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钢包精炼炉的电极系统智能建模及控制
引用本文:张绍德. 钢包精炼炉的电极系统智能建模及控制[J]. 工程科学学报, 2004, 26(1): 82-85. DOI: 10.13374/j.issn1001-053x.2004.01.022
作者姓名:张绍德
作者单位:1.安徽工业大学电气信息学院, 马鞍山 243002
摘    要:针对钢包精炼炉电极控制系统具有非线性、时变、模型不确定、大滞后、多输入多输出耦合的特点,提出一种基于神经网络实时在线辩识的内模控制方案.控制器采用神经网络解耦,将混沌机制引入到BP算法中,用以加快学习的收敛速度.仿真结果证实了控制策略的有效性.

关 键 词:钢包精炼炉  神经网络内模控制  神经网络解耦  混沌机制
收稿时间:2003-06-18

Intelligent Modeling and Control Strategy for the Electrode System in Ladle Furnance
ZHANG Shaode. Intelligent Modeling and Control Strategy for the Electrode System in Ladle Furnance[J]. Chinese Journal of Engineering, 2004, 26(1): 82-85. DOI: 10.13374/j.issn1001-053x.2004.01.022
Authors:ZHANG Shaode
Affiliation:1.Electrical Engineering and Information School, Anhui Uninversity of Technology, Mananshan 243002, China
Abstract:In accordance with such characters of the electrode control system in ladle furnace as the high non-linearity, time-variant, uncertainty of the model, output response time delay serious, and multivariable input and output coupling, an internal model control strategy based on real-time identification on line by neural network was presented. The control strategy applies neural network decoupline control and the chaos algorithm to the improved BP algorithm and speeds up the training of neural network. The validity of the control strategy is verified by simulation analysis.
Keywords:ladle furnace  neural network internal model control  neural network decoupling  chaos system
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