摘要
在介绍BP神经网络结构和学习算法的基础上,给出了一种数控机床进给伺服系统基于BP神经网络的自整定PID控制算法,并设计了基于BP神经网络自整定PID控制器的结构。在Matlab仿真中证实,该算法减小了系统的调节时间,提高了系统的响应速度、抗干扰能力和对被控对象参数变化的适应能力。
On the basis of introducing BP neural network structure and learning algorithm, this paper provides a self-tuning PID control algorithm based on BP neural network and designs the structure of controller. The Matlab simulation verifies that this method reduces the system＇s adjusting time, improves the system＇ s response speed, anti-interference capability and adaptive ability to deal with the parameter＇s change of controlled object.
出处
《自动化与仪器仪表》
2012年第5期176-178,共3页
Automation & Instrumentation
