Interference-Resistant Control of Fixed-Wing UAV Based on Enhanced Pigeon-Inspired Optimization

In this paper, an active disturbance rejection controller (ADRC) parameter tuning method for a fixed-wing unmanned aerial vehicle (UAV) is proposed. First, a six-degree-of-freedom nonlinear model of a fixed-wing UAV is established, and the attitude controller of the UAV is built based on ADRC. Then, the Pigeon-Inspired Optimization (PIO) is enhanced based on Directional crossover (DC) and Directional variation (DV), and DXPIO is proposed to improve the searching and convergence ability of PIO. Finally, the cost function of ADRC is designed based on sigmoid function for parameter optimization training of DXPIO. In the experiments, the benchmark optimization performance of DXPIO has a significant advantage over the other 7 peers in terms of both search and development capabilities. Additionally, DXPIO is used to optimize the UAV pitch-roll controller separately, and the tuned ADRC controller is compared to the traditional proportional-integral-derivative (PID) controller when gust interference is added on the UAV's body axis. The results demonstrate that the adjusted ADRC controller has improved robustness, anti-interference rejection, and reaction time.