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Finite-time adaptive event-triggered command filtered backstepping control for a QUAV

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  • Yang, Wei
  • Cui, Guozeng
  • Ma, Qian
  • Ma, Jiali
  • Tao, Chongben

Abstract

In this paper, the problem of event-triggered finite-time trajectory tracking control for a quadrotor unmanned aerial vehicle (QUAV) is studied. For the translation and rotation subsystems of QUAV, the finite-time command filter can make the derivative of virtual control signals be quickly approximated, and the effect of filtered error is eliminated by constructing the fractional power error compensated mechanism. By synthesizing command filter technique and event-triggered mechanism into the framework of backstepping design procedure, the finite-time adaptive control strategy for a QUAV is proposed, which reduces the resource occupation and maintains the stability and performance. It is proved that the position and attitude tracking errors can converge to a small neighborhood near the origin in a finite time. Finally, the availability and superiority of the proposed finite-time algorithm are verified by a comparative simulation.

Suggested Citation

  • Yang, Wei & Cui, Guozeng & Ma, Qian & Ma, Jiali & Tao, Chongben, 2022. "Finite-time adaptive event-triggered command filtered backstepping control for a QUAV," Applied Mathematics and Computation, Elsevier, vol. 423(C).
    • Handle: RePEc:eee:apmaco:v:423:y:2022:i:c:s0096300321009814
    DOI: 10.1016/j.amc.2021.126898
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    References listed on IDEAS

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    1. Lijia Cao & Yongchao Wang & Shengxiu Zhang & Tan Fei, 2018. "Command-filtered sensor-based backstepping controller for small unmanned aerial vehicles with actuator dynamics," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(16), pages 3365-3376, December.
    2. Huo, Xin & Ma, Li & Zhao, Xudong & Zong, Guangdeng, 2020. "Event-triggered adaptive fuzzy output feedback control of MIMO switched nonlinear systems with average dwell time," Applied Mathematics and Computation, Elsevier, vol. 365(C).
    3. Lü, Shao-Yu & Jin, Xiao-Zheng & Wang, Hai & Deng, Chao, 2021. "Robust adaptive estimation and tracking control for perturbed cyber-physical systems against denial of service," Applied Mathematics and Computation, Elsevier, vol. 404(C).
    4. Shao, Xingling & Yue, Xiaohui & Li, Jie, 2021. "Event-triggered robust control for quadrotors with preassigned time performance constraints," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    5. Vadivel, R. & Hammachukiattikul, P. & Gunasekaran, Nallappan & Saravanakumar, R. & Dutta, Hemen, 2021. "Strict dissipativity synchronization for delayed static neural networks: An event-triggered scheme," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
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    Cited by:

    1. Xiongfeng Deng & Yiming Yuan & Lisheng Wei & Binzi Xu & Liang Tao, 2022. "Adaptive Neural Tracking Control for Nonstrict-Feedback Nonlinear Systems with Unknown Control Gains via Dynamic Surface Control Method," Mathematics, MDPI, vol. 10(14), pages 1-13, July.
    2. Cui, Guozeng & Xu, Hui & Yu, Jinpeng & Ma, Jiali & Li, Ze, 2023. "Fixed-time distributed adaptive attitude control for multiple QUAVs with quantized input," Applied Mathematics and Computation, Elsevier, vol. 449(C).
    3. Xu, Xiao & Wang, Li & Du, Zhenbin & Kao, Yonggui, 2023. "H∞ Sampled-Data Control for Uncertain Fuzzy Systems under Markovian Jump and FBm," Applied Mathematics and Computation, Elsevier, vol. 451(C).
    4. Xu, Lin-Xing & Wang, Yu-Long & Wang, Fei & Long, Yue, 2023. "Event-triggered active disturbance rejection trajectory tracking control for a quadrotor unmanned aerial vehicle," Applied Mathematics and Computation, Elsevier, vol. 449(C).

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