Observer‐based adaptive consensus tracking for linear multi‐agent systems with input saturation. Issue 14 (1st September 2015)

• Record Type: Journal Article
• Authors: Chu, Hongjun; Yuan, Jingqi; Zhang, Weidong
• Is Part Of: IET control theory & applications. Volume 9:Issue 14(2015)
• Page Start: 2124
• Page End: 2131
• Publication Date: 2015-09-01
• Subjects: observers -- multi‐agent systems -- linear systems -- trees (mathematics) -- matrix algebra -- adaptive control -- vibration control -- springs (mechanical); observer‐based adaptive consensus tracking problem -- linear multi‐agent systems -- input saturation -- observer‐based consensus protocols -- undirected graph -- Laplacian matrix -- adaptive consensus protocol -- time‐varying coupling weight -- topological graph -- directed spanning tree -- semi‐global observer‐based consensus tracking -- mass‐spring systems; Control theory -- Periodicals; Automatic control -- Periodicals; 629.8312
• DOI: 10.1049/iet-cta.2014.1268
• Languages: English
• ISSNs: 1751-8644

Abstract

Abstract : This study considers the observer‐based consensus tracking problem of linear multi‐agent systems with input saturation. Existing observer‐based consensus protocols are designed based on an undirected graph, and need global information, such as the network size or eigenvalue information of the Laplacian matrix. In this study, based on only the agent dynamics and the relative outputs of neighbouring agents, an adaptive consensus protocol is proposed by assigning a time‐varying coupling weight to each node, and this protocol is independent of any global information and hence is fully distributed. Under the assumptions that each agent is asymptotically null controllable with bounded controls and detectable, and the topological graph has a directed spanning tree with the leader as the root node, semi‐global observer‐based consensus tracking of multi‐agent systems can be reached despite actuator saturation occurring. The results are applied to consensus tracking control of two‐mass‐spring systems, which are well‐known models for vibration in many mechanical systems.