Adaptive Neural Tracking Control of a Class of Hyperbolic PDE With Uncertain Actuator Dynamics

被引:14
作者
Xiao, Yu [1 ]
Yuan, Yuan [2 ,3 ]
Yang, Chunhua [1 ]
Luo, Biao [1 ]
Xu, Xiaodong [1 ,3 ]
Dubljevic, Stevan [3 ]
机构
[1] Cent South Univ, Sch Automat, Changsha 410083, Peoples R China
[2] Changsha Univ Sci & Technol, Sch Elect & Informat Engn, Changsha 410205, Peoples R China
[3] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 1K7, Canada
基金
中国国家自然科学基金;
关键词
Actuator dynamics; adaptive tracking control; hyperbolic PDE; neural networks (NNs); unknown nonlinearities; BACKSTEPPING BOUNDARY CONTROL; OUTPUT REGULATION; SYSTEMS; EQUATION; DESIGN;
D O I
10.1109/TCYB.2022.3223168
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 investigates the adaptive neural tracking control problem for a class of hyperbolic PDE with boundary actuator dynamics described by a set of nonlinear ordinary differential equations (ODEs). Particularly, the control input appears in the ODE subsystem with unknown nonlinearities requiring to be estimated and compensated, which makes the control task rather difficult. It is the first time to consider tracking control of such a class of systems, rendering our contributions essentially different from the existing literature that merely focus on the stabilization problem. By formulating a virtual exosystem to generate a reference trajectory, we propose a novel design of the adaptive geometric controller for the considered system where neural networks (NNs) are employed to approximately estimate nonlinearities, and finite and infinite-dimensional backstepping techniques are leveraged. Moreover, rigorously theoretical proofs based on the Lyapunov theory are provided to analyze the stability of the closed-loop system. Finally, we illustrate the results through two numerical simulations.
引用
收藏
页码:693 / 705
页数:13
相关论文
共 50 条
  • [31] Fixed-Time Adaptive Neural Tracking Control for a Class of Uncertain Nonlinear Pure-Feedback Systems
    He, Cheng
    Wu, Jian
    Dai, Jiyang
    Zhe, Zhang
    Tong, Tianchi
    IEEE ACCESS, 2020, 8 (08): : 28867 - 28879
  • [32] Adaptive neural network tracking control for a class of non-linear systems
    Liu, Yan-Jun
    Tong, Shaocheng
    Li, Yongming
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2010, 41 (02) : 143 - 158
  • [33] Adaptive Tracking Control of Robotic Manipulators With Unknown Kinematics and Uncertain Dynamics
    Tong, Yuchuang
    Liu, Jinguo
    Zhou, Hao
    Ju, Zhaojie
    Zhang, Xin
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024, 21 (04) : 5252 - 5269
  • [34] Adaptive decoupling control for a class of spinning rockets considering actuator dynamics
    Shi Z.
    Zhu H.
    Zhao L.
    Liu Z.
    Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica, 2022, 43 (03):
  • [35] Neural adaptive control of air-breathing hypersonic vehicles robust to actuator dynamics
    An, Hao
    Guo, Ziyi
    Wang, Guan
    Wang, Changhong
    ISA TRANSACTIONS, 2021, 116 : 17 - 29
  • [36] Adaptive neural tracking control for a class of uncertain switched nonlinear systems with unknown backlash-like hysteresis control input
    Wang, Xinyong
    Li, Hongmin
    Zhao, Xudong
    NEUROCOMPUTING, 2017, 219 : 50 - 58
  • [37] Adaptive tracking control of vehicle suspensions with actuator saturations
    Zhang Jing
    Wang Jue
    2015 34TH CHINESE CONTROL CONFERENCE (CCC), 2015, : 8051 - 8056
  • [38] Robust adaptive neural control for a class of uncertain MIMO nonlinear systems
    Wang, Chenliang
    Lin, Yan
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2015, 46 (11) : 1934 - 1943
  • [39] Robust tracking control of uncertain nonholonomic wheeled mobile robot incorporating the actuator dynamics
    Wang, Yu
    Wu, Yuxiang
    PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC), 2019, : 2392 - 2397
  • [40] Adaptive output feedback tracking control for a class of nonlinearly parameterised uncertain systems
    Yan, Shuai
    Sun, Weichao
    He, Fenghua
    INTERNATIONAL JOURNAL OF CONTROL, 2021, 94 (05) : 1174 - 1187