High-order differential feedback control and its application in quadrotor UAV

被引：0
|
作者：
Li X. [1 ]
Qi G. [2 ]
Guo X. [1 ]
Zhao X. [2 ]
机构：
[1] School of Mechanical Engineering, Tianjin Polytechnic University, Tianjin
[2] Tianjin Key Laboratory of Intelligent Control of Electrical Equipment, Tianjin Polytechnic University, Tianjin
来源：
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2022年 / 43卷 / 12期
基金：
中国国家自然科学基金;
关键词：
active disturbance rejection control; attitude system; extended state observer; high-order differentiator; model-free control; quadrotor unmanned aerial vehicle; unknown model function estimation;
D O I：
10.7527/S1000-6893.2021.26047
中图分类号：
学科分类号：
摘要：
The high-order differential feedback controller is a control scheme inddepent of the precise model of the system. It indirectly compensates for the system unknown model function through a control filter. However, the high-order differentiator has not been used to estimate the system unknown model function, which is indirectly compensated. In this paper, an improved high-order differentiator is proposed by introducing control input information, which can estimate the unknown functions in nonlinear models and the differential information of system output and reference input in real-time. The convergence of the unknown model functions estimated by the improved high-order differentiator and the extended state observer is compared and analyzed. It is proved that the former is one type higher than the latter. A novel high-order differential feedback control algorithm is designed using the estimated differential and model functions, suppressing unknown disturbance and successfully controlling the Quadrotor Unmanned Aerial Vehicle(QUAV) attitude system. Lyapunov-based stability analysis is conducted to prove the stability of the closed-loop system. In the control test platform experiment based on the Pixhawk, schemes of the proposed improved high-order differential feedback control, PID control, active disturbance rejection control and the traditional high-order differential feedback control are adopted to test the tracking performance and disturbance rejection ability of the quadrotor unmanned aerial vehicle for different reference attitude. The results show that the proposed scheme is significantly superior to other ones in transient performance, steady-state tracking accuracy and robustness. © 2022 AAAS Press of Chinese Society of Aeronautics and Astronautics. All rights reserved.
引用
收藏
相关论文
共 33 条
  • [1] ZHANG Y., CHEN Z Q., ZHANG X H, Et al., A novel control.scheme for quadrotor UAV based upon active disturbance rejection control [J], Aerospace Science and Technology, 79, pp. 601-609, (2018)
  • [2] ZHAO B, X1AN B, ZHANG Y, Et al., Nonlinear robust adaptive tracking control of a quadrotor UAV via immersion and invariance methodology, IEEE Transactions on Industrial Electronics, 62, 5, pp. 2891-2902, (2015)
  • [3] JIA Y N, TIAN S Y, LI Q., Recent development of unmanned aerial vehicle swarms, Acta Aeronautica et Astronautica Sinica, 41, 31, (2020)
  • [4] BI HY, QI CY, HU JB., Modeling and analysis of chaos and bifurcations for the attitude system of a quadrotor unmanned aerial vehicle, Complexity, 2019, (2019)
  • [5] BI H Y, QI G Y, HU J B, Et al., Hidden and transient chaotic attractors in the attitude system of quadrotor unmanned aerial vehicle, Chaos, Solitons & Fractals, 138, (2020)
  • [6] AILON A, AROGETI S., Closed-form nonlinear tracking controllers for quadrotors with model and input generator uncertainties, Automatica, 54, pp. 317-324, (2015)
  • [7] XIAN B, ZHA J H., Nonlinear disturbance-rejection control design for tilting tri-rotor UAV[J], Control and Decision, 33, 2, pp. 263-268, (2018)
  • [8] ZHANG X Y, WANG Y, ZHU G Q, Et al., Compound adaptive fuzzy quantized control for quadrotor and its experimental verification, IEEE Transactions on Cybernetics, 51, 3, pp. 1121-1133, (2021)
  • [9] DOU L Q, SU X T, ZHAO X Y, Et al., Robust tracking control of quadrotor via on-policy adaptive dynamic programming, International Journal of Robust and Nonlinear Control, 31, 7, pp. 2509-2525, (2021)
  • [10] LIN X B, YU Y, SUN C Y., Supplementary reinforcement learning controller designed for quadrotor UAVs, IEEE Access, 7, pp. 26422-26431
1234