The Identification of Nonlinear Nondynamic Systems With Application to a Hot Steel Rolling Mill
Abstract
The problem of obtaining information about the structure of an unknown nonlinear system is considered. An algorithm is presented for identifying the structure of a nonlinear system with a set of possible candidates for the model of the system as a priori information. It is shown that for certain categories of functions the algorithm may select a suboptimal model. A detailed analysis of this selection error is presented along with a method for assigning a probability to the occurrence of this error. This identification algorithm is then used to derive setup models for the finishing stands in a hot steel rolling mill. Comparisons are made with the method of least squares which illustrate that the proposed method can be used to obtain a simpler, yet equally effective model. Also, the parameter identification problem is considered along with several methods for on line control of roll force prediction.
Degree
Ph.D.
Subject Area
Electrical engineering
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