Active Disturbance Rejection Control of Quadrotor UAVs Based on Joint Observation and Feedforward Compensation

Abstract

Under the influence of uncertain parameters and external disturbance, the accuracy is low and the response is slow of attitude and trajectory tracking in the flight control of the quadrotor unmanned air vehicles (UAV). In order to solve the problems, Because of the excellent adaptability and noise suppression ability of the extended Kalman filter for nonlinear system problems , it is used to suppress the high-frequency signal disturbance to reduce the estimation burden of the extended state observer, and jointly with the expanded state observer to estimate the total disturbance formed by the system uncertainty parameters and external disturbances to reduce system reliance on accurate models, and the differential values of perturbation estimated values is used by feedforward compensation to improve the tracking accuracy under abrupt disturbances and to overcome the phase lag caused by abrupt disturbances. Extended Kalman filtering, extended state observer with the feedforward compensation and PD controller with error compensation are comprehensively integrated into an improved active disturbance rejection controller which can suppress high frequency noise and abrupt disturbances to the better extent. Simulation and experiment results show that the joint observer can effectively reduce the observation error amplitude, correct the observation phase lag in advance, and obtain more accurate state information, and that the improved active disturbance rejection controller can better meet requirements of quadrotor UAV for fast response, efficient and stable control. Therefore, it can accurately and efficiently complete complex trajectory tracking operations.