A New Modeling Method of Control Systems Based on Pattern Recognition

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.