Command-Filter-Based Adaptive Fuzzy Finite-Time Control for Switched Nonlinear Systems Using State-Dependent Switching Method

被引:0
|
作者
Li, Shi [1 ]
Ahn, Choon Ki [2 ]
Xiang, Zhengrong [1 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Peoples R China
[2] Korea Univ, Sch Elect Engn, Seoul 02841, South Korea
基金
中国国家自然科学基金; 新加坡国家研究基金会;
关键词
Switches; Nonlinear systems; Adaptive systems; Switched systems; Design methodology; Backstepping; Adaptive fuzzy control; command filtering; finite-time control; nonlinear systems; state feedback; switched systems;
D O I
10.1109/TFUZZ.2020.2965917
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The adaptive fuzzy finite-time tracking control problem of a class of switched nonlinear systems is investigated in this study. Fuzzy logic systems are introduced to handle the unknown nonlinear terms in the considered system. To overcome the drawback in the recursive design method, a finite-time command filter is employed. By constructing a new state-dependent switching law and adaptive fuzzy control signal, the existing restrictions on subsystems of switched systems are relaxed, all subsystems of the considered system are allowed to be unstabilizable. To avoid the Zeno behavior, a new hysteresis switching law is derived. It is proven that all states of the closed-loop system are bounded in finite time under the proposed fuzzy finite-time control scheme. Additionally, the proposed control method is extended to a class of more general switched large-scale nonlinear systems. Finally, two examples are provided to verify the developed method's effectiveness.
引用
收藏
页码:833 / 845
页数:13
相关论文
共 50 条
  • [21] Fast finite-time command filter-based adaptive composite tracking control for nonlinear systems
    Siwen Liu
    Tieshan Li
    Huanqing Wang
    Nonlinear Dynamics, 2023, 111 : 3393 - 3409
  • [22] Fast finite-time command filter-based adaptive composite tracking control for nonlinear systems
    Liu, Siwen
    Li, Tieshan
    Wang, Huanqing
    NONLINEAR DYNAMICS, 2023, 111 (04) : 3393 - 3409
  • [23] Command-filter-based fast finite-time composite adaptive neural control for nonlinear systems with input dead-zone
    Jiang, Wei
    Wang, Huanqing
    Wang, Wei
    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2023, 37 (07) : 1782 - 1802
  • [24] Fuzzy Finite-Time Command Filtering Output Feedback Control of Nonlinear Systems
    Wang, Libin
    Wang, Huanqing
    Liu, Peter Xiaoping
    Ling, Song
    Liu, Siwen
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 30 (01) : 97 - 107
  • [25] Neural-Network-Based Adaptive Constrained Control for Switched Systems Under State-Dependent Switching Law
    Tang, Li
    Zhang, Xin-Yu
    Liu, Yan-Jun
    Tong, Shaocheng
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 34 (08) : 4057 - 4067
  • [26] Finite-Time Adaptive Fuzzy Tracking Control for a Class of Nonlinear Systems With Full-State Constraints
    Zhao, Lin
    Liu, Guoqing
    Yu, Jinpeng
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2021, 29 (08) : 2246 - 2255
  • [27] Adaptive Fuzzy Finite-time Control for Switched Nonlinear Inverted Pendulum Systems
    Fan, Yanli
    Yang, Tingting
    Li, Yongming
    PROCEEDINGS OF THE 15TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA 2020), 2020, : 1288 - 1293
  • [28] Finite-Time Stability of Switched Nonlinear Systems With State Jumps: A Dwell-Time Method
    Wu, Feiyue
    Li, Can
    Lian, Jie
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2022, 52 (10): : 6061 - 6072
  • [29] Finite-Time Command-Filtered Composite Adaptive Neural Control of Uncertain Nonlinear Systems
    Sun, Jinlin
    He, Haibo
    Yi, Jianqiang
    Pu, Zhiqiang
    IEEE TRANSACTIONS ON CYBERNETICS, 2022, 52 (07) : 6809 - 6821
  • [30] Adaptive Finite-Time Fuzzy Funnel Control for Nonaffine Nonlinear Systems
    Liu, Cungen
    Wang, Huanqing
    Liu, Xiaoping
    Zhou, Yucheng
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (05): : 2894 - 2903