Distributed iterative learning coordination control for leader-follower uncertain non-linear multi-agent systems with input saturation

被引:21
作者
Yang, Nana [1 ,2 ]
Li, Junmin [1 ]
机构
[1] Xidian Univ, Sch Math & Stat, Xian 710126, Shaanxi, Peoples R China
[2] Lanzhou Univ Technol, Sch Sci, Lanzhou 730000, Gansu, Peoples R China
关键词
learning (artificial intelligence); nonlinear control systems; adaptive control; control system synthesis; uncertain systems; multi-robot systems; learning systems; iterative methods; multi-agent systems; distributed control; Lyapunov methods; nonlinear multiagent systems; input saturation; fully distributed adaptive iterative learning coordination control; nonlinear leader-follower multiagent systems; alignment initial condition; novel adaptive distributed; control protocol; fully saturated parameter learning law; global perfect consensus tracking; consensus tracking problem; formation control problem; CONSENSUS TRACKING CONTROL; GLOBAL CONSENSUS; CONTROL DESIGN; CONSTRAINTS;
D O I
10.1049/iet-cta.2018.6268
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 study, the fully distributed adaptive iterative learning coordination control of the uncertain non-linear leader-follower multi-agent systems with input saturation is studied. Under the alignment initial condition and Lyapunov theory, a novel adaptive distributed control protocol with a fully saturated parameter learning law is designed. Despite the existence of input saturation, the global perfect consensus tracking can be realised over a finite time interval. Besides, the consensus tracking problem is extended to the formation control problem as well. Ultimately, the validity of theoretical analysis of this study is shown by two examples.
引用
收藏
页码:2252 / 2260
页数:9
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