基于神经网络模型参考-PID的电阻炉控制系统的应用

以电阻炉为控制对象,针对其所具有的时滞性、非线性、模型结构难以确定等特点,利用神经网络控制技术和常规PID控制方法,将传统控制理论与智能控制理论相结合应用于温度控制的实际工程中。充分利用了神经网络所具有的自学习、自适应和全局逼近的能力特点,构建电阻炉的神经网络参考模型,组成神经网络参考模型PID控制器。运用Matlab软件中的Simulink建立电阻炉温度控制系统的仿真模型,并通过与常规PID控制系统的对比来观测基于神经网络参考模型-PID的电阻炉温控系统的控制效果。仿真结果表明,方案具有满意的动静态特性。

The Application of Resistance Stove Control System Based on Model Reference Controller of Neural Network-PID

This paper considers resistance stove as the modeling object,which have a time lag,nonlinear and uncertain model structure characteristics.In addition,it combined the traditional control theory and intelligent control theory applying in temperature control oof neural networks with self-learning,adaptive and global approximatif the actual projects,by using control techniques with neural networks and conventional PID control methods.Taking full advantage on characteristics of the ability,the writer build the ...