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Consensus control for multi-agent systems with quasi-one-sided Lipschitz nonlinear dynamics via iterative learning algorithm

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Abstract

This paper deals with the problem of iterative learning control algorithm for consensus of a class of multi-agent systems, and all the agents in the considered systems are governed by the nonlinear dynamics with quasi-one-sided Lipschitz condition. Based on the framework of network topologies, distributed consensus-based iterative learning control protocols are designed by using the nearest neighbor knowledge. Under the action of the iterative learning control law, consensus on the finite time interval along the iteration axis can be reached for all the directed communication graphs with spanning trees. A simulation example is finally used to illustrate the effectiveness of the proposed approach.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (No. 11371013) and Natural Science Foundation of Suzhou University of Science and Technology (No. XKZ201613). The authors would like to express their gratitude to the editor and the anonymous referees for their valuable suggestions that have greatly improved the quality of the paper.

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Authors and Affiliations

  1. The School of Mathematics and Physics, Suzhou University of Science and Technology, Suzhou, 215009, Jiangsu, China

    Qin Fu, Xiang-Dong Li, Li-Li Du, Guang-Zhao Xu & Jian-Rong Wu

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  1. Qin Fu
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  2. Xiang-Dong Li
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  3. Li-Li Du
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  4. Guang-Zhao Xu
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  5. Jian-Rong Wu
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Correspondence to Qin Fu.

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Fu, Q., Li, XD., Du, LL. et al. Consensus control for multi-agent systems with quasi-one-sided Lipschitz nonlinear dynamics via iterative learning algorithm. Nonlinear Dyn 91, 2621–2630 (2018). https://doi.org/10.1007/s11071-017-4035-7

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  • DOI: https://doi.org/10.1007/s11071-017-4035-7

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