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Iterative learning control approach for a kind of heterogeneous multi-agent systems with distributed initial state learning

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  • Li, Jinsha
  • Li, Junmin

Abstract

In this paper, leader–follower coordination problems of a kind of heterogeneous multi-agent systems are studied by applying iterative learning control (ILC) scheme in a repeatable control environment. The heterogeneous multi-agent systems are composed of first-order and second-order dynamics in two aspects. The leader is assumed to have second-order dynamics and the trajectories of the leader are only accessible to a subset of the followers. To overcome the strict identical initial condition commonly used in ILC, the distributed initial state learning controller for each follower is designed, thus each follower agent can take arbitrary initial state. Distributed iterative learning protocols guarantee that all follower agents can achieve perfect tracking consensus for both fixed and switching communication topologies, respectively. In addition, the proposed scheme is also extended to achieve formation control for heterogeneous multi-agent system. Finally, simulation examples are given to illustrate the effectiveness of the proposed methods in this article.

Suggested Citation

  • Li, Jinsha & Li, Junmin, 2015. "Iterative learning control approach for a kind of heterogeneous multi-agent systems with distributed initial state learning," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 1044-1057.
    • Handle: RePEc:eee:apmaco:v:265:y:2015:i:c:p:1044-1057
    DOI: 10.1016/j.amc.2015.06.035
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    Cited by:

    1. Zhao, Lin & Jia, Yingmin & Yu, Jinpeng & Du, Junping, 2017. "H∞ sliding mode based scaled consensus control for linear multi-agent systems with disturbances," Applied Mathematics and Computation, Elsevier, vol. 292(C), pages 375-389.
    2. Xiongfeng Deng & Xiuxia Sun & Shuguang Liu & Boyang Zhang, 2019. "Leader-Following Consensus for Second-Order Nonlinear Multiagent Systems with Input Saturation via Distributed Adaptive Neural Network Iterative Learning Control," Complexity, Hindawi, vol. 2019, pages 1-13, May.
    3. Zhao, Lin & Yu, Jinpeng & Lin, Chong & Yu, Haisheng, 2017. "Distributed adaptive fixed-time consensus tracking for second-order multi-agent systems using modified terminal sliding mode," Applied Mathematics and Computation, Elsevier, vol. 312(C), pages 23-35.

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