A genetic algorithm based PID fine-tuning scheme for quadrotor flight control

Abstract In this paper, an optimal adaptive proportional-integral-derivative (PID) controller to finish trajectory tracking and attitude control missions is proposed. First, a quadrotor model is designed in two controller loops, one is the position outer loop and another is the attitude inner loop. Then, a genetic algorithm (GA) is used to fine-tun the parameters of the PID controller, and an adaptive law is designed. The Euler-Lagrange equation is used to optimize the linear-quadratic regulator (LQR) cost of this controller. Compared with traditional pure PID performance, the simulation results show that the scheme in this paper got high performance and a fast response.