A New Modeling Method of Control Systems Based on Pattern Recognition

被引:0
|
作者
Xu, Zhengguang [1 ]
Wang, Mushu [1 ]
机构
[1] Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing, Peoples R China
来源
2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) | 2016年
基金
中国国家自然科学基金;
关键词
pattern recognition; system modeling; k-means clustering; conditional entropy; IDENTIFICATION;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
For many industrial production processes obeying certain statistical laws, a new method of establishing a SISO control model is put forward based on pattern recognition technology. Firstly, k-means clustering algorithm is used to partition input and output data collected into several classes respectively. Secondly, the distance between two classes is described by the distance of the two class centers. Then the mapping relationship between input and output of the control model is established based on pattern classification technology. And input and output orders of the model are identified by conditional entropy. Lastly experimental results illustrate the feasibility of the modeling method using the data collected from an actual industrial process.
引用
收藏
页码:80 / 85
页数:6
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