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Fuzzy adaptive iterative learning coordination control of second-order multi-agent systems with imprecise communication topology structure

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  • Jiaxi Chen
  • Junmin Li

Abstract

In this paper, we investigate the perfect consensus problem for second-order linearly parameterised multi-agent systems (MAS) with imprecise communication topology structure. Takagi-Sugeno (T–S) fuzzy models are presented to describe the imprecise communication topology structure of leader-following MAS, and a distributed adaptive iterative learning control protocol is proposed with the dynamic of leader unknown to any of the agent. The proposed protocol guarantees that the follower agents can track the leader perfectly on [0,T] for the consensus problem. Under alignment condition, a sufficient condition of the consensus for closed-loop MAS is given based on Lyapunov stability theory. Finally, a numerical example and a multiple pendulum system are given to illustrate the effectiveness of the proposed algorithm.

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  • Jiaxi Chen & Junmin Li, 2018. "Fuzzy adaptive iterative learning coordination control of second-order multi-agent systems with imprecise communication topology structure," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(3), pages 546-556, February.
    • Handle: RePEc:taf:tsysxx:v:49:y:2018:i:3:p:546-556
    DOI: 10.1080/00207721.2017.1412533
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    Cited by:

    1. Yang, Nana & Li, Junmin & Chen, Jiaxi, 2020. "Fully distributed hybrid adaptive learning consensus protocols for a class of non-linearly parameterized multi-agent systems," Applied Mathematics and Computation, Elsevier, vol. 375(C).

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