JOURNAL ARTICLE

Event‐triggered cooperative compensation control for consensus of heterogeneous multi‐agent systems

Yanliang CuiMinrui FeiDajun Du

Year: 2016 Journal:   IET Control Theory and Applications Vol: 10 (13)Pages: 1573-1582   Publisher: Institution of Engineering and Technology

Abstract

This paper addresses the event‐triggered consensus for heterogeneous multi‐agent systems (He‐MASs) via a distributed cooperative compensation control (D3C) strategy. The proposed D3C law involves two dynamics: (i) a pre‐given virtual leader, which specifies the synchronisation trajectory for whole He‐MASs; (ii) two intermediate compensation system, whose system state is broadcasted to neighbour agents through communication network for facilitating the consensus. To further reduce data exchanging frequency so as to alleviate communication burden, an exponential event‐trigger is employed to determine whether the current sampled data need to be broadcasted or suspended. By two concise algebraic Riccati inequalities and some supplement conditions, a sufficient collaborative design method is presented for obtaining the values of D3C gains and the thresholds of event‐trigger, while the Zeno phenomena is also excluded. The proposed strategy guarantees the consensus of He‐MASs and significantly reduces data exchanging amounts. Finally, some illustrative examples are given to validate effectiveness of the proposed results.

Keywords:
Compensation (psychology) Control theory (sociology) Multi-agent system Computer science Control (management) Consensus Event (particle physics) Distributed computing Artificial intelligence Psychology Physics

Metrics

23
Cited By
4.18
FWCI (Field Weighted Citation Impact)
46
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Distributed Control Multi-Agent Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
Advanced Memory and Neural Computing
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Neural Networks Stability and Synchronization
Physical Sciences →  Computer Science →  Computer Networks and Communications
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