Application research on improved genetic algorithm and active disturbance rejection control on quadcopters

Abstract

For nonlinear, strongly coupled, underdriven quadcopters in the context of modeling complexity and demanding performance requirements for the controller, this paper proposes a strategy based on an improved genetic algorithm to optimize the active disturbance rejection control (ADRC) controller. To make the quadcopter continue to fly stably in a complex environment, the dynamics model of the quadcopter was firstly established, the mathematical model was simplified according to the real world, and the ADRC controller of the quadcopter was designed. Given a large number of ADRC controller parameters, the difficulty of manual tuning and obtaining the optimal control effect, and the shortcomings of the genetic algorithm in solving the problem of local optimal and precocious convergence, a control strategy based on improved genetic algorithm to optimize ADRC’s parameters is proposed to improve the genetic diversity in the population and enhance the adaptability of individuals to the environment, ITAE (Integral-of-Time-multiple Absolute Error) evaluation index is selected as the fitness value. Finally, the model of the control system is built according to the real aircraft. The application results prove that the altitude, attitude of the quadcopter are controlled stably, and it is verified that the control strategy based on the improved genetic algorithm optimizing ADRC has faster rapidity, stronger tracking performance, and robustness in altitude, attitude control of the quadcopter, which has greater practical application value.