Finite-Time Prescribed Performance Tracking Control for High-Order Nonlinear Time-Delay Systems

被引：0
|
作者：
Lu, Kexin [1 ]
Wang, Huanqing [1 ]
Shen, Haikuo [2 ]
Wang, Dongyang [1 ]
机构：
[1] Bohai Univ, Sch Math Sci, Jinzhou 121000, Peoples R China
[2] Beijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing 100091, Peoples R China
来源：
2023 2ND CONFERENCE ON FULLY ACTUATED SYSTEM THEORY AND APPLICATIONS, CFASTA | 2023年
关键词：
Time-delay systems; Finite-time performance function (FTPF); Radial basis function neural networks; GLOBAL STABILIZATION;
D O I：
10.1109/CFASTA57821.2023.10243167
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 study on the tracking control problem of a class of nonlinear high order time-delay systems. The method used to approximate the unknown nonlinear functions is the Radial basis function neural networks (RBFNNs). Then, we propose a feasible adaptive neural tracking control scheme backstepping and prescribed performance technology. The Lyapunov stability theory is applied to ensure that all signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB), and that the tracking error is always kept within the prescribed performance range. The proposed control policy is verified to he effective through simulation results.
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页码：258 / 263
页数：6
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