Full-state constraints stabilization control for uncertain nonlinear systems

被引：0
|
作者：
Jia, Fu-Jin [1 ,2 ]
Zhang, Tian-Liang [2 ]
Lu, Jun-Wei [3 ]
机构：
[1] School of Electrical Engineering and Automation, Anhui University, Anhui, Hefei,230039, China
[2] School of Automation, Nanjing University of Science and Technology, Jiangsu, Nanjing,210094, China
[3] School of Electrical and Automation Engineering, Nanjing Normal University, Jiangsu, Nanjing,210023, China
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2024年 / 41卷 / 12期
基金：
中国国家自然科学基金;
关键词：
Approximation methods - Barrier lyapunov function - Constraint stabilization - Full-state constraint - Fuzzy approximation - Lyapunov's functions - Neural-network approximations - Stabilization control - State constraints - Uncertain nonlinear systems;
D O I：
10.7641/CTA.2023.20731
中图分类号：
学科分类号：
摘要：
In this paper, the full-state constraints stabilization control for a class of nonlinear systems with unknown functions is studied. Different from the fuzzy approximation method and the neural network approximation method for solving the unknown function problem, the control method in this paper can make the system state asymptotically converge to the origin, and solve the explosion of terms problem of the backstepping method. At the same time, different from the barrier Lyapunov functions for solving the full-state constraints control problem, a new full-state constraints method is proposed to make the state asymptotically stable. Finally, the simulation results of Duffing system and single-link robot verify the effectiveness of this algorithm. © 2024 South China University of Technology. All rights reserved.
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页码：2393 / 2400
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