基于模糊神经网络的火电机组广义预测控制算法

Wei Sun, Hujun Ling
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引用次数: 0

摘要

现代电力过程是典型的复杂工业过程,具有多变量非线性、长时滞、时变等特点,难以建立精确的模型。因此,采用常规的控制策略难以达到系统运行的最佳效果。在广义预测控制策略中,利用具有动态特征的FNN网络对协调控制系统进行辨识,建立预测模型,实现了在线滚动优化和实时反馈修正的预测控制。将该方法与传统的PID控制方法进行了比较,仿真结果表明,该方法能够适应对象的变化特性。该方法具有良好的控制效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generalized Predictive Control Algorithm Applied to Thermal Power Units Based on Fuzzy Neural Network
Mordern electric power process is a typical complex industy course which is multivariable nonlinear,long-time delay ,time-variant and difficult to be established accurate model. So it is hard to get optimum effect when system operating with conventional control strategy.A FNN network with dynamic feature has been used to identify the coordinated control system for establishing a predictive model in Generalized predictive control strategy, and a predictive control has been achieved with online rolling optimization and real-time feedback revision in the paper. This method was compared with conventional PID control method,the simulation result shows that this method can adapt the object change characteristic.This method has a good control effect.
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