Adaptive non-singular fast terminal sliding mode control for multi-agent systems with unknown non-linear dynamics

被引：17
|
作者：
Gu, Xiaowei [1 ]
Niu, Yugang [1 ]
Chen, Bei [2 ]
机构：
[1] East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China
[2] Shanghai Univ Engn Sci, Sch Elect & Elect Engn, Shanghai 201620, Peoples R China
来源：
IET CONTROL THEORY AND APPLICATIONS | 2020年 / 14卷 / 16期
基金：
上海市自然科学基金;
关键词：
multi-agent systems; variable structure systems; nonlinear control systems; neurocontrollers; convergence; adaptive control; radial basis function networks; setting time; adaptive nonsingular fast terminal sliding mode control; nonlinear dynamics; finite time consensus tracking problems; second-order nonlinear multiagent system; unknown dynamics; radial basis function neural networks; approximate the lumped unknown dynamic model; finite-time consensus tracking; nonsingular fast terminal sliding mode control strategy; BREATHING HYPERSONIC VEHICLES; NEURAL APPROXIMATION; CONSENSUS CONTROL; TRACKING;
D O I：
10.1049/iet-cta.2019.1136
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 study considers the finite time consensus tracking problems for second-order non-linear multi-agent system with the unknown dynamics. Firstly, the radial basis function neural networks are utilised to approximate the lumped unknown dynamic model. And then, to achieve the finite-time consensus tracking, a distributed non-singular fast terminal sliding mode control strategy is designed which can speed up the convergence of the multi-agent system. Moreover, the consistency under the proposed control strategy is theoretically analysed and the upper bound of setting time is explicitly obtained. Finally, two simulation examples are provided.
引用
收藏
页码：2223 / 2232
页数：10
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