Fuzzy Automatic Disturbance Rejection Control of Quadrotor UAV Based on Improved Whale Optimization Algorithm

Abstract

With the aim of improving the rapidity and accuracy of quadrotor UAV positional trajectory tracking, this paper proposes a fuzzy automatic disturbance rejection control of quadrotor UAV based on improved whale optimization algorithm (IWOA-Fuzzy-ADRC). (1) To address the problems of low accuracy and slow convergence of the traditional whale algorithm, a combination of logistic chaos mapping and skew tent mapping is applied to improve the diversity of the initial population. (2) The global search capability is strengthened to avoid falling into local optimum through introducing the cross operator and Gaussian variational operators. (3) The IWOA is employed to iteratively optimize the adjustment coefficients of the fuzzy active disturbance rejection controller, the calculus gain of the nonlinear state error feedback control (NLSEF), and the error correction coefficients of the expansive state observer (ESO). The simulation results demonstrate that compared with the traditional ADRC controller and PID controller, the proposed IWOA-Fuzzy-ADRC controller can effectively improve the control performance of the system, accurately track the desired flight trajectory, accelerate the dynamic response of the control system, reduce the steady-state error, and enhance the anti-interference capability.

Keywords

• UAV trajectory tracking
• fuzzy ADRC
• whale optimization algorithm
• chaotic mapping
• cross-operator
• Gaussian variant operators