Simplified adaptive backstepping control for uncertain nonlinear systems with unknown input saturation and its application

被引:4
作者
Liu, Jiapeng [1 ]
Chen, Xinkai [2 ]
Yu, Jinpeng [1 ]
机构
[1] Qingdao Univ, Sch Automat, Qingdao 266071, Peoples R China
[2] Shibaura Inst Technol, Dept Elect & Informat Syst, Saitama 3378570, Japan
基金
中国国家自然科学基金;
关键词
Adaptive control; Backstepping; Input saturation; Uncertainty; Nonlinear system; OUTPUT-FEEDBACK CONTROL; TRACKING CONTROL;
D O I
10.1016/j.conengprac.2023.105639
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The calculation complex problem is one of the significant obstacles in the real-time implementation of traditional backstepping controllers. In this paper, we consider the simplification problem of the adaptive backstepping tracking controller for uncertain nonlinear systems with unknown input saturation. Compared with traditional backstepping controllers, virtual stabilizing functions and their derivatives are needless in our controller, which effectively reduces the computation burden. And then the one-order compensation subsystem is employed to eliminate the effect of nonlinear uncertainties based on the adaptive control scheme and the congelation of variables technique. Next, the performance of the closed-loop nonlinear system is analyzed based on the Lyapunov stability theorem. In the final, simulation and experimental results are given to show the effectiveness of our controller.
引用
收藏
页数:9
相关论文
共 35 条
  • [1] Adaptive backstepping control for an engine cooling system with guaranteed parameter convergence under mismatched parameter uncertainties
    Butt, S.
    Aschemann, H.
    [J]. CONTROL ENGINEERING PRACTICE, 2017, 64 : 195 - 204
  • [2] Adaptive Control for Systems With Time-Varying Parameters
    Chen, Kaiwen
    Astolfi, Alessandro
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2021, 66 (05) : 1986 - 2001
  • [3] Finite-time adaptive fuzzy command filtered control for nonlinear systems with indifferentiable non-affine functions
    Chen, Lian
    Wang, Qing
    [J]. NONLINEAR DYNAMICS, 2020, 100 (01) : 493 - 507
  • [4] An improved design strategy for approximation-based adaptive event-triggered tracking of a class of uncertain nonlinear systems
    Choi, Yun Ho
    Yoo, Sung Jin
    [J]. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2019, 356 (08): : 4378 - 4396
  • [5] Neural-Based Decentralized Adaptive Finite-Time Control for Nonlinear Large-Scale Systems With Time-Varying Output Constraints
    Du, Peihao
    Liang, Hongjing
    Zhao, Shiyi
    Ahn, Choon Ki
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2021, 51 (05): : 3136 - 3147
  • [6] Command Filtered Backstepping
    Farrell, Jay A.
    Polycarpou, Marios
    Sharma, Manu
    Dong, Wenjie
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2009, 54 (06) : 1391 - 1395
  • [7] Robust adaptive backstepping tracking control of stochastic nonlinear systems with unknown input saturation: A command filter approach
    Homayoun, Behrouz
    Arefi, Mohammad Mehdi
    Vafamand, Navid
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2020, 30 (08) : 3296 - 3313
  • [8] Command filter-based event-triggered adaptive neural network control for uncertain nonlinear time-delay systems
    Li, Baomin
    Xia, Jianwei
    Sun, Wei
    Park, Ju H.
    Sun, Zong-Yao
    [J]. INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2020, 30 (16) : 6363 - 6382
  • [9] Finite time command filtered adaptive fault tolerant control for a class of uncertain nonlinear systems
    Li, Yuan-Xin
    [J]. AUTOMATICA, 2019, 106 : 117 - 123
  • [10] Adaptive Neural Control of Pure-Feedback Nonlinear Systems With Event-Triggered Communications
    Li, Yuan-Xin
    Yang, Guang-Hong
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2018, 29 (12) : 6242 - 6251