Observer-based finite-time adaptive fuzzy back-stepping control for MIMO coupled nonlinear systems

被引:3
|
作者
Wang, Chao [1 ]
Zhang, Cheng [1 ]
He, Dan [2 ]
Xiao, Jianliang [1 ]
Liu, Liyan [1 ]
机构
[1] Dalian Univ Technol, Sch Comp Engn, City Inst, Dalian 116000, Peoples R China
[2] Dalian Univ Finance & Econ, Sch Management, Dalian 116000, Peoples R China
关键词
coupled nonlinear systems; adaptive fuzzy logic system; extended state observer; back-stepping; finite time; DYNAMIC SURFACE CONTROL; BACKSTEPPING CONTROL; NEURAL-NETWORK; MOTION CONTROL; DESIGN; MOTORS;
D O I
10.3934/mbe.2022497
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
An attempt is made in this paper to devise a finite-time adaptive fuzzy back-stepping control scheme for a class of multi-input and multi-output (MIMO) coupled nonlinear systems with immeasurable states. In view of the uncertainty of the system, adaptive fuzzy logic systems (AFLSs) are used to approach the uncertainty of the system, and the unmeasured states of the system are estimated by the finite-time extend state observers (FT-ESOs), where the state of the observer is a sphere around the state of the system. The accuracy and efficiency of the control effect are ensured by combining the back-stepping and finite-time theory. It is proved that all the states of the closed-loop adaptive control system are semi-global practical finite-time stability (SGPFS) by the finite-time Lyapunov stability theorem, and the tracking errors of the system states converge to a tiny neighborhood of the origin in a finite time. The validity of this scheme is demonstrated by a simulation.
引用
收藏
页码:10637 / 10655
页数:19
相关论文
共 50 条
  • [31] Observer-Based Adaptive Finite-Time Neural Control for Constrained Nonlinear Systems With Actuator Saturation Compensation
    Liu, Kang
    Yang, Po
    Jiao, Lin
    Wang, Rujing
    Yuan, Zhipeng
    Li, Tao
    IEEE Transactions on Instrumentation and Measurement, 2024, 73 : 1 - 16
  • [32] Observer-based finite-time consensus control for multiagent systems with nonlinear faults
    Zheng, Xiaohong
    Li, Xiao-Meng
    Yao, Deyin
    Li, Hongyi
    Lu, Renquan
    INFORMATION SCIENCES, 2023, 621 : 183 - 199
  • [33] Observer-Based Adaptive Finite-Time Neural Control for Constrained Nonlinear Systems With Actuator Saturation Compensation
    Liu, Kang
    Yang, Po
    Jiao, Lin
    Wang, Rujing
    Yuan, Zhipeng
    Li, Tao
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2024, 73 : 1 - 16
  • [34] Disturbance and state observer-based adaptive finite-time control for quantized nonlinear systems with unknown control directions
    Meng, Bo
    Liu, Wenhui
    Qi, Xiaojing
    Journal of the Franklin Institute, 2022, 359 (07) : 2906 - 2931
  • [35] Observer-Based Adaptive Finite-Time Tracking Control for a Class of Switched Nonlinear Systems With Unmodeled Dynamics
    Chang, Yi
    Zhang, Shuo
    Alotaibi, N. D.
    Alkhateeb, A. F.
    IEEE ACCESS, 2020, 8 : 204782 - 204790
  • [36] Disturbance and state observer-based adaptive finite-time control for quantized nonlinear systems with unknown control directions
    Meng, Bo
    Liu, Wenhui
    Qi, Xiaojing
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2022, 359 (07): : 2906 - 2931
  • [37] 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
  • [38] Observer-based adaptive fuzzy-neural control for a class of MIMO nonlinear systems
    Leu, YG
    Lee, TT
    IECON 2000: 26TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, VOLS 1-4: 21ST CENTURY TECHNOLOGIES AND INDUSTRIAL OPPORTUNITIES, 2000, : 178 - 183
  • [39] 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
  • [40] Adaptive TOPSIS fuzzy CMAC back-stepping control system design for nonlinear systems
    Lin, Chih-Min
    Tuan-Tu Huynh
    Tien-Loc Le
    SOFT COMPUTING, 2019, 23 (16) : 6947 - 6966