JOURNAL ARTICLE

Periodic event‐triggered consensus control for multi‐agent systems with switching jointly connected topologies

Jian SunZhanshan WangXiaofei Fan

Year: 2020 Journal:   IET Control Theory and Applications Vol: 14 (19)Pages: 3282-3290   Publisher: Institution of Engineering and Technology

Abstract

The consensus problem for a class of multi‐agent systems with switching jointly connected topologies via periodic event‐triggered control is studied. The distinguishing feature of such system is that the eigenvalues of system matrix can contain positive real parts. Due to the coexistence of unstable system matrix and disconnected topologies, the agents can diverge from each other across some periods even if the control input is imposed on them. To overcome this difficulty, a periodic‐sampling time unit (PSTU) approach is introduced to analyse the local convergence or divergence property within each sampling time unit based on the periodic event‐triggering control. Then the stabilisation property of switching behaviours is utilised to compensate the divergence within each switching interval via the dwell time technique. It is interesting to see that each switching period is considered to consist of finite number of PSTUs. Then by confining a pair of lower and upper bounds on the dwell time, the overall consensus can be reached. Further, a novel class of event‐dependent discretised Lyapunov functions are utilised to describe the error characteristics and computable conditions for the overall consensus can be derived. Finally, the effectiveness of the proposed result is illustrated by a numerical example.

Keywords:
Network topology Control theory (sociology) Multi-agent system Consensus Computer science Control (management) Topology (electrical circuits) Mathematics Computer network Artificial intelligence

Metrics

13
Cited By
1.70
FWCI (Field Weighted Citation Impact)
35
Refs
0.85
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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