Vol. 21, No. 9, September 2023
Jung Min Pak and Choon Ki Ahn*International Journal of Control, Automation, and Systems 2023; 21(9): 2771-2781
Abstract : Unmanned vehicles represent a research hotspot in the fields of control and robotics. The realization of autonomous driving of unmanned vehicles requires various technologies, such as localization, mapping, path planning, and obstacle avoidance. Among these technologies, localization is a fundamental component, which can be accomplished through various methods. In this work, we focus on localization based on state estimation, as these algorithms are predominantly applied to unmanned vehicles. This paper provides a comprehensive review of state estimation algorithms commonly used for the localization of unmanned vehicles, from the perspective of control and robotic engineers. First, we provide an overview of localization schemes based on state estimation algorithms. Subsequently, we can categorize the research subjects into eight classes and clarify the principles and features of each type of state estimation algorithm. Furthermore, we examine the recent research trends associated with these algorithms.
Linhe Ge, Yang Zhao*, Shouren Zhong, Zitong Shan, Fangwu Ma, Zhiwu Han, and Konghui GuoInternational Journal of Control, Automation, and Systems 2023; 21(9): 2782-2796
Abstract : The steady-state error problem of autonomous vehicle MPC-based motion control has not been effectively solved for a long time. This problem is more serious for lateral and longitudinal coupling control problems of vehicles with over-actuated configurations. Based on our newly designed general offset-free MPC (OF-MPC) solver and the TMeasy tire model, a steady-state error free control strategy for simultaneous stability and path following control of four-wheel steering and four-wheel drive vehicles is proposed. OF-MPC uses the disturbances term to describe the model mismatch and external disturbances, then uses the Kalman filter to observe the disturbances, and finally considers the disturbances in the optimization stage to realize the control without steady-state error. Realtime simulation results show that OF-MPC can solve model mismatch and external disturbances problems, and the steady-state error free control is realized. The simulation results of the double lane change maneuver show that the OF-MPC dynamic control performance is also better than the traditional MPC (TRA-MPC), which is more obvious when the vehicle is at the stability boundary and under various constant or time-varying disturbances. Regardless of the dimensions and complex constraints of this problem, real-time performance is still guaranteed, thanks to the proposed OF-MPC. When the horizon length is 100, the average time consumption is only about 15 milliseconds.
Chao Cheng, Xiuyuan Sun, Junjie Shao, Hongtian Chen*, and Chao ShangInternational Journal of Control, Automation, and Systems 2023; 21(9): 2797-2809
Abstract : Traction systems in high-speed trains exhibit significant dynamic characteristics, which mainly arise from operation-point changes. Most existing fault detection methods provide static data models for global structures, especially for traditional multivariate statistical analysis methods constrained by constant operating points. The symptoms of incipient faults are slight and easily hidden. Despite the moderate effect of incipient faults, they will compromise the overall performance and remaining life of traction systems in the long run. Therefore, a just-in-time slow feature analysis method is proposed in this study. The salient advantages of the proposed method are: 1) It can be applied to dynamic non-linear systems; 2) It can detect incipient faults subject to environments containing noise and unknown disturbances; 3) It mitigates false alarms caused by parameter mutation during mode-switching. A series of experiments are carried out on a traction system platform to verify the effectiveness and superiority of the proposed method.
Qing-Yuan Xu, Yun-Shan Wei, Jing Cheng, and Kai Wan*International Journal of Control, Automation, and Systems 2023; 21(9): 2810-2820
Abstract : In this paper, an adaptive iterative learning control (ILC) design method is proposed for a class of nonlinear discrete-time systems with nonaffine structure, randomly varying trail length, and uncertain control direction. In order to achieve repetitive tracking control of the nonaffine structure systems with uncertain control direction, randomly varying trail length, and other uncertainties, we apply a high-order neural network to approximate the expected system input. Then, a novel adaptation law is designed for the neural network weight vector. The main feature of the method proposed in this paper is that the weight vector norm instead of the weight vector itself is updated iteratively to realize the successive approximation of the expected system input, the custom-designed identification mechanism is not necessary to deal with the uncertain control direction, and the analysis of randomly varying trail lengths problem is strictly established. The convergence of the proposed adaptive ILC is set up by a composite energy function. The effectiveness of the proposed adaptive ILC design is validated by two simulation examples.
Karthi Ramachandran* and Jyh-Ching JuangInternational Journal of Control, Automation, and Systems 2023; 21(9): 2821-2834
Abstract : The consensus problem for nonlinear multi-agent systems communicating on a connected undirected topology is addressed in this paper. The system nonlinearity of each agent accepts the one-sided Lipschitz and the quadratic-inner bounded properties. Furthermore, actuators of the agents are subject to a loss in their efficiency and are also assumed to have nonlinearity at the input. In addition, the agents are influenced by parametric uncertainties both at the system and input level, also bounded external disturbances affect the system states. To attain a consensus under these constraints, an observer-based state feedback protocol is developed. Subsequently, a robust finite-time boundedness study is performed by constructing an appropriate Lyapunov function from a closed loop observererror dynamics. Following this, the controller and observer gains are designed from the resulting linear matrix inequalities. This guarantees a reliable consensus among the agents in a finite time against actuator faults and uncertainties. The protocol’s effectiveness is shown by a suitable example.
Meng-Yi Jiang, Yong-Hui Yang, Li-Bing Wu, and Qi Li*International Journal of Control, Automation, and Systems 2023; 21(9): 2835-2843
Abstract : In this paper, we consider a containment control problem for a class of uncertain multi-agent systems (MASs). The systems contain unknown parameters and virtual control gain functions. By introducing lower bounds of virtual control gain functions into the Lyapunov functions, a novel controller design scheme is proposed based on an adaptive control design approach and bound estimation method. The designed controller is simpler in comparison with other controllers. The simulation results show that three followers converge into the convex hull rapidly following the sinusoidal leaders, and the effectiveness of the designed controller is verified.
Wei Gao, Yan Ren*, Liyun Zhao, Kai Weng, and Huimin WangInternational Journal of Control, Automation, and Systems 2023; 21(9): 2844-2855
Abstract : This paper studies the leader-following consensus of second-order multi-agent systems with input delays. Firstly, a feedback-tracking control protocol with the leader’s delayed state derivative is proposed to guarantee the leader-following consensus. Secondly, considering the same input delay of the second-order multi-agent system, the explicit formula of the upper bound of delay for the asymptotic stability of the second-order multi-agent system is obtained by using the frequency domain analysis method. Compared with the latest existing controllers, the controller designed in this paper improves the convergence speed and tracking accuracy. Thirdly, a variety of diverse input delays are further considered, the feedback tracking controller is designed to improve the convergence speed and tracking accuracy, and sufficient conditions of leader-following consensus are given by using the generalized Nyquist stability criterion. Finally, simulation examples are given to show the effectiveness of our control protocol.
Runyu Zhu, Lei Liu*, and Lichao FengInternational Journal of Control, Automation, and Systems 2023; 21(9): 2856-2866
Abstract : This paper investigates the mean square average consensus for a class of stochastic multi-agent systems via an intermittent event-triggered strategy. First, a sufficient criterion for mean square average consensus via an intermittent event-triggered strategy is established. Meanwhile, Zeno behavior is excluded. Second, these results are extended to an intermittent self-triggered strategy. Finally, some simulation results verify the validity of the proposed control schemes.
Wenbin Yu, Guolai Yang*, Liqun Wang, Lei Li, and Hongyi ZhangInternational Journal of Control, Automation, and Systems 2023; 21(9): 2867-2878
Abstract : Traditional counter-recoil machines always have problems of difficulty in adjusting the movement process flexibly, maintenance difficulties, and so on. To end these, this paper proposes a new electromagnetic counterrecoil scheme using cylindrical linear motors. Firstly, the mathematical expression of counter-recoil movement under the linear motor is formulated, and the ideal movement trajectory is designed using the piecewise polynomial of velocity based on acceleration. To obtain a better performance, of the motor controller, a composed approach of an adaptive sliding mode control based on barrier function (BFASMC) and the finite-time disturbance observer (FTDO) is introduced into the modeling and computation. The stability of the controller is proved by establishing the Lyapunov function. The new adaptive laws based on the barrier function effectively make up for the shortcomings of the exponential function and improves control chattering. At last, the new scheme is simulated. The results show that it has a strong robustness and anti-interference ability.
Bingxin Li, Xuefeng Zhang, Xiangfei Zhao, Yaowei Liu, and Xin Zhao*International Journal of Control, Automation, and Systems 2023; 21(9): 2879-2890
Abstract : In the paper, observer-based sliding mode control (SMC) for fractional order singular fuzzy (FOSF) systems with order 0 < α < 1 is studied. The non-fragile FOSF observer is designed to reconstruct the unmeasured states, and a novel fractional order integral sliding function is formulated. Then, the admissibility condition of the FOSF error system is derived, based on the linear matrix inequality (LMI) approach. By using the singular value decomposition approach, the strict LMI-based admissibility condition is improved. Based on the fractional order Lyapunov function and sliding surface, the fractional order SMC is constructed to ensure the reachability of the sliding surface. Two examples are given to illustrate the effectiveness of the methods proposed in the paper.
Juan Carlos González Gómez, Rogério Rodrigues dos Santos, Kevin Herman Muraro Gularte*, José Alfredo Ruiz Vargas, and José Antonio Ruz HernándezInternational Journal of Control, Automation, and Systems 2023; 21(9): 2891-2903
Abstract : This paper presents the synchronization of a class of hyperchaotic systems using a robust underactuated approach. The proposed scheme guarantees the convergence in finite time of the slave system trajectories to the master system based on Lyapunov theory. The main novelty of the method is its simplicity resulting from the underactuated strategy and its robustness due to the presence of disturbances in the stability analysis. Simulations are presented to show the performance of the proposed method and its advantages compared with another recent study in the literature. In addition, a secure communication example is considered to illustrate the simple application of the synchronizer.
Jingmei Liu, Wei Wang*, Juanjuan Xu, and Huanshui ZhangInternational Journal of Control, Automation, and Systems 2023; 21(9): 2904-2915
Abstract : In this paper, we study the open-loop Stackelberg strategy of the stochastic Stackelberg game with time delay. The main contribution is to give the explicit Stackelberg strategy in terms of Riccati equations. The key to solving the problem is the explicit solvability of the forward and backward stochastic difference equations (FBSDEs). Moreover, the optimal costs are indicated by using the initial value of the state.
Shuang Liu, Chunmei Duan*, and Wuneng ZhouInternational Journal of Control, Automation, and Systems 2023; 21(9): 2916-2926
Abstract : This paper deals with the stochastic stability problem of the closed-loop system under deception attacks based on an adaptive event-triggering scheme (AETS) with saturation constraint. Some novel stability criteria related to networked control systems under deception attacks are devised by taking the fixed threshold which is difficult to adapt to changeable systems into account. An adaptive event-triggering scheme with saturation constraint involving a threshold variable with system states is proposed to reduce network load, and the desired controller gain matrix is obtained by employing the linear matrix inequalities (LMIs) technique. Moreover, the LyapunovKrasovskii method is used to obtain sufficient conditions for ensuring the stability of the system. In the end, the simulation results are shown to indicate the validity of the proposed method.
Chao Ge*, Chenlei Chang, Yajuan Liu, and Changchun HuaInternational Journal of Control, Automation, and Systems 2023; 21(9): 2927-2937
Abstract : The exponential synchronization for a class of neural networks (NNs) based on dynamic event-triggered mechanism (DETM) is researched in this article. Firstly, an unbounded distributed delay is introduced into the NNs. Next, based on the characteristics of the sawtooth structure, an improved bilateral Lyapunov-Krasovskii functional (LKF) is constructed, which involves more information. By using improved integral inequality, some sufficient conditions are achieved for the exponential stability of the synchronization error system. Due to the influence of external factors or internal components, the controller parameter is uncertain. Then, a non-fragile controller is designed based on the decoupling technique. Moreover, a co-design scheme of controller gain and event-triggered matrix is obtained based on the linear matrix inequality technique. Finally, two examples are used to illustrate the validity and feasibility of the presented method.
Bing Chen, Yangzhou Chen*, and Jingyuan ZhanInternational Journal of Control, Automation, and Systems 2023; 21(9): 2938-2949
Abstract : In this paper, the periodic event-triggered consensus problem for linear multiagent systems (MASs) with random packet dropouts in a generic directed communication topology is addressed. Both leaderless and leader-following mean square consensus problems, where the random packet dropouts are described by a Bernoullidistributed sequence, are considered. To solve these problems, a linear transformation matrix is constructed from a given directed spanning tree of the communication topology of the MASs, which equivalently transforms the mean square consensus problem into the corresponding mean square asymptotic stability problem of the derived reduced-order systems with constraints. Then, mean square consensus criteria are derived using the Lyapunov stability theory, which is expressed in terms of linear matrix inequalities (LMIs) concerning the sampling period, the packet dropout probability, and the control gain matrix. To reduce the information updating number, an event-triggered mechanism is designed with fewer unknown parameters. Finally, numerical simulations are given to verify the effectiveness of the theoretical results.
Peijun Ju*, Tongxing Li, Jing Lei, and Zhongjin GuoInternational Journal of Control, Automation, and Systems 2023; 21(9): 2950-2956
Abstract : This paper investigates the stabilization problem of linear delay systems with two unstable poles, by using a modified proportional-integral (PI) controller. A necessary and sufficient condition for stabilizability is obtained, and the relationship between the system parameters and the time delay size is established. Furthermore, a tighter upper bound of the delay margin for the linear system with two unstable poles is provided. Finally, the effectiveness of the results is demonstrated by a simulation study.
Gualberto Solís-Perales*, Jairo Sánchez-Estrada, and Ricardo FematInternational Journal of Control, Automation, and Systems 2023; 21(9): 2957-2968
Abstract : This contribution presents a gain adaptation, which allows us to tune a robust asymptotic feedback linearization (RAFL). The gain adaptation allows the RAFL to attenuate the measurement noise sensitivity. The RAFL is considered here because it ensures tracking without prior information about the system’s nonlinearities and parameter bounds. Also, the RAFL only has the system output available for feedback. In this work, the robust tracking problem is faced considering: modeling errors, parametric variations, external perturbations, and noisy output measurement. On one side, the RAFL control faces modeling errors, parametric variations, and external perturbations through an observer that estimates uncertainties using an extra state, which lumps all the unknown nonlinearities and uncertainties. On the other hand, the proposed adaptive gain function allows the observer’s high gain to vary to have a fast observer’s convergence while simultaneously avoiding amplifying the measurement noise in the steadystate. The adaptive gain function provides the RAFL control robustness against noisy measurement. Thereby, the RAFL control with adaptive gain function becomes a robust feedback linearizing against to measurement noise. Finally, the RAFL controller with the adaptive gain function is illustrated by a numerical simulation of a tracking problem for a DC-motor and a chemical oxygen demand regulation in an anaerobic digestion process.
Chunmei Zhang*, Dan Xia, Huiling Chen, and Guiling ChenInternational Journal of Control, Automation, and Systems 2023; 21(9): 2969-2979
Abstract : This paper is mainly concerned with partial topology identification of stochastic multi-group models with multiple dispersals (SMGMMD) by adaptive pinning control. By using a graph-theoretic approach and adaptive synchronization techniques, some sufficient criteria for partial topology identification of SMGMMD with time delay are obtained. Meanwhile, the partial topological structures of SMGMMD without time delay and the whole topological structures of SMGMMD can also be identified successfully. Finally, coupled Lorenz systems with time delay are identified to demonstrate the feasibility and effectiveness of theoretical results.
Yuhai Yang, Chongquan Zhong, Xiaodong Liu, and Wei Lu*International Journal of Control, Automation, and Systems 2023; 21(9): 2980-2994
Abstract : Cyber-physical systems (CPS) are rapidly developing in smart factories. However, CPS for smart factories is facing great challenges in the integration of heterogeneous devices (sensors and control devices) and analysis methods like stability and expandability of systems. In this study, a comprehensive solution is provided to integrate heterogeneous devices and to analyze CPS dynamic behaviors with the aid of Petri net. Specifically, in the physical layer, a kind of controller PAG200 is used as an edge control gateway, to integrate a multitude of sensing and control devices into one system. The integrated system can assist managers to better deal with the manufacturing data captured on-site; In the cyber layer, a cyber-physical system analysis method based on Petri net is proposed. The method combines Petri net principle with cyber-physical system technology, and the purpose is to provide a graphical modeling and analysis method for information perception, device management and data processing. System extensibility is measured by coupling intensity. The necessity and priority of the elastic expansion of the system are established. The system stability and performance are analyzed from the stability probability and its related parameters. There have been enough successes to demonstrate that PAG200 can undertake the task of internet integration as an edge gateway to eliminate information gaps. Correspondingly, the extensibility of the model and the feasibility of the method are verified.
Seungho Han, Minseong Choi, Minsu Cho, Ji-il Park*, and Kyung-Soo Kim*International Journal of Control, Automation, and Systems 2023; 21(9): 2995-3005
Abstract : In this letter, a control strategy comprising velocity and yaw rate controllers is proposed for a real fourwheel vehicle in a leader-follower formation when the leader vehicle drives at high speed, i.e., 100 km/h. Since vehicle stability plays an increasingly important role as speed increases, vehicle dynamics must be considered in vehicle formation control. Therefore, to increase the accuracy of the formation geometric model, bicycle modelbased leader-follower formation models are suggested, which are denoted as the follower (F) bicycle model and the leader-follower (LF) bicycle model. Then, the velocity and yaw rate control of the follower vehicle is designed. In addition, vehicle longitudinal and wheel dynamic models are considered in the velocity control to generate the wheel torque. Finally, the control gains are determined under conditions that satisfy the Routh-Hurwitz stability criterion, which guarantees the stability of the vehicle simplified as a first-order lag model. The performance of the proposed leader-follower bicycle model and controllers are strictly demonstrated by implementing vehicle dynamics simulations in cases when vehicles in a formation drive at high speeds. The simulation results confirm that the suggested formation control strategy can be applied to real four-wheel vehicles under high-speed conditions on various types of paths, in comparison with the unicycle model-based formation shape model.
Bao-Lin Ye*, Shaofeng Niu, Lingxi Li, and Weimin WuInternational Journal of Control, Automation, and Systems 2023; 21(9): 3006-3021
Abstract : Efficient trajectory tracking approaches can enable autonomous vehicles not only to get a smooth trajectory but to achieve a lower energy dissipation. Since vehicle model plays an important role in trajectory tracking, this paper investigates and compares the performance of two classical vehicle models for trajectory tracking of autonomous vehicles using model predictive control (MPC). Firstly, a two-degree-of-freedom kinematic model and a three-degree-of-freedom yaw dynamic model are established for autonomous vehicles. Meanwhile, in order to carry out tracking control more effectively and smoothly, the tire slip angle has been taken into account by the dynamic model. Then, we design two MPC controllers for trajectory tracking, which are based on the kinematic model and the dynamic model, respectively. The performances of two MPC controllers are evaluated and compared on the Carsim/Matlab joint simulation platform. Experimental results demonstrated that, under low-speed working conditions, both two MPC controllers can follow the reference trajectory with high accuracy and stability. However, under high-speed working conditions, the tracking error of the kinematic model is too large to be used in the real trajectory tracking problem. On the contrary, the controller based on the dynamic model still performs a good tracking effect. In addition, this study offers guidance on how to select a suitable vehicle model for autonomous vehicles under different speed working conditions.
Zhenyi Zhang, Jianfei Chen, Zhibin Mo, Yutao Chen, and Jie Huang*International Journal of Control, Automation, and Systems 2023; 21(9): 3022-3035
Abstract : In this work, a behavior-based adaptive dynamic programming (BADP) method is proposed for the coordination control of unmanned ground vehicle-manipulator systems (UGVMs). Through a null-space-based behavioral control (NSBC) framework, the multi-objective coordination control is transformed into a single-objective tracking control at the mission layer. Since cost functions and control constraints are simplified at the control layer, the complexity of controller design is reduced. Then, an identifier-actor-critic reinforcement learning algorithm framework is introduced to learn the optimal control policy by balancing the control performance and consumption. Simulation results show that control costs are reduced by around 13.5% per sampling period compared to existing multiple objective control methods. Finally, the BADP method is experimentally validated using four real UGVMs.
Zengpeng Lu, Yuanchun Li, and Yan Li*International Journal of Control, Automation, and Systems 2023; 21(9): 3036-3047
Abstract : This paper presents a novel decentralized fixed-time tracking control approach, which realizes the advantages of modular robot manipulators (MRMs) with fixed-time convergence, strong robustness, and high tracking performance. First, to estimate the total uncertainty of MRMs, the fixed-time observer based on the extended state is developed. Then, combined with the disturbance observer, a novel decentralized control method based on a fixedtime control strategy was devised to accomplish global fixed-time convergence of MRMs. And, stability analysis based on Lyapunov is utilized to obtain the fixed-time stability as well as convergence time of MRMs. Finally, numerical analysis and experiment respectively verify the excellent tracking ability of the presented decentralized fixed-time tracking control.
Sanggyu Kim and Hong Seong Park*International Journal of Control, Automation, and Systems 2023; 21(9): 3048-3056
Abstract : This paper proposes, implements, and verifies a multicore real-time scheduler (MCRT scheduler) for periodic and sporadic threads and processes, and non-real-time processes where periodic and sporadic (or eventdriven) processes are processed according to real-time characteristics such as limited periods and deadlines. Using the Xenomai and Linux operating systems, the proposed MCRT scheduler was implemented and verified through various test cases designed for multicore operations. The proposed MCRT scheduler generates scheduling tables for periodic and sporadic threads and processes, based on which they are executed during the basic period. The MCRT scheduler was verified using several examples.
Jigang Kim, Dohyun Jang, and H. Jin Kim*International Journal of Control, Automation, and Systems 2023; 21(9): 3057-3067
Abstract : Deploying multiple robots for target search and tracking has many practical applications, yet the challenge of planning over unknown or partially known targets remains difficult to address. With recent advances in deep learning, intelligent control techniques such as reinforcement learning have enabled agents to learn autonomously from environment interactions with little to no prior knowledge. Such methods can address the explorationexploitation tradeoff of planning over unknown targets in a data-driven manner, streamlining the decision-making pipeline with end-to-end training. In this paper, we propose a multi-agent reinforcement learning technique (MARL) with target map building based on distributed Gaussian process (GP). We leverage the distributed GP to encode belief over the target locations in a scalable manner and incorporate it into centralized training with decentralized execution MARL framework to efficiently plan over unknown targets. We evaluate the performance and transferability of the trained policy in simulation and demonstrate the method on a swarm of micro unmanned aerial vehicles with hardware experiments.
Xuejie Que, Zhenlei Wang*, and Xin WangInternational Journal of Control, Automation, and Systems 2023; 21(9): 3068-3079
Abstract : Two-time-scale (TTS) systems were proposed to describe accurately complex systems that include multiple variables running on two-time scales. Different response speeds of variables and incomplete model information affect the tracking performance of TTS systems. For tracking control of an unknown model, the practicability of reinforcement learning (RL) has been subject to criticism, as the method requires a stable initial policy. Based on singular perturbation theory (SPT), a composite sub-optimal tracking policy is investigated combining model information with measured data. Besides, a selection criterion for the initial stabilizing policy is presented by considering the policy as an input constraint. The proposed method integrating RL technique with convex optimization improves the tracking performance and practicability effectively. Finally, an emulation experiment in F-8 aircraft is given to demonstrate the validity of the developed method.
Jakub Bernat, Jakub Kołota, and Paulina Superczyńska*International Journal of Control, Automation, and Systems 2023; 21(9): 3080-3090
Abstract : System identification is a field of control engineering that deals with the preparation of a mathematical description by recognizing the static and dynamic properties of automation systems. It becomes particularly important in the black-box approach, in which the modeling technique constructs a model using only the output data obtained from the system based on the known input signal. One of the most complete and powerful identification methodologies available today for the identification of nonlinear systems is the NARMAX approach. This paper presents and compares three methodologies used to approximate the unknown structure of a dielectric electroactive polymer actuator by applying one-step and multi-step prediction. The motivation of this study was to check the possibilities of the recent identification techniques on the object with complicated dynamics like DEAP actuators.
Hang Li* and Wusheng ChouInternational Journal of Control, Automation, and Systems 2023; 21(9): 3091-3104
Abstract : This paper proposes an adaptive fuzzy neural network backstepping control scheme for bilateral teleoperation systems with asymmetric time delays induced by the communication links and various uncertainties. Specifically, the control scheme adopts a kind of asymmetric structure to design respectively the fuzzy-neuralnetwork adaptive controllers of the master and slave sides. For reducing the convergence time of trajectory error, instead of conventional tracking error signals, the velocity-based parameters is applied in the master side. And the backstepping controller in the slave side effectively avoids the acquisition of acceleration signal for engineering application. Meanwhile, the joint frictions of manipulators and the additive uncertainties of environmental parameters are substituted by the non-power approximate signals of the fuzzy logic algorithms, which copes with the passivity problem of the time-delayed channel. Under ignoring the upper bound information of the external disturbances, the asymptotically stability and trajectory tracking performance of the closed-loop system is analysed by the Lyapunov function. Finally, the experimental tests demonstrate that the closed-loop teleoperation system is stable under asymmetric time delays and possess a better joint position tracking performance than other neural network control schemes.
Hyun-Soo Kim and Dong-Joong Kang*International Journal of Control, Automation, and Systems 2023; 21(9): 3105-3115
Abstract : Using deep learning (DL) technology, neural networks have achieved great success in various fields of computer vision. Among them, anomaly detection is a promising application of image defect analysis. The purpose of the detector is to find the out-of-distribution when predicting the probability of a DL network for abnormal samples, after some normal sample images are given for training. Geometric transformation (GT) based anomaly detection is one of the recent best methods for classifying abnormal samples among many normal ones. However, the GT method training process is unstable and too inaccurate to be used in industrial applications. The goal of this study is to suggest a method to improve the performance of a GT-based anomaly detector (GTnet). Using observations of GTnet behavior and its training properties, we propose the addition of three techniques that can improve anomaly detection performance for defect inspection in a factory production process. Specifically, k-Winners-Take-All (kWTA) was applied to the GTnet base model to resist data corruption such as dust on the sample, the temperature scaling method was added to consider correlations between GT classes with similar appearance, and loss redefinition was applied to improve the efficiency of optimal training. Accuracy was improved from 98.56% to 99.86% in the inspection of vehicle part assembly defects, which requires extremely high accuracy. Experimental evaluations were conducted to verify the performance improvement of the GT anomaly detector.
Qunpo Liu*, Ming Ye, Zhonghua Wu, Xuhui Bu, and Naohiko HanajimaInternational Journal of Control, Automation, and Systems 2023; 21(9): 3116-3126
Abstract : This paper focuses on the problem of finite-time trajectory tracking control of long-stroke hybrid robots with uncertain system parameters and external disturbances. A system filtering prescribed performance backstepping control based on adaptive fuzzy compensation is proposed. For the unknown terms corresponding to the parameter uncertainties and unknown disturbances existing in the system, a set of auxiliary filter variables is introduced in the adaptive fuzzy approximator and an estimation error function is constructed. An adaptive law based on the estimated error function is proposed to adjust the adaptive weight parameters of the fuzzy system. An adaptive fuzzy approximation algorithm based on the estimation error is finally constructed to compensate for the performance loss caused by the unknown term. For the system state convergence speed problem, a performance function that can transform the system tracking error into an unconstrained error is presented, and the unconstrained error is used as the backstepping control variables. To avoid the differential explosion problem, a new set of inverse control variables is defined by combining the filter variables obtained based on the low-pass filter and the joint velocity. Based on the above variables, a system filtering-based prescribed performance backstepping control strategy is proposed. Finally, the semi-global practical finite-time stability of the closed-loop system is proved by the Lyapunov function. Experiments on the MATLAB platform verify the effectiveness of the proposed method.
Yi-Qing Xue and Ping Zhao*International Journal of Control, Automation and Systems 2023; 21(7): 2099-2111
Hyo-Sung AhnInternational Journal of Control, Automation, and Systems 2023; 21(8): 2429-2429