神经网络PID工业温度控制系统研究  

Study of Neural Network PID Industrial Temperature Control System

作　　者：李强[1] 刘承志[1] 张薇[1] 

机构地区：[1]西南交通大学电气工程学院,四川成都610031

出　　处：《自动化信息》2009年第5期37-39,共3页Automation Information

摘　　要：本文介绍了一种神经网络PID控制器，并将它与传统PID控制器、模糊控制器和神经网络控制器进行比较。神经网络PID控制器综合了PID控制器和神经网络控制器的优点并弥补了它们各自的不足之处。通过上述各种控制器在工业温度控制系统的仿真研究表明，神经网络PID控制器具有超调小，过度时间短，控制精度高的优点，对大滞后的温度控制系统有很好的控制效果。A neural network PID controller is introduced in this paper and compared it with the traditional PID controller, fuzzy controller and neural network controller. Neural network PID controller integrates the advantages of PID controller and neural network controller, thus making up the deficiencies of the two. Through a variety of controller＇s simulation studies in the industrial temperature control system, it has shown that the neural network PID controller has the merits of small overshoot, short transient time, higher control accuracy, and a very good effect on the large lag temperature control system.

关 键 词：BP神经网络 PID控制器 模糊控制 温度控制 

分 类 号：TM571[电气工程—电器]