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Iterative learning control for UAVs formation based on point-to-point trajectory update tracking

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  • Fu, Xingjian
  • Peng, Jianshuai

Abstract

For the problem of trajectory tracking in UAVs formation system, an adaptive iterative learning control strategy based on point-to-point trajectory update tracking is proposed. The nonlinear discrete system after iterative dynamic linearization approximation is combined with the UAVs formation system, and the time-varying parameters are introduced for trajectory tracking. According to the iterative linear dynamic condition and the global Lipschitz condition, the system tracking error is analyzed under the iterative learning control based on point-to-point trajectory tracking. The proposed control method not only uses the freedom degree of the tracking points to analyze the convergence and robustness for the UAVs formation, but also introduces error prediction to improve the anti-disturbance ability for the system. Finally, the simulation study for the UAV formation system is carried out to verify the effectiveness of the proposed method.

Suggested Citation

  • Fu, Xingjian & Peng, Jianshuai, 2023. "Iterative learning control for UAVs formation based on point-to-point trajectory update tracking," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 209(C), pages 1-15.
    • Handle: RePEc:eee:matcom:v:209:y:2023:i:c:p:1-15
    DOI: 10.1016/j.matcom.2023.01.038
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    References listed on IDEAS

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    1. Dong Shen, 2020. "Iterative learning control using faded measurements without system information: a gradient estimation approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 51(14), pages 2675-2689, October.
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    Cited by:

    1. Lina Si & Xinyang Guo & Lixun Huang & Qiuwen Zhang, 2024. "State Estimators for Plants Implementing ILC Strategies through Delay Links," Mathematics, MDPI, vol. 12(18), pages 1-18, September.

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