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Attitude Control of UAVs with Search Optimization and Disturbance Rejection Strategies

Author

Listed:
  • Wensheng Li

    (China Southern Power Grid Technology Co., Ltd., Guangzhou 510080, China
    Guangdong Engineering Technology Research Center of Special Robots for Special Industries, Guangzhou 510080, China)

  • Fanke Yang

    (Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China)

  • Liqiang Zhong

    (China Southern Power Grid Technology Co., Ltd., Guangzhou 510080, China
    Guangdong Engineering Technology Research Center of Special Robots for Special Industries, Guangzhou 510080, China)

  • Hao Wu

    (China Southern Power Grid Technology Co., Ltd., Guangzhou 510080, China
    Guangdong Engineering Technology Research Center of Special Robots for Special Industries, Guangzhou 510080, China)

  • Xiangyuan Jiang

    (Institute of Marine Science and Technology, Shandong University, Qingdao 266237, China)

  • Chunbo Luo

    (Department of Computer Science, University of Exeter, Exeter EQ4 4QN, UK)

  • Andrei V. Chukalin

    (Laboratory of Interdisciplinary Problems in Energy Production, Ulyanovsk State Technical University, Ulyanovsk 432027, Russia)

Abstract

This study aims to achieve rapid and stable control of quadrotor unmanned aerial vehicles’ (UAVs) attitude by using an Active Disturbance Rejection Control (ADRC) controller. Addressing the challenge of numerous and complex ADRC parameters, optimization algorithms are employed for parameter tuning. This paper draws on the group mechanism of the Ant Colony Optimization (ACO) algorithm and innovatively introduces population search into the Beetle Antennae Search (BAS) algorithm. The refined algorithm is then applied to tune the ADRC parameters, reducing complexity and human intervention while enhancing intelligence and efficiency. The advanced optimization algorithm exhibits an exceptional global optimization capacity, convergence speed, and stability. Ultimately, flight simulation and experimental results suggest that the optimized ADRC controller demonstrates superior control and antidisturbance capabilities.

Suggested Citation

  • Wensheng Li & Fanke Yang & Liqiang Zhong & Hao Wu & Xiangyuan Jiang & Chunbo Luo & Andrei V. Chukalin, 2023. "Attitude Control of UAVs with Search Optimization and Disturbance Rejection Strategies," Mathematics, MDPI, vol. 11(17), pages 1-16, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:17:p:3794-:d:1232510
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    References listed on IDEAS

    as
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    2. Alphonsus, Ephrem Ryan & Abdullah, Mohammad Omar, 2016. "A review on the applications of programmable logic controllers (PLCs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1185-1205.
    3. Yudong Zhang & Shuihua Wang & Genlin Ji, 2015. "A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-38, October.
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