Distributed Learning Consensus Control for Unknown Nonlinear Multi-Agent Systems based on Gaussian Processes

被引：3
|
作者：
Yang, Zewen [1 ,2 ]
Sosnowski, Stefan [1 ]
Liu, Qingchen [1 ]
Jiao, Junjie [1 ]
Lederer, Armin [1 ]
Hirche, Sandra [1 ]
机构：
[1] Tech Univ Munich, Dept Elect & Comp Engn, Chair Informat Oriented Control ITR, D-80333 Munich, Germany
[2] Harbin Engn Univ, Coll Intelligent Syst Sci & Engn, Harbin 150001, Peoples R China
来源：
2021 60TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2021年
基金：
欧洲研究理事会;
关键词：
TRACKING CONTROL; LEADER;
D O I：
10.1109/CDC45484.2021.9683522
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, a distributed learning leader-follower consensus protocol based on Gaussian process regression for a class of nonlinear multi-agent systems with unknown dynamics is designed. We propose a distributed learning approach to predict the residual dynamics for each agent. The stability of the consensus protocol using the data-driven model of the dynamics is shown via Lyapunov analysis. The followers ultimately synchronize to the leader with guaranteed error bounds by applying the proposed control law with a high probability. The effectiveness and the applicability of the developed protocol are demonstrated by simulation examples.
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页码：4406 / 4411
页数：6
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