首页> 外文会议>International Conference on Natural Computation;ICNC '09 >The Neural Network Proportion Integral Differential Controller and the Application on Mill Hydraulic Pressure Automatic Gauge Control System
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The Neural Network Proportion Integral Differential Controller and the Application on Mill Hydraulic Pressure Automatic Gauge Control System

机译:神经网络比例积分微分控制器及其在轧机液压自动仪表控制系统中的应用

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This paper presents a neural network proportion integral differential (PID) controller for automatic gauge control (AGC) System of rolling mill, it is an high non-linear and time-varying system. The traditional PID controller has the invariable parameters. However in the actual factory, the environment of the controlled object is often changed. If the three parameters of PID controller canȁ9;t adjusted adaptively, the controller will have a badly control effect. The neural network can adjust the three parameter based on the control error. If the control error becomes zero, the parameter didnȁ9;t adjust too. The simulation shows that neural network PID controller has good dynamic quality. The control system has short response time, small over modulation, highly steady state behavior and robustness comparing with the traditional PID controller.
机译:本文提出了一种用于轧机自动仪表控制(AGC)系统的神经网络比例积分微分(PID)控制器,它是一种高度非线性且时变的系统。传统的PID控制器具有不变的参数。但是,在实际工厂中,经常改变受控对象的环境。如果PID控制器的三个参数不能自适应地调整为9,则控制效果将很差。神经网络可以基于控制误差来调整这三个参数。如果控制误差为零,则该参数也不会调整为9。仿真表明,神经网络PID控制器具有良好的动态质量。与传统的PID控制器相比,该控制系统响应时间短,过调制小,稳态行为高且具有鲁棒性。

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