基于神经网络的电弧炉电极系统模型参考自适应控制

2006 CES/IEEE 5th International Power Electronics and Motion Control Conference Pub Date : 2006-08-01 DOI:10.1109/IPEMC.2006.4778237

Shi-feng Zhang, Shao-de Zhang, L. Kun, Zheng Xiao

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引用次数: 2

摘要

提出了基于径向基函数神经网络(RBFNN)在线辨识的模型参考自适应控制(MRAC)控制策略，并设计了控制器。针对电弧炉电极系统具有高非线性、时变、不确定性和多变量输入输出耦合的特点。实验结果验证了控制策略的有效性

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Model Reference Adaptive Control based on Neural Network for Electrode System in Electric Arc Furnace

Control strategy of model reference adaptive control (MRAC) based on radial basis function neural network (RBFNN) online identification is proposed, and a controller is also designed. Which in accordance with the characteristics of the electrode system in electric arc furnace as the high nonlinearity, time-variant, uncertainty and multivariable input and output coupling. The validity of control strategy is verified by result of experimentation

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2006 CES/IEEE 5th International Power Electronics and Motion Control Conference

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