基于神经模糊PID控制的四旋翼飞行器算法

四旋翼飞行器在执行任务时经常会出现稳定姿态精度低,抵抗干扰能力差等问题,提出一种神经模糊PID控制算法来调整原有模糊PID控制的模糊规则和隶属度函数,将设计的神经模糊PID控制算法与建立的四旋翼飞行器动力学模型相结合.为了验证神经模糊PID控制器的有效性,将传统PID、模糊PID控制算法作为对比算法,同时给定人为干扰因素.经过Matlab/Simulink仿真实验表明:在神经模糊PID控制下的四旋翼飞行器,具有较好的响应速度,稳态精度及更好的抗干扰能力,控制效果均优于对比算法.

Algorithm of Quadrotor Based on Neural Fuzzy PID Control

Quadrotor aircrafts often encounter problems such as low stable attitude accuracy and poor resistance to interference when performing tasks. A neuro-fuzzy PID control algorithm is proposed to adjust the fuzzy rules and membership functions of the original fuzzy PID control. The neuro-fuzzy PID control algorithm is combined with the established dynamic model of the quadrotor aircraft. The traditional PID and fuzzy PID control algorithms are used as comparison algorithms with human interference factors considered to validate the neuro-fuzzy PID controller. The Matlab/Simulink simulation experiment shows that the neuro-fuzzy PID control has better control effect on quadrotor aircrafts than comparison algorithms according to its faster response, higher stable attitude accuracy, and stronger resistance to interference.