JOURNAL ARTICLE

Adaptive consensus tracking for linear multi-agent systems with input saturation

Hongjun ChuWeidong Zhang

Year: 2015 Journal:   Transactions of the Institute of Measurement and Control Vol: 38 (12)Pages: 1434-1441   Publisher: SAGE Publishing

Abstract

This paper addresses the consensus protocol design problem for linear multi-agent systems with input saturation. Existing consensus protocols usually contain certain global information, such as network size or the spectrum of the Laplacian matrix, and this global knowledge is often unavailable to all agents. In this paper, based on only the agent dynamics and the relative states of neighbouring agents, a novel adaptive consensus protocol is designed by assigning a time-varying coupling weight to each node. This protocol has two advantages: it is independent of any global information, and hence is fully distributed; and it is implemented by actuators with input saturation constraints. By combining the low-gain feedback method and appropriate Lyapunov techniques, it is shown that our protocol can achieve the semi-global consensus tracking in a fully distributed fashion, under the mild assumptions on agent dynamics and the topology graph. The results are illustrated by numerical simulations

Keywords:
Multi-agent system Computer science Laplacian matrix Consensus Protocol (science) Control theory (sociology) Graph Distributed computing Lyapunov function Algebraic graph theory Node (physics) Topology (electrical circuits) Nonlinear system Mathematics Theoretical computer science Engineering Artificial intelligence

Metrics

21
Cited By
3.67
FWCI (Field Weighted Citation Impact)
26
Refs
0.94
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
Neural Networks Stability and Synchronization
Physical Sciences →  Computer Science →  Computer Networks and Communications
Adaptive Control of Nonlinear Systems
Physical Sciences →  Engineering →  Control and Systems Engineering

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