A Data-Driven Distributed Adaptive Control Approach for Nonlinear Multi-Agent Systems

被引：1

作者：

Yu, Xian ^{[1
]}

Jin, Shangtai ^{[1
]}

Liu, Genfeng ^{[1
]}

Lei, Ting ^{[2
]}

Ren, Ye ^{[3
]}

机构：

[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China

[2] Zhengzhou Univ Light Ind, Coll Elect & Informat Engn, Zhengzhou 450002, Peoples R China

[3] North China Univ Technol, Sch Elect & Control Engn, Beijing 100144, Peoples R China

来源：

IEEE ACCESS | 2020年 / 8卷

基金：

中国国家自然科学基金;

关键词：

Adaptive control; Decentralized control; Heuristic algorithms; Data models; Multi-agent systems; Adaptation models; Topology; Dynamic linearization; data-driven control; adaptive control; multi-agent systems; consensus tracking; FINITE-TIME CONSENSUS; TRACKING; DESIGN; AGENTS;

D O I：

10.1109/ACCESS.2020.3038629

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper the distributed leader-follower consensus tracking problem is investigated for unknown nonlinear non-affine discrete-time multi-agent systems. Via a dynamic linearization method both for the agent system and the local ideal distributed controller, a distributed adaptive control scheme is proposed in this paper using the Newton-type optimization method. The proposed approach is data-driven since only the local measurement information among neighboring agents is utilized in the control system design. The consensus tracking stabilities of the proposed approach are rigorously guaranteed in the cases of fixed and switching communication topologies. The simulations are conducted to verify the effectiveness of the proposed approach.

引用

页码：207884 / 207893

页数：10

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