Article
Computer Science, Artificial Intelligence
Kewen Li, Yongming Li
Summary: This article investigates the problem of adaptive neural network (NN) optimal consensus tracking control for nonlinear multiagent systems (MASs) with stochastic disturbances and actuator bias faults. By utilizing adaptive dynamic programming (ADP), an adaptive NN optimal consensus fault-tolerant control algorithm is presented, and its effectiveness is proven.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Yunfeng Kang, Lina Yao, Jinglin Zhou, Hong Wang
Summary: In this paper, a fault isolation, diagnosis and fault tolerant control algorithm is proposed for nonlinear multiple multiplicative faults stochastic distribution control systems employing Takagi-Sugeno fuzzy system. A fault detection algorithm is introduced to discover the fault occurrence time and a fault isolation observer is built to produce the residual. The validity of the designed algorithm is demonstrated through a simulation example.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Kewen Li, Yongming Li
Summary: This article investigates the problem of adaptive fuzzy optimal distributed consensus control for stochastic multiagent systems (MASs) with full-state constraints and nonaffine nonlinear faults. Fuzzy logic systems are employed to identify the unknown nonlinearities. To solve the problem of optimal state constraint control, a barrier Lyapunov function based optimal cost function is designed. By introducing Butterworth low-pass filter into control design, the deleterious effects raised by nonlinear fault can be compensated. By utilizing adaptive dynamic programming algorithm in critic-actor construction, a fuzzy adaptive distributed optimal consensus fault-tolerant control method is proposed, which can ensure that all signals of the controlled system are semiglobally uniformly ultimately bounded in probability, and outputs of the follower agents keep consensus with the output of leader. In addition, system states are all not exceeded their constrained bound. Finally, simulation results are provided to illustrate the feasibility of the developed control method and theorem.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Fanlin Jia, Xiao He
Summary: This paper discusses the problem of fault-tolerant tracking control for discrete-time nonstrict-feedback nonlinear systems in the presence of stochastic noises and actuator faults. A novel fault-tolerant tracking control strategy is proposed by integrating the properties of the backstepping framework and neural networks, and introducing an adaptive fault compensation term. The designed fault-tolerant controller ensures that the tracking error converges to an adjustable region regarding the origin and that all system signals are uniformly bounded concerning the mean-square sense.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Automation & Control Systems
Yuan-Xin Li, Quan-Yu Wang, Shaocheng Tong
Summary: This paper investigates the adaptive control problem for uncertain fractional nonlinear systems with actuator faults, introducing a compensating term and using a modified backstepping technique to design an adaptive controller. The proposed controller is proven to converge even in the presence of actuator faults using Fractional Lyapunov stability criterion. A simulation example of a fractional-order Chua-Hartley's system is provided to verify the effectiveness of the proposed fault-tolerant control scheme.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Rui Meng, Changchun Hua, Kuo Li, Pengju Ning
Summary: This article focuses on the problem of adaptive output feedback fault-tolerant control (FTC) for nonlinear stochastic systems with output constraint. It proposes a dynamic gain-based reduced-order K-filter for reconstructing unmeasurable state variables and a funnel-like constraint function for constraining the tracking error. It also introduces a monitoring function to detect actuator failures and applies Lyapunov stability theory to prove the boundedness of all closed-loop system signals.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Jianbin Qiu, Min Ma, Tong Wang
Summary: This article investigates the command filtering-based event-triggered adaptive fuzzy control problem for a class of stochastic nonlinear systems with stochastic faults and input saturation. The unknown nonlinear functions and system dynamic changes that caused by stochastic faults are approximated by fuzzy logic systems (FLSs). The effectiveness of the proposed method is verified by simulation studies, in which the uniform ultimate boundedness of the system is guaranteed and all the signals in the closed-loop system are bounded.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Weiyu Ji, Yingnan Pan, Meng Zhao
Summary: This article proposes an adaptive fault-tolerant formation control strategy for strict-feedback nonlinear multiagent systems with nonlinear faults and external disturbances. By employing dynamic surface control technique and disturbance-fault observer, the optimized control performance is guaranteed.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Computer Science, Artificial Intelligence
Kangkang Sun, Lu Liu, Jianbin Qiu, Gang Feng
Summary: This article investigates a fuzzy adaptive control strategy based on dynamic surface control technique for addressing nonaffine nonlinear faults in a class of strict-feedback nonlinear systems. A novel fault-tolerant control strategy is designed to ensure semi-global practical finite-time stability and convergence of tracking error to a small residual set in a finite time under the framework of finite-time stability. Simulation studies on an electromechanical system are presented to validate the feasibility of the proposed approach.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Theory & Methods
Lei Chen, Hong Xue, Hongjing Liang, Meng Zhao
Summary: This paper investigates the finite-time fault-tolerant containment control problem for stochastic nonlinear multiagent systems with intermittent actuator faults. A modified distributed observer is designed for accurate state estimation, and a compensation mechanism is proposed to suppress the adverse effects of intermittent faults. A finite-time fuzzy fault-tolerant containment control scheme is developed to achieve convergence of followers to leaders in a finite time. The effectiveness of the proposed control scheme is demonstrated through simulation studies.
FUZZY SETS AND SYSTEMS
(2023)
Article
Automation & Control Systems
Yanli Fan, Yongming Li, Shaocheng Tong
Summary: This paper discusses the adaptive finite-time output tracking control problem for nonlinear large-scale systems with positive odd rational numbers as power exponents, addressing actuator loss-of-effectiveness and bias faults with fault-tolerant control technique. An intelligent approximator is introduced to approximate the unknown nonlinear function, along with the technique of adding a power integrator to overcome system issues with power exponents. A finite-time fault-tolerant controller is proposed based on Lyapunov stability theory and backstepping algorithm, achieving convergence of tracking errors to a small neighborhood of the origin in finite time, with a simulation example demonstrating the effectiveness of the control strategies.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Computer Science, Artificial Intelligence
Yongwei Zhang, Bo Zhao, Derong Liu, Shunchao Zhang
Summary: This article presents a distributed fault-tolerant consensus control (DFTCC) approach for multiagent systems using adaptive dynamic programming. By establishing a local fault observer, the potential actuator faults of each agent are estimated. The DFTCC problem is then transformed into an optimal consensus control problem by designing a novel local value function for each agent. A critic-only structure is used to solve the Hamilton-Jacobi-Bellman equation and obtain the approximate local optimal consensus control law for each agent. The effectiveness of the proposed DFTCC scheme is validated through simulation examples.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Automation & Control Systems
Shuyi Xiao, Jiuxiang Dong
Summary: This article addresses the problem of distributed adaptive fuzzy fault-tolerant containment control for a class of heterogeneous nonlinear multiagent systems. Two FTCC strategies are proposed for different cases, and the effectiveness of the methods is demonstrated through simulation results.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Arun Bali, Siddharth Singh Chouhan, Gourav Kumar, Rahul Kumar, Uday Pratap Singh
Summary: In this article, the problem of adaptive fault-tolerant control for a class of stochastic pure-feedback nonlinear systems with simultaneous actuator and sensor faults is examined. The stochastic pure-feedback nonlinear system is converted into a strict-feedback system using the mean value theorem, and unknown functions are approximated using radial basis function neural networks. By determining the greatest value of the norm of the neural network weight vector, only one adaptive parameter needs to be calculated online. The unavailability of state variables caused by sensor faults is addressed using regrouping and parameter separation methods. The Lyapunov function methods and backstepping recursive design technique are used to design an adaptive fault-tolerant controller, which ensures convergence of tracking errors and boundedness of all signals in the closed-loop system.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Aerospace
Hyunsang Park, Youdan Kim
Summary: An adaptive fault-tolerant control scheme is proposed for nonlinear systems with actuator redundancy in this article. The L-1 adaptive control scheme for nonlinear time-varying reference systems is extended to systems with redundant inputs, and a fixed, predictable control allocation is achieved through a feedback loop. Increasing the adaptation rate and the feedback gain can improve the performance bounds of the system relative to the ideal system.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2021)
Article
Automation & Control Systems
Tao Li, Gang Li, Qing Zhao
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2015)
Article
Automation & Control Systems
Gang Li, Tao Li, Qing Zhao
IET CONTROL THEORY AND APPLICATIONS
(2017)
Article
Acoustics
Gang Li, Qing Zhao
JOURNAL OF SOUND AND VIBRATION
(2017)
Article
Engineering, Mechanical
Gang Li, Geoff L. McDonald, Qing Zhao
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2017)
Proceedings Paper
Automation & Control Systems
Gang Li, Qing Zhao
2016 AMERICAN CONTROL CONFERENCE (ACC)
(2016)
