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Soft Computing
Published in: Soft Computing 15/2019

07-06-2018 | Methodologies and Application

Coordination control of uncertain topological high-order multi-agent systems: distributed fuzzy adaptive iterative learning approach

Authors: Hui Wu, Junmin Li

Published in: Soft Computing | Issue 15/2019

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Abstract

This paper demonstrates that the method of T–S fuzzy model can be used to describe the uncertain topological structure for high-order linearly parameterized multi-agent systems (MAS). The dynamic of the leader is only available to a portion of the follower agents; thus, we present a novel distributed adaptive iterative learning control (AILC) protocol without using any global information to deal with the consensus problem of MAS under initial-state learning condition. It is proved that the proposed control protocol ensures all the internal signals in the multi-agent system are bounded, and the follower agents track the leader exactly on the finite time interval [0, T]; a sufficient condition is obtained for the exactly consensus result of the multi-agent system by choosing the appropriate composite energy function. Extensions to the formation control of multi-agent systems are also given. In the end, illustrative examples are shown to verify the availability of the proposed AILC scheme.
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Metadata
Title
Coordination control of uncertain topological high-order multi-agent systems: distributed fuzzy adaptive iterative learning approach
Authors
Hui Wu
Junmin Li
Publication date
07-06-2018
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 15/2019
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3271-1

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