Observer-based distributed consensus for multi-agent systems with directed networks and input saturation

被引:10
作者
Yu, Shuzhen [1 ]
Yu, Zhiyong [1 ]
Jiang, Haijun [1 ]
Mei, Xuehui [1 ]
机构
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-agent systems; Input saturation; Low-gain feedback control; Directed networks; LEADER-FOLLOWING CONSENSUS; COORDINATED CONTROL; ADAPTIVE CONSENSUS; LINEAR-SYSTEMS; TRACKING; SYNCHRONIZATION; SUBJECT; AGENTS;
D O I
10.1016/j.neucom.2020.09.003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we devise a distributed protocol to study the consensus of multi-agent systems (MASs) with input saturation over directed networks. Firstly, a low-gain feedback control method is applied to overcome the saturation constraints, and an observation system without saturation constraints is designed. The semiglobal consensus condition over directed strongly connected networks is developed by using Ricatti equation. Secondly, a novel of tree-type error scheme is proposed to solve the consensus of MASs with general directed spanning tree networks. Combination with inequality techniques and Lyapunov stability theory, some criteria for achieving semiglobal consensus are obtained. In addition, the semiglobal consensus of MASs with directed switching networks is further considered, in which the network topologies only need to contain a directed spanning tree in some time intervals. Some related conditions are derived to ensure the consensus. Finally, some numerical simulations are given to demonstrate the validity of the theoretical results. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:111 / 123
页数:13
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