH bladed platform to show the effectiveness of the proposed scheme.

Keywords: Control Applications, Nonlinear Control, Variable-Structure/Sliding-Mode Control
Abstract: This paper proposes a nonlinear tracking controller for autonomous vehicles. The dynamic model used for controller design is nonlinear without the assumption of constant forward speed. The controller with two control inputs (steer angle and traction force) is developed by employing input-output linearization where the outputs are the forward speed and yaw rate of the vehicle, integral sliding mode control (ISMC) for robustness, and backstepping method.

Keywords: Nonlinear Control, Maritime Control, Control Applications
Abstract: In this paper, the problem of trajectory tracking control of surface vehicles is investigated. Based on fixed-time theory, a novel control scheme is proposed. Under the proposed control law, the vehicle can track the desired trajectrory within finite time upper bounded by a constant independent of initial tracking error, while guarantee that all signals in the closed-loop tracking control system are globally fixed-time stable. In addition, the compensator-based command filtered control technique make the designed control law simple and easy to implement in practice. A simulation example is include to demonstrate the effectiveness and the performance of proposed control scheme.

Keywords: Adaptive Control and Tuning, Intelligent and Learning Control, Nonlinear Control
Abstract: Traditional quadcopter designs entail 4 independent thrusters that can control the dynamics of 6 DoF quadcopter resulting in an under-actuated system. As a consequence of this, traditional quadcopters can not track a desired reference trajectory with arbitrary Euler angles and require two virtual control inputs. Single Tilt axis thrust vectored quadcopter designs were recently proposed for higher operational flexibility rendering it the capability to hover at a point or follow any desired reference trajectory with arbitrary Euler angles. In this paper, online adaptive control was formulated for a single axis tilt thrust vectored quadcopter to control all the states. Adaptive sliding mode control was synthesized for the position control loop and Adaptive online neural network control was used for the attitude control loop. Physical parameters of the thrust vectored quadcopter were varied in real time during simulation and the control formulation was able to adapt to these variations in real-time and successfully track the desired trajectories. Simulation results provided at the end establish the effectiveness of the approach.

Keywords: Process and Chemical Systems
Abstract: Currently, the majority of studies on process alarm thresholds optimizations are less concerned with human factors. In response to this limitation, a novel adaptive optimization approach to process alarm thresholds concerning human factors is explicitly introduced in this paper. APRIORI algorithms are used to extract association rules between process alarms and manipulated variables. By means of fuzzy reasoning strategies, a human factor index in terms of operators’ perception and treatment capabilities is created before the nuisance alarm rate and alarm treatment rate are calculated, respectively. Subsequently, an thresholds optimization objective function with respect to the weighted false alarm rate (FAR) and missed alarm rate (MAR) is established, in which, the FAR and MAR are estimated with kernel density methods while weights are calculated based on the human factor index. Case studies show that the proposed method can adapt to operators’ human factors, facilitate the process alarm treatment and improve the process safety.

Keywords: Process and Chemical Systems, Computational Intelligence
Abstract: It takes many efforts to establish accurate soft sensor models because of the increasing complication of processes. For the sake of solving this problem, a novel multi-kernel extreme learning machine based on partial least square regression (PLSR) is proposed. In the proposed method, different kernel functions are used for mapping the space of process data to highly nonlinear space. The partial least square regression is adopted to obtain the relationship between the nonlinear space and output layer. To validate the performance of the proposed model, a case study using the High Density Polyethylene process is executed. Simulation results confirm the performance of the proposed model.

Keywords: Process and Chemical Systems, Control Applications
Abstract: Continuous casting is an important process in iron and steel production. In continuous casting process, in order to improve the control precision of mould level under steady-state working condition, and to suppress large fluctuation under non-steady-state working condition, a fuzzy PID controller is designed based on working condition identification. First, a mechanism model of mould level is established. After analyzing the characteristics of the model, the continuous casting process is divided into different working conditions. Then, fuzzy rules are designed to regulate the parameters of PID. Finally, results in industrial site show both of the control precision of mould level under steady-state working condition and the anti-interference ability under non-steady-state working condition are improved, indicating that the proposed method is effective.

Keywords: Process and Chemical Systems, Control Applications, Manufacturing Systems
Abstract: The shoulder is a process of maintaining dislocation-free growth in a Czochralski grown monocrystalline silicon, which is the key to the smooth entry of the crystal into the body. It has been found in production practice that crystal-change often occurs in the middle section of the shoulder. In this paper, the dynamic distribution of the thermal field, flow field, thermal stress and crystal-melt interface shape of the shoulder process is analyzed by numerical simulation. Theoretically, the phenomenon of easy crystal-change in the process of shouldering is explained, and the heater power adjustment process of the shoulder process is proposed. The comparison between the simulation and the actual crystal pulling data shows the correctness of the analysis and provides guidance for the actual crystal pulling.

Keywords: Process and Chemical Systems, Identification and Estimation, Manufacturing Systems
Abstract: Fault prognostic, which estimates the time to failure and risk for existing and future failure modes has recognized as a key component in maintenance strategies currently. The fault degradation process is in general slowly varying autocorrelated and shows typical nonstationary nature. However, most of existing prognostic methods don’t consider the nonstationary characteristics of the fault degradation process. Besides, stationary fault information may bury the fault degradation trend. In this work, a fault degradation modeling and online fault prognosticating strategy is proposed based on degradation-oriented slow feature analysis and temporal smoothness analysis. First, a fault degradation-oriented slow feature analysis (FDSFA) algorithm is proposed to extract critical fault degradation features. Second, a stability weighting factor (SW) is defined to evaluate the stability of each feature and a key fault degradation factor (KFDF) is calculated by combining critical features and SW. Considering the nonstationary characteristics of KFDF, a time-varying regression model with temporal smoothness regularization is developed for online fault prognostics. Case study on a real industrial process illustrates the validity of the proposed method.

Keywords: Identification and Estimation, Sensors and Senor Fusion, Pattern Recognition
Abstract: Time-varying and state shifting are two of the primary process factors that deliver unsatisfactory prediction performance of soft sensors. Adaptive soft sensor is commonly the alternative practice to guarantee desirable predictive results. In this paper, combining with symmetric Kullback-Leibler (SKL) divergence, a novel streaming variational Bayesian supervised factor analysis (S-VBSFA) model is developed to scratch the process time-varying and state shifting features through online updating of the posterior of model parameters with the latest process data, which is much more efficient than traditional adaptive strategies with thorough local modeling. During the updating process, the SKL divergence is utilized to determine priors of the next variation Bayesian inference. As a result, the proposed algorithm not only reduces the time for adaptive model updating, but also improves the prediction accuracy. Besides, the tracking time delay for process variations are also reduced. An industrial process case has verified the superiority of the proposed approach.

Keywords: Sensors and Senor Fusion
Abstract: Recently, welfare vehicles are widely used among the elderly and the aged. However, it is difficult for inexperienced beginners to control the welfare vehicle in narrow places such as elevators and narrow corridors. For the difficulty, the driving assistance system for the welfare vehicle has been proposed, which is maneuverable by the virtual platoon control technique using Augmented or Mixed Reality. However, it is not certified that driver focus on designed digital content in Head Mounted Display (HMD). To overcome the query, the measurement devices of eye movement are required wearing HMD. In this paper, HMD with a measurement device to detect the eye movement is prototyped using the corneal reflection. Wearing HMD with a measurement device, the driver is assisted using novel virtual platoon control by Augmented Reality. The driver’s gaze-point, that is where the driver focus, is analyzed on-line. As a result, the popular hypothesis for the facilitate driving with the assistance system of the welfare vehicle is obtained from experiments.

Keywords: Sensors and Senor Fusion, Human-Machine Systems
Abstract: Recently, with the aging of the population, fall accidents of elderly people are increasing. In order to reduce fall accidents, it is necessary to detect the walking ability decline of elderly people. People with medical knowledge qualitatively evaluate and judge walking ability from experiences by a walking test. However, in this case, it is difficult to examine many subjects and to evaluate them quantitatively. Therefore, it is increasing to the demand for walking measurement systems using instruments. Requirement of this system is not that it can be measured with high accuracy but that it is simple, inexpensive and accurate enough for gait ability evaluation. In this study, we propose a quantitative measurement system using a skeleton model of a depth sensor (Kinect v2). Kinect can estimate the position of a person’s joint using depth information. However, with a single Kinect, it is difficult to measure the turning motion because hidden parts occur and the movement that can be acquired is limited to the movement facing the front. Therefore, in this study, we propose a mutual interpolation method that can overcome overlap and track turning motions that are not always facing front, using two Kinects. Specifically, in consideration of the tracking state of each sensor, integration of two Kinect information was performed using a constant acceleration motion walking model.

Keywords: Sensors and Senor Fusion, Pattern Recognition, Process and Chemical Systems
Abstract: In order to model nonlinear industrial processes for on-line estimating those quality-related but difficult-to-measure variables, this paper proposes an inferential sensing approach based on Gaussian mixture model and extreme learning machine which is referred to as the ‘GMM-ELM’. In the GMM-ELM, mixture of ELMs is developed under the framework of GMM to deal with nonlinear and non-Gaussian characteristics, where localization and localized ELMs are completed unifiedly instead of separately. In addition, Bayesian regularization is exerted for the weight vector that connects the hidden and output nodes for each ELM to handle overfitting. We also develop an efficient learning algorithm to train the GMM-ELM. Experiments are carried out on a real-world industrial process to evaluate the performance of the GMM-ELM, which demonstrate the effectiveness of the proposed approach as well as its promising foreground in monitoring or automatic control of the quality-related variables.

Keywords: Sensors and Senor Fusion, Process and Chemical Systems, Identification and Estimation
Abstract: Gaussian mixture regression (GMR) is one widely adopted approach to construct soft sensors for industrial processes that work with multiple operating modes. However, outliers which usually result from inappropriately observed, recorded or stored measurements into database exist widely in industrial datasets and are very difficult to be completely recognized and removed. The presence of outliers renders the predictive performance of the GMR-based soft sensors quite unsatisfactory. Besides, labeled samples in industrial process are usually limited, which easily leads to overfitted soft sensors. To resolve these problems, a Bayesian regularized Student’s-t mixture regression (BSMR) is proposed in this paper. In the BSMR, the outliers are dealt with by the Student’s-t distribution that has heavier tail than the Gaussian distribution; in addition, the overfitting issue is tackled by an explicit model structure that facilitates Bayesian regularizations on the regression coefficients. An efficient parameter learning algorithm based on variational Bayesian expectation maximization is also designed for the BSMR. Two case studies including a numerical example and a real-world industrial process are supplied to assess the performance of the BSMR, which demonstrate the effectiveness and feasibility of the proposed approach.

Keywords: Sensors and Senor Fusion, Signal Processing
Abstract: Radars and automatic dependent surveillance -broadcast (ADS-B) are two important surveillance technologies in aerial surveillance networks. For this situations with different systematic errors of 2D radars and their time-difference-arrival (TOA) measurements in the fusion center, a fuzzy track initialization method based on topology sequences (TS-FTI) for heterogeneous sensors is proposed. In this proposed method, topology sequences of various measurements from a radar and an ADS-B receiver are respectively constructed. Then the topology sequence method is utilized to classify these measurements. The measurement sets of candidate targets can be constructed by accumulating measurements in several successive sampling intervals. Finally, a fuzzy Hough transform (FHT) method is used to detect tracks. The performance of the TS-FTI method is evaluated by simulation experiments, and it is found to be better than that of the track initialization method based on standard Hough transform (HT-TI) in calculated complexity and correct initialization rate.

Keywords: Robotics and Motion Control, Identification and Estimation, Control Applications
Abstract: This paper presents a three-dimensional (3D) cooperative Simultaneous-Location-and-Mapping (SLAM) method for a quadrotor flying together with a differential driving autonomous ground robot (AGR) in indoor environments. An ORB (Oriented Fast and Rotated BRIEF)-SLAM approach is used to find a 3D map and poses of individual quadrotor simultaneously, and the particle-filter SLAM approach is used to construct 2D map of the global environment for the AGR. A more accurate 3D pose method for the quadrotor is proposed with the assistance of AGR. The two SLAM approaches and quadrotor pose estimation method are operated under the robotic operation system (ROS) environment. One experiment is conducted to show the feasibility and effectiveness of the proposed method.

Keywords: Human-Machine Systems, Robotics and Motion Control, Control Applications
Abstract: Along with fast progress in their ability and flexibility, more robots are introduced for automation, and applied for more complicated tasks. Consequently, it demands more versatile and advanced manipulative devices for task manipulation and teaching. We thus propose a novel manipulation system based on virtual reality (VR). This system is intended for achieving 3D manipulation in a real-time manner. VR is recognized for capable of providing immersive feeling for the user. Meanwhile, it also faces the challenge in making the VR environment as close as the real one. To tackle this, we propose building a point cloud model of the real environment and integrating it with the virtual one. Meanwhile, to ease the load of the user during manipulation, we also develop a user-friendly interface, including a mechanism that can adjust the resolution of the command according to task complexity. Experiments are conducted to evaluate system’s performance, and questionnaires administered for acquiring user’s feedback.

Keywords: Fuzzy Neural Systems, LMIs, Control Applications
Abstract: This paper proposed the design of an underactuated robot controller based on polynomial fuzzy systems. First, we obtain the nonlinear state equations by the properties of the underactuated robot systems. Second, the polynomial fuzzy model can be constructed by the nonlinear state equations. We apply the strategy of parallel distributed compensation to design the nonlinear controller. To guarantee the stability of the underactuated robot system, the constraint conditions are derived using the polynomial Lyapunov function. Furthermore, the stability conditions are represented in terms of sum of squares of the polynomial fuzzy model. In order to improve the performance of control system, we use the SOSTOOL to design the polynomial fuzzy controller.

Keywords: Manufacturing Systems, Control Applications
Abstract: This paper presents an object volume measurement system on a conveyor belt. A client-server architecture is proposed to obtain a flexible and efficient measurement system for object size on the conveyor belt. The client works to integrate the sensor data and convert them into three dimensional point cloud. The server is responsible for calculating the object size. A laser scanner scans the object on the conveyor belt that moves with a constant speed. We applied the trigonometric function method to integrate two-dimensional distance data form the laser scanner and encoder data of the conveyor belt to obtain three-dimensional point cloud data. A progressive morphological filter was adopted to segment the background point cloud and the object point cloud. Then a convex hull algorithm was applied to find the set of the smallest convex polygon that contains all the object point cloud. Further, we can find a rectangle which has the smallest area to determine the object size. The experimental results show that the shape of object can be square, cylindrical or irregular. When the conveyor belt speed is set at 20 cm/s, the percentage error of the object size measurement is around 5% with the laser scanner installed at 50 cm above the conveyor belt and that within 7% with the laser scanner installed at 100cm.

Keywords: Robotics and Motion Control
Abstract: A simultaneous localization and calibration system (SLAC) by using two flying cameras is proposed in this research. The main purpose of the proposed system is to calibrate the transformation between an active 3D camera and a mobile manipulator. The system can be applied to resolve the problem of fixed workspace and expand the workspace in automated picking and assembly systems for a variety of objects. The transformations among the mobile manipulator, the working platform, and the active 3D camera can be determined by using Extended Kalman Filtering - Simultaneous Localization and Calibration (EKF-SLAC) through estimation of positions of feature points in the world frame based on two flying cameras. After estimating the transformations, two mobile platforms, each with the manipulator and the 3D camera, respectively, are controlled to move around the working platform. Finally, experimental results are provided to validate the performance of the approach developed in this paper.

Keywords: Cooperative Control, Decentralized Control, Sampled-data control
Abstract: This paper focuses on the consensus problem for second-order continuous-time multi-agent systems (MASs) with randomly switching topologies. A novel rectangular impulsive protocol of heterogeneous control widths is developed by utilizing sampled data, which is beneficial for a collection of agents with incongruent actuator capacities. By the model transformation and matrix theories, sufficient conditions, showing that the gains need not to be identical for all agents, and can be selected dependent on the local topology only, are established to guarantee the consensus of systems. A numerical example is delivered to validate the effectiveness of the obtained results.

Keywords: Cooperative Control, Filtering, Networked Control Systems
Abstract: This paper presents a collaborative pose filtering algorithm for distributed localization of a team of heterogeneous robots moving in 3D space. Each robot estimates its own pose (attitude and translation and associated covariance matrices) with respect to a global reference frame using velocity measurements, absolute measurements, relative inter-vehicle measurements and communicated pose estimates of nearby vehicles. Our distributed filtering mechanism is derived based on distributed nonlinear least squares optimization, and transforms relative measurements and communicated pose estimates obtained from nearby vehicles into the form of landmark measurements. The resulting measurements can readily be utilized with any pose filtering algorithm to achieve distributed localization of individual vehicles. The proposed approach is compatible with a range of covariance tuning approaches. In this paper the Geometric Approximate Minimum Energy (GAME) filter on the special Euclidean group SE(3) is utilized as the pose filtering algorithm. A continuous-discrete version of the GAME filter is provided that is able to update the continuously predicted pose estimate with the absolute and relative measurements obtained in discrete time. We validate the proposed algorithms in simulation, showing platforms can achieve localization with minimal landmark measurements.

Keywords: Cooperative Control, Linear Systems, Control Applications
Abstract: In this paper, a novel distributed event-triggeredscheme is presented to solve the problem of the leader-followingconsensus for a class of multi-agent systems with general lineardynamics under fixed topology. At first, a sufficient conditionof the leader-following consensus for multi-agent systems basedon the local sampled state is presented. Furthermore, we provethat the proposed distributed event-triggered control protocolscan exclude the Zeno behavior. Finally, We have applied thedesigned event-triggered communication strategy and controllerto vehicle platooning, and the effectiveness and efficiency of theproposed approach is simulated in the prescan.Index Terms: Multi-agent systems, event-triggered control,leader-follower consensus, networked control

Keywords: Cooperative Control, Networked Control Systems, Decentralized Control
Abstract: This paper addresses the leader-follower consensus problem in discrete time under fixed and time-invariant communication topology. Each agent follows a general linear dynamic and is equipped with a local Kalman estimator. While many literature illustrated a lower bound for convergence in continuous time, with similar form of feedback controller, we show that there exist an upper bound in coupling gain for the fixed gain controller. A novel distributed adaptive controller is also introduced, which only depends on local estimation of eigenvalue and neighbors' information. The performance and convergence speed of the proposed protocol are analyzed, and is demonstrated with numerical simulations.

Keywords: Cooperative Control, Networked Control Systems, LMIs
Abstract: This paper proposes robust control synthesis for homogeneous leaderless multi-agent systems (MASs) subjected to parametric uncertainty and exogenous disturbance. We employ an approach of robust H2 hierarchical decentralized control. This approach utilizes a linear quadratic performance criterion which composes of local and global terms. Local term represents local control action of agents whereas the global term deals with cooperation among agents. We formulate design of the local and global feedback control laws as optimization over linear matrix inequality (LMI). Furthermore, the LMI formulation can incorporate a specified constraint on disturbance attenuation. Finally, a design procedure and numerical examples are provided to illustrate the effectiveness of the proposed robust H2 design approach.

Keywords: Cooperative Control, Networked Control Systems, Optimal Control and Optimization
Abstract: This paper focuses on the design of the event-triggered distributed optimal consensus control for a multi-agent system with saturation actuator under a weight-balanced and strongly connected digraph. An event-triggered control protocol with a sigmoid function is presented, which reduces the communication workload among agents and overcomes the actuator saturation. The convergence of the multi-agent system to the distributed optimal consensus point is transformed into stability analysis of the corresponding closed-loop systems, which is proved by Lyapunov theory. Furthermore, it is shown that there is no Zeno behavior for such a protocol. Finally, an example is presented to demonstrate the effectiveness of the proposed control protocol.

Keywords: Behavioural Systems, Computational Intelligence
Abstract: This paper investigates by simulation the change of farmers' intention to shift from implementing incremental to transformational adaptation. An agent-based model is developed to simulate the change of farmers' intention. The intention level, which is composed mainly of opinion and information variables about incremental and transformational adaptation, is the main determinant of farmers' decisions of when to shift. Farmers update their opinion according to their connections in opinion networks layer and adjust their information according to their connections in information networks layer. The results showed that an increase in the number of farmers implementing transformational adaptation occurred when a preparatory phase was introduced. A preparatory phase is a phase to encourage further the farmers' opinion to implement transformational adaptation. This paper contributes to the understanding of the transition process to transformational adaptation and the modeling of the change of farmers' intention based on opinion and information of others in a different layer of network connections.

Keywords: Discrete Event Systems, Nonlinear Control, Networked Control Systems
Abstract: There are many finite-state and event-driven types of discrete systems, e.g., manufacturing processes, industry and welfare robots, and networked control systems, and so on. However, the analysis and design of such discrete control systems have not been established, because those systems have severe nonlinear characteristics and do not respond continuously in time. In this paper, the stability of discrete event control systems is studied based on multiple metrics and simultaneous inequalities. Especially, in this paper, the structures of discrete event types of systems are analyzed using connection matrices (i.e., permutation (0,1)-matrices). The relationship between connection matrices and graph representations is also reviewed in general. A stability condition is derived based on the concept of nonnegative inverse matrices (so-called M-matrices). Numerical examples are shown to clarify the stability and boundedness of discrete-event control systems.

Keywords: Markov Processes, Hybrid Systems
Abstract: In this paper, the problem of event-triggered mixed and passive control for a class of time delay stochastic Markov jump systems subject to input constraint is addressed. In order to reduce network burden, a useful event-triggered scheme is proposed. Then, due to network-induced delays, a time-delay model analysis approach is used to reconstruct the system. Analysis and design of state feedback event-triggered control is obtained such that the resulting system is stochastically stable. Sufficient conditions are obtained in terms of liner matrix inequalities. Finally, a numerical example is given to illustrate that the proposed method is effective.

Keywords: Multivariable Control, AI and Expert Systems, Adaptive Control and Tuning
Abstract: The efficiency of the grinding mill process plays significant role in overall performance of the mine circuit. The decisions taken at this early stage of ore influence the whole downstream up to final product storage. Most of already used control systems incorporate measurement of the quality of the grinding process output product which is a delayed information. The reaction to deviations from quality set points may be calculated with large input error. The proposed solution uses the set of implicit correlation functions defined for the pre-specified Fragmentation Size Distribution curves of the input ore feed. This property is used to determine the future behavior of the grinding process and does not introduce unnecessary delay in the control loop. The property may be provided by an additional sensor system based on the video image of the material transported to the mill by the conveyor belt (line scan camera, laser profiler, line 3D camera). The dedicated tool – Grinding Mill Optimizer – was developed and used to perform the analysis of the dynamic model of the grinding process. The model is based on the basis of the experimental data.

Keywords: Nonlinear Control, Switched Systems, LMIs
Abstract: Computing the Region of Attraction of switched nonlinear systems is an interesting but challenging problem. Approaches based on a common Lyapunov function are effective, while the estimation result is sometimes conservative when switched systems do not share a common Lyapunov function. For estimating the RA of switched polynomial systems, this paper proposes a method via a continuous piecewise polynomial Lyapunov function. The main idea is to find a Lyapunov function separately for each subsystem, and to guarantee the continuity of Lyapunov functions in the transitions amongst subsystems. The sublevel sets of a continuous piecewise Lyapunov function are exploited to inner-approximate the RA, and less conservative results are obtained compared to the common Lyapunov function approach. Finally, the effectiveness of proposed method is illustrated by examples.

Keywords: Mechatronics, Sensors and Senor Fusion, Power Systems and Power Electronics
Abstract: Superconducting (SC) technique is applied to a SC magnetic levitation system. The levitation system is composed of a SC coil, a copper coil, a levitated object, a photo sensor, a PID controller, and power amplifiers. Persistent current in SC coil and control current in copper coil are used for levitating object and controlling object, respectively. In this paper, large gap trial on the system is performed, and the dynamic characteristics of the levitated object are performed. As a result, it is found that the levitated object continues to levitate at a distance 43 mm for 14 s. The details of the SC persistent current are discussed. This may be the first trial that SC persistent current is used for a magnetic levitation system.

Keywords: Mechatronics, Transportation Systems
Abstract: In a steel plate factory, conveyance is performed while the steel plate is in contact with a roller, and the quality deterioration of the steel plate surface is a problem. Therefore, to perform noncontact conveyance of a thin steel plate using the attraction force of electromagnets, research was conducted on the levitation stability of thin steel plates. Previously, a bending magnetic-levitation system capable of levitating using a bending thin steel plate was proposed. It was confirmed that the levitating stability is improved by bending levitation. In this report, a bending magnetic-levitation system was constructed that can input disturbances to simulate an actual usage environment, and magnetic-levitation experiments on a thin steel plate were conducted using disturbance cancellation control. The levitation target was a rectangular galvanized steel sheet (SS400) with a length of 800 mm, a width of 600 mm, and a thickness of 0.19 mm.

Keywords: Mechatronics, Transportation Systems, Optimal Control and Optimization
Abstract: In thin steel plate production lines widely used for various industrial products, thin steel plates are contact-conveyed by rollers in the conveying process. Owing to this conveying method, the quality of the surface deteriorates, resulting in degradation such as scratches or peeling of the plating layer of the thin steel plate. As a solution to these problems, we studied a noncontact magnetic levitation system for a rectangular thin steel plate using electromagnets and permanent magnets. We determined the optimal placement of permanent magnets using a genetic algorithm (GA), which searches for placements using an evaluation function. However, although the evaluation function was defined by the GA, since only a basic examination was conducted, the weight coefficient used in the evaluation was insufficient. In this paper, we changed the weight coefficient of the evaluation function and compared and analyzed the results of the permanent magnet arrangement determined by the GA. It is possible to obtain an optimum permanent magnet arrangement in which the levitation stability is improved by experimentally verifying the effects of the maximum deflection and average deflection on levitation performance. The levitation experiment is carried out using each weight coefficient for permanent magnet arrangement. Then, the levitation stability is evaluated.

Keywords: Power Systems and Power Electronics, Nonlinear Control, Mechatronics
Abstract: In this report, as the environmental power generation and wave power generation device, inverted pendulum type power generator based on autoparametric resonance is devised. Theoretical study and experimental verification of proposed device were performed. The autoparametric resonance is an unstable vibration generated by nonlinear coupling between the main system and the subsystem in which the vibration directions of two degrees of freedom or more are orthogonal. The purpose of this research is to develop a system which converts vibration external force of low frequency band to high efficiency for rotation of pendulum using this autoparametric excitation. A model of a two degree of freedom system composed of an inverted pendulum supported by a spring system, and a mass-spring system was devised. Approximate analysis and shooting method were used to calculate the amplitude of the main resonance and the amplitude of the pendulum in each system. We examined the influence of parameters theoretically. Experiments using model device were also conducted to verify the validity of the theoretical results.

Keywords: Sensors and Senor Fusion, Mechatronics, Control Applications
Abstract: A mass measurement system using relay feedback of velocity was developed. In this system, the velocity of the object was fed back through a relay with a hysteresis. Although the efficacy of the proposed method has been already confirmed experimentally, it was subject to drift mainly because only the velocity was fed back. To prevent such drift, a spring element was added to produce restoring force. However, smaller drifts still occurred and the trajectory of the object fluctuated because the switching positions are not determined uniquely. In this paper, an estimation formula is derived, which can estimate the mass regardless of switching positions. The efficacy of the derived formula is confirmed experimentally.

Keywords: Education, Embedded Systems
Abstract: Commercial educational tools for teaching feedback concepts in control systems engineering and mechatronics are generally expensive, large, complex and sensitive instruments; therefore cannot be used for homework assignments outside the classroom. This paper presents a novel open-source teaching aid that can be readily manufactured under 3 EUR and as such, is financially accessible to students and universities operating on a tight budget. The device proposed in this paper implements a simple optical experiment, allowing students to follow a prescribed brightness level using feedback control concepts. In addition to real-time control, the apparatus is also suitable for teaching signal processing and system identification principles. The educational aid presented here is attached to the popular Arduino microcontroller prototyping platform in a form of a miniature extension shield, thereby using a standardized physical layout and software ecosystem. We describe the hardware, the application programming interface (API) and library written in C/C++ for the Arduino integrated development environment (IDE) and the accompanying Simulink toolbox; moreover present sample exercises for system identification and proportional-integral-derivative (PID) control.

Keywords: Nonlinear Control
Abstract: This paper investigated the stabilization control problem for the nonholonomic vehicle with second order dynamics, which evolves in Lie group SE(2). At first, we designed the control law for the vehicle by dint of the exponential coordinates in Lie algebra, and then proved the stability of the closed loop system by choosing an appropriate Lyapunov function. The greatest novelty of the proposed control law was the global convergence property. In other words, the vehicle was able to be stabilized to the identity configuration from any position with arbitrary orientation. Furthermore, the initial attitude angle specified as Pi or -Pi would correspond to different trajectories, which provided choices in case of limitations imposed by surroundings. In order to demonstrate the effectiveness of the control law, numerical simulations were presented at the end. To the best of our knowledge, it is the first time that a global stabilization control algorithm for nonholonomic vehicles is proposed directly based on second order dynamics without using the backstepping technique.

Keywords: Nonlinear Control
Abstract: This paper investigates the finite-time simultaneous stabilization problem for two nonlinear descriptor systems with actuator saturation. Firstly, under the output feedback controller, we combine two nonlinear descriptor systems to generate an augmented descriptor system. Furthermore, a sufficient condition is given to guarantee that the augmented descriptor system is finite-time stabilization, which deduces two nonlinear descriptor systems are the finite-time simultaneous stabilization. Finally, a numerical example is represented to illustrate the effectiveness of the proposed approach in this paper.

Keywords: Nonlinear Control, Control Applications
Abstract: Combustion oscillations occur themselves as pressure and heat release oscillations in lean premixed combustors, and may cause some unexpected damage. This paper proposes a design method of a reset controller to eliminate a combustion oscillation in a lean premixed combustor model. We consider a plant model consisting of a linear system with a nonlinear feedback element and a reset controller using a first-order lag element, which is called a first-order reset element (FORE). We show parameter conditions of the reset controller for which limit cycles are eliminated, using a describing function of the nonlinear element. We apply the proposed design method of the reset controller and a flame describing function to eliminate the combustion oscillation in the lean premixed combustor model and show its effectiveness appropriately.

Keywords: Nonlinear Control, Cooperative Control, Variable-Structure/Sliding-Mode Control
Abstract: This paper studies the velocity and altitude consensus problems of multi-hypersonic vehicle systems with disturbances. By the combination of integral sliding-mode control method and high-order disturbance observer technique, consensus protocols for a class of leaderless multi-hypersonic vehicle systems are proposed to achieve the velocity and altitude consensus. Firstly, high-order disturbance observers are designed to estimate the disturbances affecting each hypersonic vehicle. Then, based on integral sliding-mode control and disturbance estimates, a consensus scheme is presented to achieve the velocity and altitude asymptotic consensus of the multi-hypersonic vehicle systems. Moreover, numerical simulations are given to validate the efficiency of the proposed consensus algorithms.

Keywords: Nonlinear Control, Delay systems, Control Applications
Abstract: This paper is devoted to stability analysis of Hamiltonian systems subject to actuator saturation and input delay. The dissipative structural properties of the Hamiltonian systems are fully considered and sufficient conditions obtained via Wirtinger inequalities method are stated to guarantee the asymptotical stability of the closed-loop systems when control saturations effectively occur. An augmented Lyapunov-Krasovskill functional is constructed and Wirtinger inequalities are utilised to estimate the derivatives of the candidate Lyapunov functionals more accurately. The time-varying delay is considered and corresponding stability criterion is established for the system. An application on power systems is illustrated to show the effectiveness and less conservatism of the developed theoretical method.

Keywords: Adaptive Control and Tuning, Linear Systems, Predictive Control
Abstract: A control separation based LQ control design has the capability for achieving both optimal tracking and disturbance rejection. In this paper, a control separation based model predictive control (MPC) scheme is developed for rejection of unmatched input disturbances of possibly nonminimum-phase time-varying systems. A control separation based MPC framework is formulated for disturbance rejection, which has the enhanced capability for handling system parameter variations by a closed-loop system operation. Such a framework is built in the development of three components: a baseline model predictive control design for linear time-varying systems, a control separation based LQ control design for unmatched input disturbances, and a control separation based MPC disturbance rejection design for linear time-varying systems. The analysis of system stability and output regulation is presented, and a comparison to traditional LQ based designs is given. Simulation study is conducted for the turbulence compensation problem of the hypersonic vehicles, and its results verify the effectiveness of the new control separation based MPC design for disturbance rejection.

Keywords: Cooperative Control, Predictive Control, Linear Systems
Abstract: This paper addresses the distributed receding horizon control (DRHC) for multi-agent systems with neighbourhood cooperation. The agents are coupled in the cost function and the physical constraints. The proposed approach is based on the synchronous framework, so only assumed predictive information is available for local controllers. In order to improve the global system performance, a neighbour-based DRHC strategy is proposed. The performance index involving each agent and its neighbours is optimized to determine the control input. By applying the proposed DRHC approach, the recursive feasibility and exponential stability of global system are guaranteed. An example is provided to verify the effectiveness of the result.

Keywords: Delay systems, Control Applications, Predictive Control
Abstract: This paper presents the experimental results for an inverted pendulum having a flexible arm with artificial time delay. State predictive control requires integral approximation. The approximation error increase depending on the approximation method, as a result it causes an unstable response. However, this problem can be solved using the low-pass approximations reported by L-Mirkin and the convolution approximation by reported by QC-Zhong in 2004. Our experiments have shown that the inverted pendulum with time delay is stabilized under approximating distributed delay control laws with the low-pass approximations and the convolution approximation. Furthermore, we show that the combination method that merged low-pass and convolution approximation from both features is more effective.

Keywords: Nonlinear Control, Predictive Control, Optimal Control and Optimization
Abstract: In this paper, a novel model predictive control based on the dynamic linearization technology is proposed for a class of single-input and single-output nonlinear discretetime systems. By using the compact form dynamic linearization method, the designed controller is in advance constructed as a parameterized control law, which is an equivalent expression of an ideal controller. Instead of optimizing a sequence of control inputs for the traditional model predictive control, the issue is transformed into the parameter optimization of the constructed control law under the model predictive control scheme in closed loop. The effectiveness of the proposed model predictive control is demonstrated by a numerical example on discrete-time linear and nonlinear system through comparing with the traditional model predictive control.

Keywords: Nonlinear Control, Predictive Control, Robust Control
Abstract: Nonlinear model predictive control (NMPC) has been widely applied in the chemical industry for its performance of dealing with the multiple input multiple output problem (MIMO) and handling constraints. However, the performance of NMPC would be affected by the accuracy of the model. The NMPC controller has to be robust to uncertainties in the model. In this paper, the scenario-tree based on multi-stage NMPC approach has been applied to the semi-batch polymerization reactor. In this approach, in order to ensure the reasonableness of the uncertain variables and scenario tree number, a Monte Carlo-based second-order nonlinear model and K-means cluster algorithm have been proposed. The weights of each scenario branches are also considered into variable. The simulation results show that the performance of the improved method is better and the variable weights has a good ability of improving the performance of controller.

Keywords: Optimal Control and Optimization, Predictive Control, Nonlinear Control
Abstract: This paper presents an simple and easy to implement representation for the piecewise linear model. To accomplish this, an optimized lattice piecewise-linear representation is proposed. The optimization process is based on irredundant simplification and multilevel logic optimization. A heuristic algorithm is used to obtain the multilevel form of lattice piecewise linear representations. Besides, a multi-layer network structure is proposed for the implementation of lattice piecewise linear representations. The proposed strategy is applied to explicit model predictive control and the simulation result shows the effectiveness of the multilevel optimization method

Keywords: Identification and Estimation
Abstract: A new recursive identification algorithm with output weighted cosine basis functions (WCS) is investigated for the time-varying systems. After introducing a weight factor to the output of a time-varying process within the current time window, the weighted time-varying parameters, which are expanded into the virtual even periodic functions, are explicitly approximated by the cosine series. Following the orthogonality of the trigonometric functions, the parameter estimation problem becomes to the estimation problem of the series coefficients with respect to each degree of the cosine harmonic term in recursive manner. It is demonstrated that weight factor decreases the degree of cosine series and suppress the series approximation error so that the proposed algorithm has better tracking performance for rapid-variation than the conventional basis functions based identification algorithms and the existing standard methods such as RLS, LMS/NLMS, AP/BOP.

Keywords: Identification and Estimation, Biological Systems, Signal Processing
Abstract: Single particle tracking (SPT) is a powerful class of methods for studying the dynamics of biomolecules inside living cells. The techniques reveal both trajectories of individual particles, with a resolution well below the diffraction limit of light, and the parameters defining the motion model, such as diffusion coefficients and confinement lengths. Existing algorithms assume these parameters are constant throughout an experiment. However, it has been demonstrated that they often vary with time as the tracked particles move through different regions in the cell or as conditions inside the cell change in response to stimuli. In this work we apply the method of local Maximum Likelihood (ML) estimation to the SPT application combined with change detection. Local ML uses a sliding window over the data, estimating the model parameters in each window. Once we have found the values for the parameters before and after the change, we apply offline change detection to know the exact time of the change. Then, we reestimate these parameters and show that there is an improvement in the estimation of key parameters found in SPT. Preliminary results using simulated data with a basic diffusion model with additive Gaussian noise show that our proposed algorithm is able to track abrupt changes in the parameters as they evolve during a trajectory.

Keywords: Identification and Estimation, Computational Intelligence, Complex Systems and Networks
Abstract: Deep learning is widely used in soft sensors to monitor product quality in complicated batch processes. Most soft sensoring models are formed as auto-regressive with exogenous inputs (ARX) to deal with time series problems. However, it is difficult to identify the order of ARX model without any empirical knowledge. In order to avoid this issue, a novel modelling method combined the multi-phase deep recurrent neural network (RNN) and a steady state identification (SSID) is proposed in the study. First, the process is divided into several sub-phases by using SSID analysis with a moving window. Then, a RNN model is built in each sub-phase. The final state of each phase is used as the initial memory for next phase, which ensures the continuity of the entire process. The proposed algorithm is evaluated by the application in the penicillin fermentation process.

Keywords: Identification and Estimation, Fault Detection
Abstract: Determining the age of a battery under use is a highly critical but unsolved problem. On one hand , knowing battery age improves the reliability of the system using the battery. On the other hand, safety critical systems have to use new batteries on the start of each run, resulting in huge battery costs. There are numerous attempts at finding the battery age but owing to the nonlinear nature of the chemical processes in a battery, its modeling is a challenging problem. Battery ageing problem has been traditionally treated in a model-based FDI framework. The FDI techniques mostly depend upon the precision of the battery model. Obtaining accurate battery models is still an unsolved problem. Recently, data driven methods are getting acceptable by the industry owing to the ready availability of data and the growing trend towards data analytics. However, these data driven methods are not able to benefit from the battery dynamics and ground truth, considering the battery as a black box. A hybrid but rigorous approach, based on structural analysis and clustering concepts, is proposed which takes the best of both worlds by devising data driven FDI methodology benefiting from the ground truth provided by the battery models based FDI. This approach puts rigour into the classical data driven approaches. It also earmarks the right battery variables to be used in the data analysis, thus considerably decreasing the data size involved.

Keywords: Identification and Estimation, Fault Detection, Computational Intelligence
Abstract: As one of the main control subsystem implemented for controlling the wind turbine nacelle position in parallel with the inflow wind, the yaw control system directly determines the power generation performance of wind turbines. Thus, accurate measurement of yaw error is important in yaw control strategy. However, the existence of inherent misalignments on yaw error usually severely impact the performance of yaw control strategies. Aiming at the identification of yaw error inherent misalignment, a data-mining based inherent misalignment identification and compensation approach for yaw error is proposed. The raw data set is firstly preprocessed and further segmented into different partitions. A curve fitting technique is finally implemented for yaw error inherent misalignment estimation. The simulation data set from a simulation software GH Bladed is used to testify the effectiveness of this approach, and the result shows high accuracy on yaw error inherent misalignment identification.

Keywords: Identification and Estimation, Linear Systems
Abstract: This paper proposes an innovative identification scheme to estimate parameters constituting linear relations in time–invariant systems: the bounding box recursive Frisch scheme. A novel recursive version of the Frisch scheme, a linear estimator characterised by mild prior assumptions in the error-in-variables (EIV) framework, has been derived. The fast computational time and convergence in the identification of linear systems are the most relevant feature of this recursive version of the scheme. The performance of the developed algorithm has been evaluated trough numerical simulations. Results proved the effectiveness and accuracy of the proposed solution.

Keywords: Predictive Control, Mechatronics, Optimal Control and Optimization
Abstract: Automatic digging operation utilizing information of surrounding environments for hydraulic excavators has been studied. Automatic digging is realized by tracking control where desirable digging path is necessary. Approaches based on optimal calculation for designing the digging path have been proposed. When a workspace is larger than a capacity of a bucket, multiple excavations are necessary: a method to design an optimal digging path corresponding to each digging motion is required. This paper proposes a method that achieves the target shape automatically by considering remaining soil. Since the remaining soil decreases by each digging, the soil amount is utilized as a weight for index function. By using the evaluation reflecting decrease of the remaining soil, a digging path approaching the target shape in every excavation is realized. The effectiveness of the proposed method is verified through simulations and experiments with a hydraulic excavator.

Keywords: Automotive Systems, Nonlinear Control, Mechatronics
Abstract: Active steering control for lane keeping is a significant technique applied for autonomous ground vehicles (AGVs). This paper addresses a problem of high-accuracy control for lane keeping of AGVs subject to time-varying vehicle speed and parameter uncertainties. A robust adaptive triple-step nonlinear control scheme is presented. In this strategy, a nonlinear reference generator is designed to generate a virtual reference signal. Then, a robust triple-step nonlinear controller with adaptive update laws is then proposed for lane keeping of AGVs. It is shown by the Lyapunov stability analysis that the lateral offset of AGV is input-to-state (ISS) in the presence of bounded perturbation of tire stiffness coefficient. The effectiveness of the approach is verified on a high-fidelity full-vehicle model constructed in veDYNA and MATLAB/Simulink.

Keywords: Autonomous Systems, Cooperative Control, Robotics and Motion Control
Abstract: This paper presents dynamic coverage control using multiple quadcopters for a surveillance of buildings or facilities. The　surveillance system requires to move in the task area, detect and follow an invader. For observing an unknown invader, a fixed flight route cannot be chosen. In this paper, an autonomous surveillance method is proposed to detect an unknown invader considering the feature of the mounted sensor on a quadcopter. At the same time, a quadcopter follows an invader while patrolling in the task area. In order to verify the validity of the proposed method, the simulation is performed, and then the result of the simulation shows the effectiveness.

Keywords: Control Applications, Sensors and Senor Fusion, Mechatronics
Abstract: The purpose of this paper is the experimental validation of the sensor fusion designed for the possible future use in the walking-like mechanical systems design. The validation is made using the actuated leg being the part of the four-link laboratory walking-like system and it is equipped with several sensors. The experiments aim to track the reference angular positions trajectory using the state feedback controller. The information needed by that feedback controller (angular positions, velocities and input currents of DC motors actuating rotary joints) is obtained from the sensors measurements. Two types of experiments are compared: (i) using these measurements directly; (ii) pre-processing them via the designed sensor fusion method. The fusion is based on the so-called low-level hybrid Extended Kalman Filter (HEKF) realization, which has the future potential to be implemented on the PCBs attached to the legs links only. Yet, the presented experimental results demonstrate the prevalence of the control using the fused data.

Keywords: Sensors and Senor Fusion, Robotics and Motion Control, Optimal Control and Optimization
Abstract: In this paper, we describe accuracy verification of simultaneous localization and mapping (SLAM) in a crowded area where measured data often becomes insufficient. To realize autonomous locomotion of robots in an unknown environment, they need to create an environment map while estimating self-pose with measured data. When the robot works in an area where many people exist, however, the measured data is frequently occluded by them and become insufficient to achieve the SLAM. Applying moving horizon estimation to SLAM, when the measured data is insufficient, the evaluation of the motion model becomes more dominant than that of the matching error of the measured data. To verify the effectiveness of SLAM based on MHE, we conduct experiments in the crowded area to compare the result with that of SLAM based on extended Kalman filter. Also, we applied sequential quadratic programming to the optimization to reduce the computational complexity of the proposed method. It was confirmed that the computational complexity was reduced by about 88 % compared to the trust region method.

Keywords: Sensors and Senor Fusion, Mechatronics, Transportation Systems
Abstract: To guarantee high precision control and assure the reliability and safety of the railway systems operation, highly accurate measurement data from different onboard and wayside sensors are needed. This paper proposes a solution approach to obtain more accurate measurement data which are collected during train movement using an Unscented Kalman Filter (UKF)-based multi sensors data fusion. Several sensors that are used in the proposed approach include indoor positioning systems, radio frequency identification, and rotary encoder. Experimental results that were conducted on a train model show how the proposed method effectively able to provide more accurate measurement data about the train position.

Keywords: Aerospace Engineering, Cooperative Control, Automata
Abstract: In this paper, a novel event-based distributed control scheme is proposed to address the coordinated control problem for multiple spacecraft formation flying, in the presence of mass uncertainties and external disturbances. Considering that the on-board resources in terms of communication and computation are limited, the event-triggered mechanism is applied to regulate the information transmission frequency among formation spacecraft and to govern the update time of the controllers. In doing so, each spacecraft only needs to broadcast information and update its own control command when the specified events occur, thus relaxing the communication network burden and saving on-board resources. Moreover, the inter-event time intervals are shown to be strictly positive so that no Zeno behavior executes. By Lyapunov's stability theorem and topology theory, it is proved that the formation-keeping maneuvers are globally asymptotically achieved. Finally, simulation results are presented to show the effectiveness of the proposed control scheme.

Keywords: Cooperative Control, Adaptive Control and Tuning
Abstract: This paper studies an open leader-following output consensus problem of multi-agent systems described by general uncertain linear systems. The control objective is to make the outputs of the follower agents with parametric uncertainties track a desired trajectory given by a virtual leader. For such general agent systems, a new distributed adaptive state feedback control framework is developed for multi-agent output consensus, without restrictive follower-leader matching conditions. This paper solves the state feedback output consensus problem for uncertain multi-agent systems with relative degree one. The adaptive control design has a desirable structure, simple as it is useful for many control applications, and essential as it is extensible to the higher relative degree case and/or the output feedback control case. Such a new distributed adaptive consensus scheme is designed based on model reference adaptive control which is capable of achieving desired tracking and effectively dealing with system parameter uncertainties. It guarantees the desired leader-following output consensus and closed-loop signal boundedness. A simulation study on a multiple-aircraft system verifies the effectiveness of the proposed adaptive multi-agent output consensus scheme.

Keywords: Cooperative Control, Autonomous Systems, Game Theory
Abstract: In this paper, we study the problem of distributed network topology control in order to minimise the received power of network communications at an adversary location. The proposed approach utilises a market-based distributed decision making mechanism to coordinate the deletion of links that contribute most to the received power at the adversary location whilst maintaining network connectivity. Given an initially strongly connected network and static agents, our approach guarantees that the network remains strongly connected and the received power at an adversary location is asymptotically minimised to a greedy optimal solution. The effectiveness of our approach is illustrated in a number of simulations.

Keywords: Cooperative Control, Autonomous Systems, Identification and Estimation
Abstract: This work addresses the localization and enclosing problem of a target which is stationary or moving by a group of mobile agents. Each agent is assumed to know its bearing angle with respect to the target. Using the bearing angle to the target, an estimator is proposed for each agent to localize the target, and a distributed control law is then designed. It is shown that when the target is stationary or moving with a bounded velocity, the group of agents globally converge to an exact uniform circular formation around the target or its neighborhood, respectively. The effectiveness of the proposed algorithm is illustrated via simulations.

Keywords: Cooperative Control, Decentralized Control, Linear Systems
Abstract: This paper presents the robust stability of the Hierarchical control structures in Multi Agent Systems (MAS). We provided an analysis that shows that Hierarchical structures which are more superior than the single-layer strategy in terms of convergence rate, are also more robust to weighted perturbations in links between agents in consensus network. Simulation results and graphical comparison support the theoretical results.

Keywords: Maritime Control, Observer Design, Nonlinear Control
Abstract: The design of reduced-order observers that estimate both unmeasured velocity and disturbance of sampled-data ships with unknown constant disturbance is considered. When the angular velocity of yaw of ships is small, it is shown that the reduced-order observer is semiglobal and practical in T fot the exact model of sampled-data ships. The proposed design of reduced-order observers is applied to the circular path following control of sampled-data underactuated ships with unknown constant disturbance where the angular velocity of yaw becomes small. The efficiency of the proposed design is shown by simulation results.

Keywords: Nonlinear Control, Optimal Control and Optimization, Quantum Information and Control
Abstract: Conservative dynamical systems propagate as stationary points of the action functional. Hence, dynamical-systems questions may be addressed by control-theoretic methods. Using this representation, it has previously been demonstrated that one may obtain fundamental solutions for two-point boundary value problems for some classes of conservative systems via solution of an associated dynamic program. It is also known that the gravitational and Coulomb potentials may be represented as stationary points of cubicly-parameterized quadratic functionals. Hence, stationary points of the action functional may be represented via iterated staticization of polynomial functionals. This leads to representations through operations on sets of solutions of differential Riccati equations (DREs). A key step in this process is the reordering of staticization operations.

Keywords: Quantum Information and Control
Abstract: Imperfect observation is an indispensable but often neglected part for practical measurement. In this work, we mainly investigate its effect upon estimating quantum states by focusing on several specific examples. It is shown that the accuracy of the quantum state estimation will be greatly degraded in the presence of imperfect observation. In order to reduce its destructive influence, a cautious estimation method and the adaptive measurement strategy are attempted. However, it turns out that both of the methods cannot always overcome the performance deterioration due to the observation error. The results warn us that we have to seriously deal with the problem of imperfect observation in practical quantum information processing.

Keywords: Sampled-data control, Quantum Information and Control, Nonlinear Control
Abstract: Using piecewise sampled-data control with finite-time settling function called vibration manipulation function (VMF), we tried to swing up a pendulum, whose natural period is τ, by driving a trolley under numerical simulations. We used VMF under the finite-time settling control to determine an acceleration of the trolley. In this study, we used three staged operations with equivalent angular displacement for swinging the pendulum up. After fixing the operational period as τ/4 and aimed angular velocity as 0.7 for the first-stage operation, we fixed the operational period as τ/10 and aimed angular velocity as 0 for the third-stage operation. Then we tried to change the operational period and aimed angular velocity for the second-stage operation in a simulation. In case the operational period as τ/20 and the aimed angular velocity as 0 or small negative value in the second-stage operation, we could swing up the pendulum much easier.

Keywords: Sampled-data control, Robust Control, Networked Control Systems
Abstract: An L2 gain bound is derived for an operator dependent on a saw-tooth time-varying delay that does not necessarily reset to a constant value. Operators of the kind considered arise in input-output based robust stability analysis of asynchronous sampled-data systems.

Keywords: Power Systems and Power Electronics, Switched Systems, Mechatronics
Abstract: This report deals with a control problem for continuous-time linear time-invariant systems with multi-degree-of-freedom PWM-type input. Since the PWM-type input systems are nonlinear in terms of the manipulable variables, its analysis and design is in general difficult. In this report, for the exact linearization method that has been recently proposed by the authors, the stability of the zeros of derived linear systems will be discussed.

Keywords: Control Applications, Mechatronics, Flexible Structures
Abstract: Recently, various input shaping logics have been developed to improve the performance of residual vibration suppression, and thus a benchmark device to compare the performance objectively is needed. This paper presents a detailed modeling analysis for system parameters of the benchmark apparatus developed recently for input shaping control in our laboratory. Real-time sampling performance using Linux is evaluated and verified. A reasonably accurate dynamic model of the system is obtained through several experimental and simulation studies, and an identification software tool as well. The obtained model is demonstrated and verified through applying a ZVD shaping control to the system.

Keywords: Identification and Estimation, Control Applications, Mechatronics
Abstract: This paper contains research on magnetic levitation system with two electromagnetic actuators in E shape configuration, located anti-parallel. The document presents influence of the coil current in the operating point on the lateral stiffness and damping of the levitating object, under the external static and dynamic load. Numerical model and experimental research, validated with support of image processing, are presented. The lateral displacement is identified.

Keywords: Mechatronics
Abstract: This paper discusses the stability of a tilt-controlling axial gap self-bearing motor with a single stator. The proposed motor consists of a stator and a disc rotor and is capable of controlling motor torque, axial displacement and tilt angles. By using passive stability in radial direction, it is possible to achieve non-contact levitation and rotation. In previous work, we have succeeded levitation and rotation with a two-pole rotor and a six-coil stator. However, there were problems with low stiffness and different tilt moment gains. To solve these problems, higher position of the center of gravity (COG) of the rotor and eight-coil stator are adopted. Axial force, motor torque, tilt moments and radial forces are theoretically analyzed, and the stability of radial motions are discussed. Results show that higher COG position increase the stability in radial motion. The experimental results show that the characteristics in tilt motions are almost the same, and the stable levitation and rotation are achieved.

Keywords: Mechatronics
Abstract: In the previous work, the authors have proposed a design of a magnetic levitated vertical axis wind turbine (VAWT) for power generation purposes by using two permanent magnets attractive type passive magnetic bearings where the rotor was actively controlled in one degree of freedom (DOF) in the axial direction. The proposed model is simpler than the other VAWT designs and has low cost; however, the radial stiffness is not high enough to rotate the rotor at high speeds. Therefore, this paper discusses the stiffness analysis of different rotor shapes which can be used in VAWT by three-dimensional (3-D) magnetic-field analysis. The simulation results will be compared with the experimental results to evaluate which rotor shape is suitable for stable levitation and rotation at the different wind speeds.

Keywords: Mechatronics
Abstract: Ultracompact mobility refers to vehicles that are intended for near-distance travel for one to two passengers. This mobility is compact and easy to turn around, so it can enter narrow roads and poor roads that are not paved. In such a road surface environment, it is susceptible to the influence of vibration caused by steps and the unevenness of the road surface, and deterioration of the ride comfort of the vehicle is expected even at low speed. The authors analyzed an organoleptic evaluation and biological information to improve the ride comfort based on a proposed control method. In this paper, the stress state of the occupant received by the vertical vibration is clarified from the cerebral blood flow, which is used as an indicator of the activity of the central nervous system.

Keywords: Mechatronics, Control Applications
Abstract: The accurate position control of exhaust gas recirculation (EGR) valve is important for emission reduction in internal combustion engine. In this paper, a nonlinear internal model control strategy for the position control of a linear motion EGR valve is proposed to compensate the effect of rate-dependent hysteresis and derive accurate positioning of the EGR valve plug. The modeling procedure of the EGR valve is presented. Then, the design method of the nonlinear internal model control is depicted based on the obtained nonlinear model of the valve. Finally, the control experiment of the EGR valve is illustrated.

Keywords: Nonlinear Control, Multivariable Control, Robust Control
Abstract: Based on the Lyapunov stability theorem, a design methodology of adaptive block backstepping controllers is proposed in this paper for a class of multi-input systems with input nonlinearity and dead zone to solve regulation problems. According to the number of block (m) in the dynamic equations, virtual inputs are firstly designed from the first block to the (m-1)th block. Then the proposed robust controller is designed from the last block. Adaptive mechanisms are also employed in each of the virtual inputs and the robust controller, hence the least upper bounds of perturbations are not required to be known in advance. The resultant controlled system is able to achieve asymptotic stability if all the control inputs is outside of the dead zone, and uniformly ultimately bounded is achieved if any one of the designed control inputs is inside of the dead zone. A numerical example is given for demonstrating the feasibility of the proposed control scheme.

Keywords: Nonlinear Control, Robotics and Motion Control, Variable-Structure/Sliding-Mode Control
Abstract: This paper is concerned with the position control problem of the planar active-passive-active (APA) underactuated manipulator, whose dynamic constraint is mainly caused by the second-order nonholonomic constraint. First, the dynamic model of the system is established and the target angles of the three links are calculated by using differential evolution algorithm. Then, we present a trajectory planning and tracking control strategy to realize the control objective, which is to stabilize the end-point from any initial position to the target position. We plan two stage trajectories, the first of which is planned for the active links. When the the active links track the first stage trajectories, they can reach to their target angles. The second one is planned for the first active link based on the differential evolution algorithm. When the first active link tracks the second stage trajectory, it will back to its target angle eventually. Meantime, the passive link will be controlled to its target angle. Then, we design sliding mode variable structure controllers to make active links track the planned trajectories, which can make the all links reach to the their target angles. Finally, numerical simulation results illuminate the effectiveness of the proposed strategy.

Keywords: Nonlinear Control, Robust Control, Robotics and Motion Control
Abstract: The control of non-linear systems has been an interesting research topic for many years. It is not feasible to control such systems using linear control because of uncertainties. Non-linear control like Sliding Mode Control (SMC) is robust against these uncertainties. Integration of SMC with Sliding Perturbation Observer (SPO) is a more robust controller with a perturbation compensation technique. Chattering is a drawback of SMC due to a high switching gain, which can be reduced by altering the structure of SMC, by multiplying the gain with the velocity error. Integration of this proportional derivative gain PDSMC with SPO introduces a more robust controller with a faster convergence to the desired state.

Keywords: Nonlinear Control, Robust Control, System Theory
Abstract: Based on the switching strategy, this paper presents an finite frequency formulation for the robust stabilization of singularly perturbed uncertain systems. An uncertain system is modeled as a parallel connection of a nominal system and an error system represented in the form of a linear parameter-varying system. A family of dynamic output feedback controllers are designed to enhance the robustness of the error system against finite frequency uncertainties over the operational region. A hysteresis switching is proposed to coordinate the candidate controllers. The proposed scheme is applied in the longitudinal control of an F16 aircraft to verify its effectiveness and merits.

Keywords: Nonlinear Control, System Theory
Abstract: This paper investigates the problem of finite-time stabilization for a class of high-order nonlinear systems with zero dynamic. The systems under investigation allow inherent nonlinearities to include high-order and low-order nonlinear growth rates, except for unmeasurable dynamic uncertainties. On basis of the constructions of integral Lyapunov functions with sign functions and input-to-state stability property, a partial state feedback stabilizer is proposed to guarantee that the convergence of system state is faster than traditional finitetime stabilizers. In particular, the convergent time can be adjusted through preassigning design parameters. The novelty lies in a distinct perspective to applying fast finite-time stability in partial state feedback control design which was previously regarded as a rather difficult problem.

Keywords: Nonlinear Control, System Theory
Abstract: This study discusses a condition of the stability with density functions, which is known as a dual theorem of the Lyapunov stability theorem, for non-smooth dynamical systems. In the previous study, the stability analysis can be applied only for smooth systems. The aim of this study is to relax the smoothness conditions to develop the analysis for non-smooth dynamical systems, which would appear in global stabilization problems of nonlinear systems and the analysis of the finite-time stability. To this end, we develop an extension of a density function approach for non-smooth systems. We focus on a class of non-smooth systems and we show the stability analysis of non-smooth systems for the class of the systems with density functions. We also provide numerical examples to show the validness of the presented results.

Keywords: Autonomous Systems, Predictive Control, Robotics and Motion Control
Abstract: Some challenging control design problems include non-linear vehicle dynamics, fast sampling time and limited computing resources on automated hardware. MPC has the ability to systematically consider nonlinearity, future predictions and operating constraints of the control system framework. One problem for autonomous vehicles operating on toll roads must be able to do a satisfactory tracking path when avoiding obstacles so that accidents do not occur. This paper will discuss designing tracking path controllers using a predictive controller (MPC) model based on scenario avoidance obstacle on the highway with several variations in speed. The trajectory has been predetermined and the controller must be able to autonomously avoid static obstacles on the road and can track the desired trajectory by controlling the front steering angle of the vehicle. This approach discusses solving a single nonlinear MPC problem for following trajectories and avoiding static obstacle. The vehicle model was developed based on 3 DOF non-linear vehicle model. This controller model was developed based on X, Y global position and yaw rate to get input in the form of steering to the vehicle dynamic system. For path tracking strategy, comparisons with the Stanley controller are done to analyse MPC reliability as non-linear controller in low and middle speed scenario. Simulation results show that the MPC controller has the advantage of a tracking path that is good at mid and high speeds.

Keywords: Predictive Control
Abstract: Being able to tackle constraints, the adaptive model predictive control (AMPC) is one of the most frequently used methodologies in coping with model uncertainties. Fundamentally, the core procedure of AMPC is dependent on the model identification to increase the suboptimality of MPC. However, only the type of data which admits the specified requirements is accessible to the identification, which implies the failure of adaptation method to some extent. Aimed at this proposal, this paper proposes a new control technique which adds data-driven representation skills into the robust model predictive controller(RMPC). The advantages over other controllers were explicitly reflected in numerical simulation. Feasibility of the algorithm is able to be proven and the stability of the controlled system is verified.

Keywords: Predictive Control, LMIs, Robust Control
Abstract: The problem of dynamic output feedback robust model predictive control (MPC) for linear parameter varying (LPV) system with bounded disturbance is addressed. In the previous approaches, an inner iteration loop handles the mutual inverse Lyapunov matrices by applying the cone complementary approach, and an outer iteration loop minimizes the performance cost by iterating the inner loop. By utilizing a linearization method to handle the mutual inverse Lyapunov matrices, the new approach in this paper utilizes a single iteration loop to replace the double iteration loops in the previous approach, so that the computational burden can be greatly reduced. The recursive feasibility and closed-loop stability are guaranteed. A numerical example is given to illustrate the effectiveness of the proposed approach.

Keywords: Predictive Control, Power Systems and Power Electronics, Optimal Control and Optimization
Abstract: The paper considers model predictive control of a voltage source converter with inductive-capacitive (LC) filter. The model of the converter describes the nonlinear effect of the switching on the converter state and the MPC problem is therefore nonlinear and non-convex. An in-depth analysis reveals a convex structure of the converter model, and a nonlinear variable transformation is introduced which allows to equivalently state the MPC problem as a convex, quadratically constrained quadratic problem (QCQP). Thus, a problem which has previously been formulated as a non-convex problem and solved approximately, can be solved exactly without approximation error. The QCQP is solved using a novel first-order method suitable for real time implementation.

Keywords: Predictive Control, Process and Chemical Systems, Linear Systems
Abstract: This paper proposes a dynamic matrix control(DMC) algorithm that uses the proper future target information to improve the tracking performance. A default choice of feed-forward implies no anticipation and could lead to degeneration of performance. By first illustrating the underlying feed-forward structure in the original DMC scheme without constraints, this paper gives a systematic method for selecting a good choice for advanced knowledge and proposes a feedforward DMC algorithm with constraint handling. A typical case study demonstrates the efficacy of the proposal.

Keywords: AI and Expert Systems, Identification and Estimation, Power Systems and Power Electronics
Abstract: Balancing the power supply and demand is one of the most fundamental and important problems for the operation and control of any electric power grid. There are multiple ways to guarantee the supply-demand balance, but in this research we focus on one specific method to facilitate it namely the prediction of electricity consumption, which is widely used by utility companies or system operators. It is known that this prediction is challenging because of many reasons, for example, inexact weather forecasts, uncertain consumers' behaviors, etc. Hence, analytical and linear models of electricity consumption might not be able to deal with such issues well. This paper therefore presents a machine learning-based approach to predict electricity consumption, in which an improved radial basis function neural network (iRBF--NN) is proposed, whose inputs are time sampling points, temperature, and humidity associated with the consumption. The parameters of this iRBF--NN are sought by solving an optimization problem where four types of cost functions are used and compared on their performances and computational costs. Afterward, the derived model is employed to predict the future electricity consumption based on the hourly forecasts of temperature and humidity. Finally, simulation results for realistic data in Tokyo are presented to illustrate the efficiency of the proposed approach.

Keywords: Flexible Structures, Identification and Estimation, Control Applications
Abstract: Piezoelectric shunt damping is a technique for vibration suppression by connecting an external circuit called the shunt circuit to a piezoelectric element attached to a mechanical structure. Many previous studies consider only a single mode for designing shunt circuits. However, the vibration of actual structures typically includes multiple vibration modes. It is consequently necessary to consider multiple modes toward designing a high-performance vibration control system. This paper proposes a method for estimating multiple-mode parameters of a piezoelectric structure, which is composed of a piezoelectric element and a flexible structure. The proposed multiple-mode parameter estimation method is derived by expanding a previously proposed method for single-mode parameter estimation. Moreover, the effectiveness of the proposed estimation method is verified by experiments.

Keywords: Identification and Estimation, LMIs, Filtering
Abstract: In this paper, a sufficient condition for identifying the Kalman gain and the covariance matrix of the innovations process is derived. Under the condition, the innovations model can uniquely be estimated in a generic sense by solving a semi-definite programming problem proposed by the author in the past. A numerical simulation illustrates the consistency of the proposed estimate.

Keywords: Identification and Estimation, MEMs and Nano Systems, Sensors and Senor Fusion
Abstract: Two inertial measurement units and a permanent magnet are attached on two feet to estimate foot motion for gait analysis. Gait events are detected using a simple peak detection method with accelerometer data. To correct foot position error, the zero-velocity intervals, z-axis position, and magnetic measurement updates are used. The proposed solution gives accurate trajectories and also the relative position of two foot in straight walking experiments, which is simple, low-cost and promising for gait analysis applications.

Keywords: Identification and Estimation, Optimal Control and Optimization, Process and Chemical Systems
Abstract: A new input design method for identification of multiple-input multiple-output (MIMO) systems is introduced. The method is completely data based as opposed to previous model-based methods. The data are obtained from one or more experiments with the system to be identified. These experiments do not require any MIMO input design. The design objective is to generate maximally informative data when a new experiment based on MIMO input design is done. The data are considered to be maximally informative when the outputs have maximal variance, subject to some constraints, and no correlation. Since the input design, with given type of perturbation signal, is not unique, it is possible to optimize some additional property, such as minimization of input or output peak value. The various design options are illustrated by application to a system with three inputs and three outputs.

Keywords: Identification and Estimation, Pattern Recognition
Abstract: Aiming to achieve a safe and efficient drilling, this paper is concerned with identification of formation lithology, which provides critical information for drilling control. Notice that it is hard to make accurate geological prediction using conventional identification approaches, due to the problem characteristics of imbalanced, multi-classification and low value density of logging data, a novel lithology identification method is developed based on the reduction error correcting output code kernel fisher discriminant analysis algorithm(RECOC-KFDA) in a online manner. It consider design optimal error correcting output code(ECOC) matrix based on a reduction algorithm. Meanwhile, it proposed a online method to reduce the computation complexity required for updating the kernel fisher discriminant analysis(KFDA) classifiers rather recalibrating them. Proposed method has been validated using the UCI machine learning database and applied to lithologic identification in drilling site. Simulations and comparisons demonstrate that our method is superior to the existing ones for both offline training and online prediction model.