Fuzzy Adaptive Iterative Learning Control for Consensus of Multi-Agent Systems with Imprecise Communication Topology Structure

CHEN Jiaxi; LI Junmin; LI Jinsha

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Fuzzy Adaptive Iterative Learning Control for Consensus of Multi-Agent Systems with Imprecise Communication Topology Structure

CHEN Jiaxi #,LI Junmin *,LI Jinsha

School of Mathematics and Statistics, Xidian University, Xi’an 710126

*Correspondence author

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Funding: National Natural Science Foundations of China（No.61573013, 61603286）, Ph.D. Pragrams Foundation of Ministry of Education of China（No.20130203110021）

Opened online:27 April 2017

Accepted by: none

Citation: CHEN Jiaxi,LI Junmin,LI Jinsha.Fuzzy Adaptive Iterative Learning Control for Consensus of Multi-Agent Systems with Imprecise Communication Topology Structure[OL]. [27 April 2017] http://en.paper.edu.cn/en_releasepaper/content/4727883

This paper investigates the adaptive consensus problem of first-order linearly para -meterized multi-agent systems (MASs) with imprecise communication topology structure. T -S fuzzy models are presented to describe leader-followers MASs with imprecise communicati -on topology structure, and a fuzzy distributed adaptive iterative learning control protocol is proposed. With the dynamic of leader unknown to any of the agent, the proposed protocol gu -arantees that the follower agents can track the leader uniformly on $left[ {0,T} ight]$ for consensus prob -lem. A sufficient condition of the consensus for the closed-loop multi-agent system (MAS) is given based on Lyapunov stability theory. Finally, a simulation example is given to illustrate the effectiveness of the proposed method in this sudy.

Keywords:AILC; consensus algorithm; MAS; T-S fuzzy system; Imprecise Communication Topology Structure

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