A Dynamic Decoupling Approach to Robust T-S Fuzzy Model-Based Control

被引:14
|
作者
Chiu, Chian-Song [1 ]
机构
[1] Chung Yuan Christian Univ, Dept Elect Engn, Chungli 32023, Taiwan
关键词
Input actuator nonlinearity; Takagi-Sugeno (T-S) fuzzy control; time-delay input; uncertainty; H-INFINITY CONTROL; NONLINEAR-SYSTEMS; STABILITY ANALYSIS; STABILIZATION; DESIGN; STATE; SUBJECT;
D O I
10.1109/TFUZZ.2013.2280145
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, a dynamic decoupling approach is proposed to improve the robust Takagi-Sugeno (T-S) fuzzy model-based control to cope with system uncertainty, input actuator non-linearity, and input time delay. First, the basic dynamic decoupling concept is introduced by involving virtual input dynamics, such that the system uncertainty and control input are decoupled in each fuzzy rule. This leads to simplified linear matrix inequality (LMI) conditions. Next, the dynamic decoupling approach is extended to controlling uncertain systems with input actuator nonlinearity (e.g., saturation, quantization, dead-zone, etc.) or time-varying input delay. Due to the decoupling between uncertainty, actuator nonlinearity, and input delay, more relaxed stability conditions are obtained for the asymptotic stability and H-infinity control performance. Furthermore, the limit on the initial condition is removed when considering input saturation. Larger and faster time-varying state and input delays are allowed under fewer LMIs. Finally, to show the advantages of the developed control method, numerical simulations are carried out on an inverted pendulum (subject to either the saturation, quantization, or delay input), a delay mass-spring-damper system, and a delay truck-trailer system.
引用
收藏
页码:1088 / 1100
页数:13
相关论文
共 50 条
  • [1] Robust output tracking CMAC control: The T-S fuzzy model-based approach
    Chiu, CS
    Chiang, TS
    PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), VOLS 1-5, 2005, : 2290 - 2295
  • [2] Robust T-S fuzzy model-based for chaotic cryptosystem
    Chiang, TS
    Wang, CC
    Chiang, CT
    PROCEEDINGS OF THE 2002 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOL 1 & 2, 2002, : 290 - 295
  • [3] T-S fuzzy model-based robust finite time control for uncertain nonlinear systems
    Tran, Xuan-Toa
    Kang, Hee-Jun
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2015, 229 (12) : 2174 - 2186
  • [4] Robust Maximum Power Tracking Control of Uncertain Photovoltaic Systems: A Unified T-S Fuzzy Model-Based Approach
    Chiu, Chian-Song
    Ouyang, Ya-Lun
    IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2011, 19 (06) : 1516 - 1526
  • [5] T-S Fuzzy Model-Based Adaptive Dynamic Surface Control for Ball and Beam System
    Chang, Yeong-Hwa
    Chan, Wei-Shou
    Chang, Chia-Wen
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2013, 60 (06) : 2251 - 2263
  • [6] Impulsive control for T-S fuzzy model-based chaotic systems
    Zhong, Qishui
    Bao, Jingfu
    Yu, Yongbin
    Liao, Xiaofeng
    MATHEMATICS AND COMPUTERS IN SIMULATION, 2008, 79 (03) : 409 - 415
  • [7] T-S Fuzzy Model-Based Depth Control of Underwater Vehicles
    Qian Y.
    Feng Z.
    Bi A.
    Liu W.
    Journal of Shanghai Jiaotong University (Science), 2020, 25 (03): : 315 - 324
  • [8] Intelligent Control: A T-S Fuzzy Model Based Approach
    Feng, Gang
    PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2012, : XXIV - XXIV
  • [9] Maximum Power Control of PV Systems via a T-S Fuzzy Model-based Approach
    Chiu, Chian-Song
    Ouyang, Ya-Lun
    Chiang, Teng-Shung
    Liu, Peter
    ICIEA 2010: PROCEEDINGS OF THE 5TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOL 4, 2010, : 468 - +
  • [10] Robust State Feedback H∞Control for Dynamic Biped Robot Based on T-S Fuzzy Model
    HUAI Chuangfeng FANG Yuefa (Department of Mechanical Engineering
    武汉理工大学学报, 2006, (S3) : 951 - 955