基于RBF逆动态辨识控制方案在钢包炉电极系统中的应用

Shao-de Zhang, Xiao Zheng
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引用次数: 2

摘要

将基于最近邻聚类算法的RBF神经网络(RBFN)应用于钢包炉三相电极系统。实现了低频三相电极系统的实时在线反辨识和间接解耦。本文采用逆辨识模型作为逆控制模型。设计了基于RBFN和PD控制的逆控制方案,并将其成功应用于马鞍山第三炼钢厂LF电极系统。
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 The Control Scheme based on RBF Inverse Dynamic Identification in Electrode System of Ladle Furnace
RBF neural network ( RBFN ) based on nearest neighbor clustering algorithm is applied for three phase electrode system in Ladle Furnace ( LF ). Real time on line inverse identification and indirect decoupling of LF three phase electrode system is realized. Hereon, the inverse identification model is applied as inverse control model. The scheme of inverse control based on RBFN and PD control is designed, which is applied to LF electrode system successfully in third iron steel plant of Maanshan P.R.China.
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