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Distributed Coordination for a Class of High-Order Multiagent Systems Subject to Actuator Saturations by Iterative Learning Control

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  • Nana Yang
  • Suoping Li
  • Xianming Zhang

Abstract

This paper investigates a distributed coordination control for a class of high-order uncertain multiagent systems. Under the framework of iterative learning control, a novel fully distributed learning protocol is devised for the coordination problem of MASs including time-varying parameter uncertainties as well as actuator saturations. Meanwhile, the learning updating laws of various parameters are proposed. Utilizing Lyapunov theory and combining with Graph theory, the proposed algorithm can make each follower track a leader completely over a limited time interval even though each follower is without knowing the dynamics of the leader. Moreover, the extension to formation control is made. The validity and feasibility of the algorithm are verified conclusively by two examples.

Suggested Citation

  • Nana Yang & Suoping Li & Xianming Zhang, 2022. "Distributed Coordination for a Class of High-Order Multiagent Systems Subject to Actuator Saturations by Iterative Learning Control," Complexity, Hindawi, vol. 2022, pages 1-18, February.
    • Handle: RePEc:hin:complx:4020266
    DOI: 10.1155/2022/4020266
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    Cited by:

    1. Zhou, Min & Wang, JinRong & Shen, Dong, 2023. "Iterative learning control for continuous-time multi-agent differential inclusion systems with full learnability," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).

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