H∞ fuzzy control design of discrete-time nonlinear active fault-tolerant control systems

被引:21
|
作者
Wu, Huai-Ning [1 ]
机构
[1] Beijing Univ Aeronaut & Astronaut, Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
fault-tolerant control; fuzzy control; H-infinity control; linear matrix inequality (LMI); nonlinear systems; stochastic stability; STOCHASTIC STABILITY ANALYSIS; OUTPUT-FEEDBACK CONTROL; DISTURBANCE ATTENUATION; IDENTIFICATION; STABILIZATION;
D O I
10.1002/rnc.1367
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper is concerned with the problem of H-infinity fuzzy controller synthesis for a class of discrete-time nonlinear active fault-tolerant control systems (AFTCSs) in a stochastic setting. The Takagi and Sugeno (T-S) fuzzy model is employed to exactly represent a nonlinear AFTCS. For this AFTCS, two random processes with Markovian transition characteristics are introduced to model the failure process of system components and the fault detection and isolation (FDI) decision process used to reconfigure the control law, respectively. The random behavior of the FDI process is conditioned on the state of the failure process. A non-parallel distributed compensation (non-PDC) scheme is adopted for the design of the fault-tolerant control laws. The resulting closed-loop fuzzy system is the one with two Markovian jump parameters. Based oil a stochastic fuzzy Lyapunov function (FLF), Sufficient conditions for the stochastic stability and H-infinity disturbance attenuation of the closed-loop fuzzy system are first derived. A linear matrix inequality (LMI) approach to the fuzzy control design is then developed. Moreover, a suboptimal fault-tolerant H-infinity fuzzy controller is given in the sense of minimizing the level of disturbance attenuation. Finally, a simulation example is presented to illustrate the effectiveness of the proposed design method. Copyright (c) 2008 John Wiley & Soils, Ltd.
引用
收藏
页码:1129 / 1149
页数:21
相关论文
共 50 条
  • [31] Active fault-tolerant control design for Takagi-Sugeno fuzzy systems
    Dziekan, L.
    Witczak, M.
    Korbicz, J.
    BULLETIN OF THE POLISH ACADEMY OF SCIENCES-TECHNICAL SCIENCES, 2011, 59 (01) : 93 - 102
  • [32] Adaptive NN fault-tolerant control for discrete-time systems in triangular forms with actuator fault
    Liu, Lei
    Wang, Zhanshan
    Zhang, Huaguang
    NEUROCOMPUTING, 2015, 152 : 209 - 221
  • [33] H∞ control design for discrete-time switched fuzzy systems
    Wang, Tiechao
    Tong, Shaocheng
    NEUROCOMPUTING, 2015, 151 : 782 - 789
  • [34] Robust Fault Estimation and Fault-Tolerant Control for Discrete-Time Systems Subject to Periodic Disturbances
    Hu, Yuxiang
    Dai, Xuewu
    Wu, Yunkai
    Jiang, Bin
    Cui, Dongliang
    Jia, Zhian
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2023, 70 (07) : 2982 - 2994
  • [35] Design of Active Holonic Fault-Tolerant Control Systems
    da Silva, Robson M.
    Miyagi, Paulo E.
    Santos Filho, Diolino J.
    TECHNOLOGICAL INNOVATION FOR SUSTAINABILITY, 2011, 349 : 367 - +
  • [36] Fault-tolerant H∞ control for discrete descriptor linear systems with time delay
    Zhang, Rui-Zhi
    Yang, Xin-Rong
    Zhang, Xian
    CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 3788 - 3793
  • [37] H∞ Control design for discrete-time nonlinear delayed systems
    Subramaniyam, Ramasamy
    Joo, Young Hoon
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2023, 33 (11) : 6188 - 6210
  • [38] Fault-tolerant control of discrete-time LPV systems using virtual actuators and sensors
    Tabatabaeipour, S. Mojtaba
    Stoustrup, Jakob
    Bak, Thomas
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2015, 25 (05) : 707 - 734
  • [39] A fault-tolerant control strategy for Lipschitz non-linear discrete-time systems
    Witczak, Marcin
    Korbicz, Jozef
    18TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION, 2010, : 1079 - 1084
  • [40] Model free adaptive fault-tolerant tracking control for a class of discrete-time systems
    Wang, Yuan
    Wang, Zhanshan
    NEUROCOMPUTING, 2020, 412 : 143 - 151