摘要
将神经网络应用到PID控制器的参数整定过程中,提出一种基于改进单神经元PID的控制算法,通过在吹瓶机温度解耦控制系统中的应用,得出了仿真结果及结论。仿真结果表明:该控制算法具有很强的自学习功能和自适应解耦能力,能取得良好的控制效果,因而可以广泛地应用于多变量系统的解耦控制中。
Neural network is applied to parameters＇ tuning of digital PID controller, a control algorithm based on the improved single neuron PID is presented and applied to control system of bottle blowing machine temperatures. So we draws simulation results and a conclusion. The simulation results show that the control algorithm has a strong self-learning function and adaptive decoupling capacity and can obtain the good control effect. As a result, it can be far-ranging applied to decoupling control of MIMO system.
出处
《黑龙江大学工程学报》
2011年第4期118-121,共4页
Journal of Engineering of Heilongjiang University
基金
广东省科技计划项目(2005A20302006)
关键词
PET吹瓶机
单神经元
PID控制器
解耦控制
PET bottle blowing machine
single neuron
PID controller
decoupling control
