Active Disturbance Rejection Control of Quadrotor UAV based on Whale Optimization Algorithm

Xinpeng Liu, Qiang Gao, Yuehui Ji, Yu Song, Junjie Liu
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引用次数: 3

Abstract

This paper aims at the problems of nonlinearity, underactuated, strong coupling, and difficult controller parameter tuning in the control process of quadrotor UAV, PID controller and ADRC are designed to control the quadrotor UAV, and the controller parameters are optimized by the Whale Optimization Algorithm. Firstly, the ADRC is designed to control the attitude loop of the quadrotor UAV. The Extended State Observer (ESO) is designed for yaw, pitch, and roll channels to observe and compensate the internal uncertainties and external disturbances in real-time, and to realize decoupling control. Secondly, in the position control system, the PID controller is used to realize the stable tracking of position variables. Finally, the Whale Optimization Algorithm (WOA) is designed to optimize the Active Disturbance Rejection Controller and PID controller for the quadrotor UAV, which has many controller parameters and is difficult to get the optimal control effect. In this method, the parameters of the controller are taken as the objective of WOA optimization to achieve the optimal control effect. The simulation results show that the WOA optimized controller has a smaller overshoot and faster adjustment time compared with human tuning parameters.
基于Whale优化算法的四旋翼无人机自抗扰控制
针对四旋翼无人机控制过程中存在的非线性、欠驱动、强耦合、控制器参数难整定等问题,设计了PID控制器和自抗扰控制器对四旋翼无人机进行控制,并采用Whale优化算法对控制器参数进行优化。首先,设计了四旋翼无人机姿态环的自抗扰控制器。针对偏航、俯仰和滚转通道设计了扩展状态观测器(ESO),实时观察和补偿内部不确定性和外部干扰,实现解耦控制。其次,在位置控制系统中,采用PID控制器实现位置变量的稳定跟踪。最后,针对四旋翼无人机控制器参数多、难以获得最优控制效果的问题,设计了Whale优化算法(WOA)对自抗扰控制器和PID控制器进行优化。该方法以控制器参数为WOA优化目标,实现最优控制效果。仿真结果表明,与人工整定参数相比,WOA优化控制器具有更小的超调量和更快的调整时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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