TY - GEN
T1 - Chaotic grey wolf optimization-based active disturbance rejection control applied to quadrotor trajectory tracking
AU - Lou, Jiang
AU - Zhou, Hui
AU - Cai, Zhihao
AU - Zhao, Jiang
AU - Wu, Kun
AU - Wang, Yingxun
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8
Y1 - 2018/8
N2 - In this paper, a new active disturbance rejection control (ADRC) scheme based on swarm intelligent method is proposed for quadrotors to achieve position tracking and attitude stabilization. First, the finite-time convergent extended state observer (FTCESO) is designed to enhance the performance of ADRC controller. Then, the chaotic grey wolf optimization (CGWO) algorithm is developed with chaos initialization and chaos search to obtain the optimal parameters of attitude and position controllers. Numerical simulations are presented to demonstrate the effectiveness of the CGWO-based ADRC scheme.
AB - In this paper, a new active disturbance rejection control (ADRC) scheme based on swarm intelligent method is proposed for quadrotors to achieve position tracking and attitude stabilization. First, the finite-time convergent extended state observer (FTCESO) is designed to enhance the performance of ADRC controller. Then, the chaotic grey wolf optimization (CGWO) algorithm is developed with chaos initialization and chaos search to obtain the optimal parameters of attitude and position controllers. Numerical simulations are presented to demonstrate the effectiveness of the CGWO-based ADRC scheme.
UR - https://www.scopus.com/pages/publications/85082443294
U2 - 10.1109/GNCC42960.2018.9019188
DO - 10.1109/GNCC42960.2018.9019188
M3 - 会议稿件
AN - SCOPUS:85082443294
T3 - 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018
BT - 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018
Y2 - 10 August 2018 through 12 August 2018
ER -