RBF神经网络PID控制器在精馏塔温度控制系统中的应用

Y. Zhang, Chao-ying Liu, Xue-ling Song, Zhifei Yan
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引用次数: 4

摘要

精馏塔温度控制是精馏过程控制系统的重要组成部分。针对精馏塔温度控制系统的时滞和参数时变特性,结合传统PID控制和神经网络径向基函数(RBF)的优点,提出了神经网络自整定PID控制器方法。仿真实验结果表明,RBF神经网络PID控制器取得了较好的控制效果,验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of RBF Neural Network PID Controller in the Rectification Column Temperature Control System
The temperature control of the rectification column is an important part of distillation process control system. For the time-delay and parameter time-varying characteristics in rectification column temperature control system, it puts forward neural network self-tuning PID controller method which combines the advantages of traditional PID control and neural network radial basis function (RBF). From the simulation experiment results it shows that RBF neural network PID controller gets much better control effect, and it verifies the effectiveness of the proposed method.
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