Article
Computer Science, Information Systems
Chao Ma, Hang Fu, Wei Wu
Summary: This paper addresses the fault detection problem of delayed semi-Markov jump systems with disturbances, considering the asynchronous phenomenon between modes of linear and nonlinear dynamics. An efficient solution for fault detection is proposed based on an asynchronous mode-dependent fault filter with conditional probability. Sufficient criteria are established using appropriate Lyapunov-Krasovskii functions to ensure H-infinity performance for the filter error and residual signal. Moreover, the filter gains are computed through convex optimization. The applicability of the proposed design is verified through an illustrative example.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Guangtao Ran, Jian Liu, Chuanjiang Li, Hak-Keung Lam, Dongyu Li, Hongtian Chen
Summary: This article addresses the event-triggered asynchronous fault detection problem of fuzzy-model-based nonlinear Markov jump systems with partially unknown transition probabilities. An adaptive event-triggered scheme and a hidden Markov model are introduced to propose a new fault detection method, which is verified through numerical simulation.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Mathematics, Applied
ZeLiang Xia, Shuping He
Summary: This paper investigates the H 00 fault-tolerant control problem for a class of conic-type nonlinear Markov jump systems with sensor and actuator faults as well as unknown disturbances. The hidden Markov model is introduced to handle the asynchronous issue in control systems. By utilizing suitable Lyapunov-Krasovskii function and linear matrix inequalities techniques, a new condition of the state feedback H 00 fault-tolerant controller with actuator faults and sensor faults is presented. The proposed control strategy ensures both the finite-time boundness of the closed loop system and the desired H 00 performance.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Engineering, Multidisciplinary
Mengmeng Liu, Jinyong Yu, Juan J. Rodriguez-Andina
Summary: In this paper, the event-triggered asynchronous fault detection problem is studied for nonlinear Markov jump systems using zonotopic residual evaluation. An adaptive event-triggered scheme is used to reduce redundant data transmission and save communication resources and network bandwidth. A hidden Markov model with hybrid probabilities is introduced to characterize asynchronization between the system components and address transition and mode detection simultaneously. A co-design criterion is derived to design an optimal asynchronous reduced-order fault detection filter and event-triggered scheme considering mode information. Furthermore, a novel zonotopic residual evaluation strategy with dynamic thresholds is developed. The effectiveness of the proposed approach is illustrated using the application of automotive electronic throttle body.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Mechanical
Qi-Dong Liu, Yue Long, Ju H. Park, Tieshan Li
Summary: This paper addresses a neural network-based event-triggered fault detection scheme for a class of nonlinear Markov jump system in the finite-frequency domain. By constructing an approximation model and applying an event-triggered transmission mechanism, fault sensitivity and disturbance attenuation for the augment systems are guaranteed. Synthesizing desired filters through derived linear solvable conditions and novel decoupling techniques, the efficiency of the proposed algorithm is demonstrated through a computational example.
NONLINEAR DYNAMICS
(2021)
Article
Automation & Control Systems
Linchuang Zhang, Yonghui Sun, Hongyi Li, Hongjing Liang, Jianxi Wang
Summary: This paper studies the event-triggered fault detection problem for nonlinear semi-Markov jump systems constructed by Takagi-Sugeno fuzzy approach. A novel double asynchronous fault detection filter is designed to address the double asynchronous phenomenon in actual network environment. The mode asynchronous phenomenon is described using a hidden semi-Markov model. Based on Lyapunov stability theory, sufficient conditions are developed to ensure system stability and performance. An illustrative tunnel diode circuit example is provided to demonstrate the effectiveness of the proposed approach.
Article
Automation & Control Systems
Peng Cheng, Hai Wang, Vladimir Stojanovic, Shuping He, Kaibo Shi, Xiaoli Luan, Fei Liu, Changyin Sun
Summary: This article discusses the design of asynchronous fault detection (FD) observer for 2-D Markov jump systems expressed by a Roesser model. By employing a hidden Markov model (HMM) and a multiobjective solution, sufficient conditions for the existence of asynchronous FD are obtained using linear matrix inequality technology. An asynchronous FD algorithm is generated to achieve optimal performance indices.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Computer Science, Information Systems
Xiang Zhang, Shuping He, Vladimir Stojanovic, Xiaoli Luan, Fei Liu
Summary: This study focuses on the finite-time asynchronous dissipative filter design problem for Markov jump systems with conic-type nonlinearity. By utilizing a suitable Lyapunov-Krasovskii function and linear matrix inequalities, adequate conditions are obtained to ensure the finite-time boundedness and strict dissipativity of the filtering error dynamic system. The design problems of passive and H-infinity filters are studied by adjusting parameters, and the correctness and feasibility of the designed approach are verified through a simulation example.
SCIENCE CHINA-INFORMATION SCIENCES
(2021)
Article
Engineering, Mechanical
Peng Cheng, Mengyuan Chen, Vladimir Stojanovic, Shuping He
Summary: This work investigates the issue of asynchronous fault detection filtering for discrete-time piecewise homogeneous Markov jump systems. A novel asynchronous fault detection filter is proposed and validated through real-time experiments.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Computer Science, Information Systems
Jun Cheng, Ju H. Park, Mohammed Chadli
Summary: This study addresses the peak-to-peak fuzzy filtering problem for a class of nonlinear discrete-time systems with analog fading channels and communication protocol. A novel filter design methodology is developed, and a practical example is provided to demonstrate the effectiveness and applicability of the proposed method.
INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Peng Cheng, Shuping He, Xiaoli Luan, Fei Liu
Summary: This paper focuses on the issue of finite-region H-infinity asynchronous control scheme for a class of two-dimensional Markov jump systems. It introduces a hidden Markov model to address the asynchronous phenomenon between the controlled plant and the controller, determining mode jumps with a given conditional probability matrix. An example is employed to illustrate the potential applications of the devised approach.
Article
Computer Science, Theory & Methods
Tao Wu, Lianglin Xiong, Jinde Cao, Ju H. Park
Summary: This paper investigates the problem of asynchronous control for nonlinear Markov jump systems using fuzzy quantized sampled-data controller. A novel criterion is proposed to ensure the stochastic stability of fuzzy nonlinear Markov jump systems, which has less conservatism and low computational complexity.
FUZZY SETS AND SYSTEMS
(2022)
Article
Automation & Control Systems
Yue-Yue Tao, Zheng-Guang Wu
Summary: This study investigates the asynchronous stabilization problem for discrete-time Markov jump linear systems (MJLSs) with complex mode transition probabilities (C-TPs). A practical scenario is considered where the system mode may not always be precisely detected, and some mode transition probabilities may be unknown or inaccurate. A mode separation strategy is proposed to deal with the C-TPs, and a unified controller design framework is established for MJLSs with or without C-TPs. The effectiveness of the proposed design method is demonstrated using a DC motor device.
Article
Automation & Control Systems
Kai Yin, Dedong Yang
Summary: This paper explores the design of a positive l1-gain asynchronous non-fragile fault detection filter (FDF) for discrete-time positive Markov jump systems (PMJSs) based on the dynamic event-triggered method (DETM). A new DETM that can avoid non-triviality is developed to account for the effect of positivity on event-triggered mechanisms and non-triviality on stability of discrete-time PMJSs. The asynchronous situation between the non-fragile FDF modes and the system modes is managed through a hidden Markov model.
Review
Automation & Control Systems
Shanling Dong, Meiqin Liu, Zheng-Guang Wu
Summary: In recent years, there has been a significant amount of research on the problems of asynchronous control and filtering for Markov jump systems (MJSs). The use of hidden Markov model (HMM) allows for the modeling of the asynchronous situation between the original MJSs and the controller/filter. This survey reviews the recent development of HMM-based asynchronous controller and filter design for different types of MJSs, such as linear MJSs, fuzzy MJSs, semi-MJSs, and 2D MJSs. The conclusion summarizes the findings and discusses potential future research directions for MJSs.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2023)
Article
Automation & Control Systems
Junyu Chen, Yue Long, Tieshan Li, Tianpeng Huang
Summary: In this article, a backstepping sliding mode control method based on the time-varying gain extended state observer is proposed to address the problems of unknown external disturbances and parametric uncertainties in quadrotor attitude tracking. The mathematical model of the quadrotor attitude system is introduced, and a time-varying gain extended state observer is proposed to observe unmeasurable states and total disturbances. A novel controller synthesized by backstepping sliding mode control method and the time-varying gain extended state observer is proposed for the quadrotor attitude system. Simulation results show the effectiveness and superiority of the proposed control method.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Weiwei Bai, Tieshan Li, Yue Long, C. L. Philip Chen
Summary: This article investigates the tracking control problem of event-triggered multigradient recursive reinforcement learning for nonlinear multiagent systems. It focuses on the distributed reinforcement learning approach, using a critic neural network to estimate the long-term strategic utility function and an actor neural network to approximate uncertain dynamics. The multigradient recursive strategy is used to learn the weight vector in the neural network, eliminating local optimal problems and reducing dependence on initial values. Furthermore, reinforcement learning and event-triggered mechanism improve energy conservation of multiagent systems.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Mathematics, Applied
Yingying Ren, Da-Wei Ding, Yue Long
Summary: This paper investigates fixed-order dynamic output-feedback (DOF) control for linear polytopic systems over finite-frequency ranges. The necessary and sufficient conditions for finite-frequency disturbance-attenuation performance are formulated as bilinear matrix inequalities (BMIs) using the generalized Kalman-Yakubovich-Popov lemma. The paper proposes relaxed synthesis conditions based on the homogeneous polynomically parameter-dependent technique. An iterative procedure is developed to address the BMI problem by solving a sequence of tractable convex approximations. The theoretical results are verified using an active suspension system.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Computer Science, Artificial Intelligence
Qidong Liu, Yue Long, Tieshan Li, Ju Hyun Park, C. L. Philip Chen
Summary: This article investigates the fault detection problem of unmanned marine vehicles (UMVs) under the influence caused by replay attacks. A Takagi-Sugeno (T-S) fuzzy system is used to model the dynamics of the UMV, and a switching-type attack tolerant fault detection filter is designed to consider possible replay attacks. The proposed algorithm is verified by simulations.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Automation & Control Systems
Huanqing Wang, Jialei Bao, Peter Xiaoping Liu, Tieshan Li, Ke Xu
Summary: This paper investigates the quantisation synchronisation control problem of bilateral teleoperation systems with communication delays. The inaccurate modelling problem is compensated by using radial basis function networks (RBFN) to handle system uncertainties and unknown disturbances. The control signals are quantised using a hysteretic quantiser to ease the accuracy requirement for physical systems and communication rate. Position synchronisation of joint variables is achieved through the designed control signals and adaptive parameters. Simulation results demonstrate that the synchronisation tracking errors gradually converge to a small neighbourhood around zero.
INTERNATIONAL JOURNAL OF CONTROL
(2023)
Article
Automation & Control Systems
Dong Liu, Ning Liu, Tieshan Li
Summary: In this article, an original event-triggered model-free adaptive control is proposed for nonlinear systems with output constraints. A compact form dynamic linear model is established based on the output saturated data, and a pseudo partial derivative (PPD) parameter is designed to identify the linear model. A novel event-triggered mechanism is inserted into the controller to save communication resources by activating only when the event-triggered error satisfies the predefined condition. The article provides a convergence proof for the present algorithm and demonstrates its feasibility through simulation study.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Ke He, Tieshan Li, Yue Long, Ju H. Park, C. L. Philip Chen
Summary: In this paper, the authors investigate the secure state estimation attack and reconstruction problems for linear cyber-physical systems (CPSs) under actuator attacks and unknown disturbances. A continuous sliding mode observer with an exponential reaching law strategy is introduced to improve the dynamic quality and eliminate chattering. The original system is transformed into a special attack channel separation form, and an improved sliding mode observer with disturbance compensation is obtained to solve the secure state estimation problem. Simulation results on a VTOL aircraft validate the effectiveness of the proposed scheme.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Zhe Chen, Xiao-Jun Wu, Josef Kittler
Summary: This paper proposes a Fisher regularized e-dragging framework for image classification, which improves the intraclass compactness and interclass separability of relaxed labels. The Fisher criterion and e-dragging technique are integrated into a unified model, achieving superior performance compared to other classification methods.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2023)
Article
Engineering, Marine
Yuxin Zhang, Yang Xiao, Qihe Shan, Tieshan Li
Summary: To reduce fuel-based energy consumption, it is crucial to investigate the optimal energy management for seaport integrated energy system in a fully distributed manner. A multi-objective energy management model is constructed, taking into account energy consumption, greenhouse gas emissions, and carbon trading to meet the sustainable development goals of the international shipping industry. Integrated carbon capture/storage devices are implemented to constrain the carbon emissions of the seaport. A fully distributed energy management strategy with dynamic-weighted coefficients is proposed to obtain the optimal solutions. Additionally, an event-triggered mechanism is designed to reduce communication resources, addressing the bandwidth limitation of the seaport. A rigorous mathematical analysis based on multi-agent theory and case studies demonstrates the effectiveness of the proposed method.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Xiaoyang Gao, Yue Long, Tieshan Li, Xin Hu, C. L. Philip Chen, Fuchun Sun
Summary: This article discusses the problem of optimal fuzzy output-feedback tracking control for dynamic positioning of marine vessels in the presence of uncertainties, disturbances, unavailable velocities, and thruster saturations. The proposed control scheme integrates a fuzzy velocity observer, a finite-time disturbance observer, a dynamic auxiliary system, and an optimal control strategy with dynamic surface control. Simulation results demonstrate the effectiveness of the proposed optimal control scheme.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Tieshan Li, Weiwei Bai, Qi Liu, Yue Long, C. L. Philip Chen
Summary: This article investigates the model-free fault-tolerant containment control problem for multiagent systems (MASs) with time-varying actuator faults. A distributed containment control method based on reinforcement learning (RL) is adopted to achieve the containment control objective without prior knowledge on the system dynamics. The article proposes an optimal regulation problem and employs the RL-based policy iteration method to deal with it, developing nominal and fault-tolerant controllers to compensate for actuator faults. Numerical simulations demonstrate the effectiveness and advantages of the proposed method.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Civil
Yuchi Cao, Tieshan Li, Li-Ying Hao, Xiaoyang Gao
Summary: A new nonlinear antiswing control scheme with a model predictive control (MPC) based auto-tuning mechanism is proposed for shipboard boom cranes. This scheme retains the superiority of MPC in handling constraints and improves the efficiency of searching for proper control gains. It also takes into account state constraints and input saturation to enhance the safe operation of shipboard cranes.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Automation & Control Systems
Hongjing Liang, Dongni Li, Yingnan Pan, Tieshan Li
Summary: This article proposes a detect-switch-compensate mechanism based on fault-tolerant control strategy to solve the tracking control problem. By constructing a fault observer to recognize the occurrence time of faults and using a discontinuous compensation method, the algorithm achieves high efficiency. Furthermore, the fault observer also solves the problem of unmeasured states to ensure system stability.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Dan Zhang, C. L. Philip Chen, Tieshan Li, Yi Zuo, Nguyen Quang Duy
Summary: Target tracking is widely used in intelligent transportation, real-time monitoring, human-computer interaction, etc. The proposed method based on broad learning system improves the performance of Siamese networks by combining offline training with fast online learning of new features, achieving accurate and real-time tracking.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Yuanyuan Xu, Tieshan Li, Yue Yang, Qihe Shan, Shaocheng Tong, C. L. Philip Chen
Summary: In this article, an anti-attack event-triggered secure control scheme is developed for a class of nonlinear multi-agent systems with input quantization. The scheme utilizes neural networks to approximate unknown nonlinear functions, and employs an adaptive neural state observer to obtain unknown states. An event-triggered control strategy is introduced to save communication resources, and a quantizer is used to provide accuracy under low transmission rates. A predictor is designed to resist attacks in the multi-agent network. The proposed secure control protocol guarantees bounded closed-loop signals under attacks.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
