Optimised backstepping control for the nonlinear strict-feedback system having unknown control dead-zone

被引:0
|
作者
Sun, Wenxia [1 ]
Ma, Shuaihua [1 ]
Li, Bin [1 ]
Wen, Guoxing [2 ]
机构
[1] Qilu Univ Technol, Shandong Acad Sci, Sch Math & Stat, Jinan, Peoples R China
[2] Shandong Univ Aeronaut, Coll Sci, Binzhou, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
Reinforcement learning (RL); dead-zone; tracking control; optimised backstepping (OB); nonlinear strict-feedback system; ADAPTIVE-CONTROL; TRACKING CONTROL;
D O I
10.1080/00207179.2024.2364357
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, the optimised backstepping (OB) strategy is extended to deal with the dead-zone control problem for a class of the nonlinear strict feedback systems. Since the dead-zone phenomenon is frequently encountered in the control of nonlinear strict feedback system, it is very necessary to consider the effect of dead-zone in the OB control. However, the published OB control methods are to rarely deal with the dead-zone problem because of the complex algorithm of reinforcement learning (RL). In this OB control, the dead-zone problem is effectively solved by utilising a simplified RL algorithm. For effective eliminating the effect of dead-zone, an adaptive compensation of dead-zone function's remainder is added to this RL. Since the RL under identifier-critic-actor architecture is implemented in every backstepping step, the requirement of complete dynamic acknowledge is released. Ultimately, the validity of this OB method is certified both theory and simulation.
引用
收藏
页码:704 / 717
页数:14
相关论文
共 50 条
  • [21] Adaptive homo-backstepping tracking control for strict-feedback systems in presence of unknown dead-zones
    Gao, Qiang
    Ji, Yuehui
    Zhou, Hailaing
    Li, Junfang
    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2017, 31 (08) : 1101 - 1110
  • [22] Fuzzy Backstepping Control for Strict-Feedback Nonlinear Systems with Mismatched Uncertainties
    Xu Zibin
    Min Jianqing
    2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2010, : 5054 - 5057
  • [23] Output Feedback Adaptive Control for Stochastic Non-strict-feedback System with Dead-zone
    Yumei Sun
    Bingwei Mao
    Hongxia Liu
    Shaowei Zhou
    International Journal of Control, Automation and Systems, 2020, 18 : 2621 - 2629
  • [24] Adaptive Non-Backstepping Fuzzy Control for a Class of Uncertain Nonlinear Systems with Unknown Dead-Zone Input
    Wang, Rui
    Yu, Fusheng
    Wang, Jiayin
    ASIAN JOURNAL OF CONTROL, 2015, 17 (04) : 1394 - 1402
  • [25] Adaptive fuzzy control for a class of nonlinear systems with unknown dead-zone
    Zhang, Tianping
    Wang, Zhengqun
    Yi, Yang
    Yang, Yuequan
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 3862 - +
  • [26] Adaptive Fuzzy Control for MIMO Nonlinear Systems with Unknown Dead-Zone
    Boulkroune, A.
    M'Saad, M.
    Tadjine, M.
    Farza, M.
    2008 4TH INTERNATIONAL IEEE CONFERENCE INTELLIGENT SYSTEMS, VOLS 1 AND 2, 2008, : 204 - +
  • [27] Adaptive Output Feedback Control for Uncertain Nonlinear Systems with Unknown Dead-Zone Input
    Xia Xiao-Nan
    Zhang Tian-Ping
    2014 33RD CHINESE CONTROL CONFERENCE (CCC), 2014, : 8729 - 8734
  • [28] Observer-Based Adaptive Fuzzy Control for Time-Varying State Constrained Strict-Feedback Nonlinear Systems with Dead-Zone
    Peihao Du
    Kai Sun
    Shiyi Zhao
    Hongjing Liang
    International Journal of Fuzzy Systems, 2019, 21 : 733 - 744
  • [29] Unifying adaptive control with the nonlinear PI methodology: Designs for unknown strict-feedback nonlinear systems with nonsmooth actuator nonlinearities
    Psillakis, H. E.
    Lagos, A. -R.
    INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2018, 32 (02) : 362 - 377
  • [30] Adaptive fuzzy prescribed performance control for MIMO nonlinear systems with unknown control direction and unknown dead-zone inputs
    Shi, Wuxi
    Luo, Rui
    Li, Baoquan
    ISA TRANSACTIONS, 2017, 66 : 86 - 95