摘要
针对传统PID控制中抗干扰性差、控制精度不高等问题,在控制中引入微分控制与神经网络,基于微分器与RBF神经网络重新设计PID控制器,经过仿真,上述控制器可以发挥更好的控制效果,改善了PID控制中的抗噪性和精准度,使得控制器的适应性及鲁棒性获得提升.研究对PID控制的改善工作具有理论性的意义,也对我国的工业发展具有现实性的指导意义.
For the problem of poor anti-interference and low control precision in traditional PID control,differential control and neural network were introduced in the control,the PID controller was redesigned based on differentiator and RBF neural network. After simulation experiment,the new controller has the better control effect,improving the noise immunity and precision of PID control and promoting the adaptation and robustness of the controller. The research has theoretical significance to the improvement of PID control and practical guide significance to China's industrial development.
作者
陈利
CHEN Li(Xianda College of Economics and Humanities Shanghai International Studies University,Shanghai 200083)
出处
《计算机仿真》
北大核心
2019年第10期298-301,共4页
Computer Simulation
