Fuzzy Observer Constraint Based on Adaptive Control for Uncertain Nonlinear MIMO Systems With Time-Varying State Constraints

被引:78
|
作者
Liu, Yan-Jun [1 ]
Gong, Mingzhe [1 ]
Liu, Lei [1 ]
Tong, Shaocheng [1 ]
Chen, C. L. Philip [2 ,3 ]
机构
[1] Liaoning Univ Technol, Coll Sci, Jinzhou 121000, Peoples R China
[2] South China Univ Technol, Sch Comp Sci & Engn, Guangzhou 510006, Peoples R China
[3] Dalian Maritime Univ, Nav Coll, Dalian 116026, Peoples R China
基金
中国国家自然科学基金;
关键词
Observers; Time-varying systems; MIMO communication; Adaptive control; Nonlinear systems; Output feedback; nonlinear multi-input– multi-output (MIMO) systems; state constraints; state observer design;
D O I
10.1109/TCYB.2019.2933700
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 article presents an adaptive output feedback approach of nonlinear multi-input-multi-output (MIMO) systems with time-varying state constraints and unmeasured states. An adaptive approximator is designed to approximate the unknown nonlinear functions existing in the state-constrained systems with immeasurable states. To deal with the tracking problem of such systems, a state observer with time-varying barrier Lyapunov functions (BLFs) is introduced in the controller design procedure. The backstepping design with time-varying BLFs is utilized to guarantee that all system states remain within the time-varying-constrained interval. The constant constraint is only the special case of the time-varying constraint which is more general in the real systems. The proposed control approach guarantees that all signals in the closed-loop systems are bounded and the tracking errors converge to a bounded compact set, and time-varying full-state constraints are never violated. A simulation example is given to confirm the feasibility of the presented control approach in this article.
引用
收藏
页码:1380 / 1389
页数:10
相关论文
共 50 条
  • [41] Multidimensional Taylor network adaptive control for MIMO time-varying uncertain nonlinear systems with noises
    Zhang, Chao
    Yan, Hong-Sen
    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2020, 30 (01) : 397 - 420
  • [42] Observer-based adaptive fuzzy H∞ tracking control of uncertain MIMO nonlinear systems
    Liu, Yanjun
    Wang, Wei
    Zhu, Ruijun
    2007 IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1-7, 2007, : 33 - 37
  • [43] Adaptive Fuzzy Fault-Tolerant Control for Uncertain Nonlinear Switched Stochastic Systems with Time-Varying Output Constraints
    Liu, Yanli
    Ma, Hongjun
    Ma, Hui
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26 (05) : 2487 - 2498
  • [44] Observer-based adaptive fuzzy tracking control for a class of uncertain nonlinear MIMO systems
    Liu, Yan-Jun
    Tong, Shao-Cheng
    Li, Tie-Shan
    FUZZY SETS AND SYSTEMS, 2011, 164 (01) : 25 - 44
  • [45] State Observer and Robust Control for Uncertain Systems with Time-varying State Delay
    Zhang, Tao
    Cui, Yanqiu
    2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 5580 - 5584
  • [46] State observer and robust control for uncertain systems with time-varying state delay
    Zhang, Tao
    Cui, Yan-Qiu
    PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2008, : 2143 - 2148
  • [47] Neural observer-based adaptive compensation control for nonlinear time-varying delays systems with input constraints
    Wen, Yuntong
    Ren, Xuemei
    EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (02) : 1944 - 1955
  • [48] Fuzzy adaptive event-triggered control for a class of nonlinear systems with time-varying full state constraints
    Jin, Xin
    Li, Yuan-Xin
    INFORMATION SCIENCES, 2021, 563 : 111 - 129
  • [49] Observer-based fuzzy adaptive control for stochastic nonlinear time-varying delay systems with unknown control directions
    Liu, Yanli
    Ma, Hongjun
    2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2017, : 6167 - 6172
  • [50] Adaptive neural network terminal sliding mode tracking control for uncertain nonlinear systems with time-varying state constraints
    Jiang, Dao-gen
    Lv, Long-jin
    Song, Sun-hao
    Li, Jia-hao
    MEASUREMENT & CONTROL, 2024,