基于模糊神经网络的温度控制系统设计  

The Design of Temperature Control System Based on Fuzzy Neural Network

作　　者：李成利[1] 黄存柱[1] 苗建[1] 

机构地区：[1]青岛科技大学自动化与电子工程学院,青岛266042

出　　处：《微计算机信息》2010年第7期75-76,98,共3页Control & Automation

摘　　要：实验室温度控制系统要求精度高,并且具有非线性、大惯性及数学模型难建立等特性,这使得用常规PID控制器以及一般模糊控制器无法很好地满足系统要求,而本文在一般模糊控制器的基础上,融合神经网络技术,设计出模糊神经网络控制器,它既有模糊控制鲁棒性好、动态响应好、上升时间快、超调小的优点,又具有神经网络的在线自学习能力,可以实现温度的智能控制,在实际应用中取得良好的效果。The system accuracy of laboratory temperature control has high request,and temperature control system has nonlinear,big delay and difficult establishment characteristic of mathematics model,etc.Normal PID controller and normal fuzzy controller cannot satisfy system require perfectly.So in this paper,using neural network technology,a fuzzy neural network controller is introducd,which is based on normal fuzzy controller.It not only can exert fuzzy control characteristics such as high robustness,good dynamic response,short rising time,small surplus,but also it can exert the neural network＇s online self-learning ability.It can realize the intelligent control of temperature,and it is taken into implication in practice and gets preferable control effect.

关 键 词：温度控制系统 模糊神经网络控制 智能控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]