Partial-state feedback adaptive stabilization for a class of output-constrained nonlinear cascaded systems

被引:0
|
作者
Wu, Kang [1 ]
Yu, Jiangbo [2 ]
Zhao, Yan [2 ]
机构
[1] Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Jiangsu, Peoples R China
[2] Shandong Jianzhu Univ, Sch Sci, Jinan 250101, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
BARRIER LYAPUNOV FUNCTIONS; TIME TRACKING CONTROL; GLOBAL STABILIZATION; NEURAL-CONTROL;
D O I
10.1016/j.jfranklin.2022.05.029
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 presents a robust adaptive stabilizing control scheme via partial-state feedback for a class of nonlinear cascaded systems with a time-varying output constraint. Different from the existing achievements, the nonlinear parameterization and unmeasured zero-dynamics are considered in this paper. The notion of input-to-state stability (ISS) and ISS-Lyapunov function are used to describe the zero-dynamics. The time-varying barrier Lyapunov function (TVBLF) is employed to ensure the output constraint satisfaction and the changing supply rates technique is used to deal with the unknown cascaded zero-dynamic states. It is shown that all the signals in the closed-loop system are bounded, and the asymptotic stabilization is achieved without violation of the output constraint. The performance of the proposed control scheme is illustrated through a simulation example. (c) 2022 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:5412 / 5432
页数:21
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