Research on UAV Adaptive Control Method Based on Genetic Programming

In order to improve the non-linear PID control effect of a small unmanned aerial vehicle (UAV) flight, an adaptive PID height controller based on genetic programming is proposed. Firstly, the structure of the PID controller is introduced and the GP algorithm is applied in view of its characteristics of clear mapping relationship and strong non-linear fitting ability. The flight state parameters and the optimal control parameters are taken as the sample data of input and output respectively, and the intuitive functional relationship between the flight state parameters of UAV and the PID control parameters is obtained. Finally, the online adaptive tuning of the control parameters is realized. The simulation results show that the proposed PID neural network controller has faster response, smaller overshoot, higher precision, better robustness and stronger adaptive ability than the traditional PID controller, which can meet the requirements of autonomous flight.