基于双空间PSO算法的四旋翼无人机自抗扰控制器优化设计

ADRC Controller Optimization Design Based on Two-space PSO Algorithm for Quad-rotor UAV

四旋翼无人机自抗扰控制器所需的参数较多,传统PSO算法虽然可以对控制器的参数进行有效的整定,但需要的粒子群数量较大,寻优速度也比较慢。本文在传统PSO算法的基础上,根据自抗扰控制器的特点,将所需整定的参数分为两组,从两个空间里分别初始化各自的粒子群,并进行交叉寻优,形成一种双空间PSO算法,对四旋翼无人机自抗扰控制器进行优化。仿真结果表明,相比传统的PSO算法,双空间PSO算法所需粒子群数量少,寻优速度更快,而且经过双空间PSO算法优化后的自抗扰控制器具有更小的误差和更快的收敛速度。

The traditional quad-rotor UAV active disturbance rejection controller(ADRC)requires many parameters,and the traditional PSO algorithm can effectively set the parameters of the controller,but it requires a large number of particle groups and slows down the optimization speed.In this paper,based on the traditional PSO algorithm,according to the characteristics of the ADRC,the ADRC parameters are divided into two groups,and initialized the particle groups in two spaces,and cross-optimization is carried out to form a two-space PSO algorithm.Simulation results show that,compared with the traditional PSO algorithm,the two-space PSO algorithm requires fewer particle groups and has a faster optimization speed,so the ADRC optimized by the two-space PSO algorithm has a smaller error and a faster convergence speed.