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Distributed Adaptive Iterative Learning Consensus for Uncertain Topological Multi-agent Systems Based on T–S Fuzzy Models

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Abstract

This paper addresses the exactly consensus problem for the multi-agent system with uncertain topology structure. A T–S fuzzy model is presented to describe the uncertain topology structure of multi-agent systems. Under the assumptions that the dynamic of the leader is only available to a portion of the follower agents and there exist initial-state errors in the procedure of the iterative learning, a new distributed adaptive iterative learning control with the distributed initial-state learning is proposed to ensure all the follower agents track the leader on the finite-time interval. Sufficient conditions are obtained by appropriately constructing Lyapunov function for the exactly consensus problem. Furthermore, the approach is also extended to the exactly formation control problem. Finally, the simulation examples are given to verify the efficacy of the theoretical analysis.

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Acknowledgements

This work is supported by National Nature Science Foundation of China under Grant 61573013 and by Ph.D. Programs Foundation of Ministry of Education of China under Grant 20130203110021.

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Authors and Affiliations

  1. School of Mathematics and Statistics, Xidian University, Xi’an, 710126, People’s Republic of China

    Hui Wu, Junmin Li & Jiaxi Chen

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  1. Hui Wu
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  2. Junmin Li
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  3. Jiaxi Chen
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Correspondence to Junmin Li.

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Wu, H., Li, J. & Chen, J. Distributed Adaptive Iterative Learning Consensus for Uncertain Topological Multi-agent Systems Based on T–S Fuzzy Models. Int. J. Fuzzy Syst. 20, 2605–2619 (2018). https://doi.org/10.1007/s40815-018-0518-z

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  • DOI: https://doi.org/10.1007/s40815-018-0518-z

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