Asymmetric integral barrier Lyapunov function-based adaptive tracking control considering full-state with input magnitude and rate constraint

被引:40
作者
Liu, Bojun [1 ]
Hou, Mingshan [1 ]
Ni, Junkang [1 ]
Li, Yajun [1 ]
Wu, Zhonghua [2 ]
机构
[1] Northwestern Polytech Univ, Sch Automat, Xian 710072, Peoples R China
[2] Henan Polytech Univ, Sch Elect Engn & Automat, Jiaozuo 454000, Henan, Peoples R China
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2020年 / 357卷 / 14期
基金
中国国家自然科学基金;
关键词
MIMO NONLINEAR-SYSTEMS; DYNAMIC SURFACE CONTROL; FIELD-OF-VIEW; PRESCRIBED PERFORMANCE; ATTITUDE-CONTROL; SPACECRAFT; GUIDANCE; ANTIWINDUP; DESIGN;
D O I
10.1016/j.jfranklin.2020.07.037
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 paper investigates the neural adaptive tracking control problem of a class of strict-feedback systems considering asymmetric full-state with input magnitude and rate constraint (MRC). By designing a dual-integral-type actual control law, the MRC on system input is transformed to be the magnitude limitations on the extended states of the original system, so the original system with both state and MRC considerations is converted to be a new system with only full-state constraint. Besides, compared with the traditional symmetric integral barrier Lyapunov function, new asymmetric integral barrier Lyapunov function is introduced to the dynamic surface-based controller design process in this paper for dealing with the asymmetric state constraint problem. It is analyzed that the original system is semi-globally uniformly ultimately bounded, and that the desired multiple constraints are never violated. The effectiveness of the control strategy is shown via numerical simulations. (C) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:9709 / 9732
页数:24
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