State-Space Model Identification of Tandem Cold Mill Based on Subspace Method

Title & Authors
State-Space Model Identification of Tandem Cold Mill Based on Subspace Method
Kim, In-Su; Hwang, Lee-Cheol; Lee, Man-Hyeong;

Abstract
In this paper, we study on the identification of discrete-time state-space model for robust control of tandem cold mill, using a MOESP(MIMO output-error state-space model identification) algorithm based on subspace method. It is shown that the identified model is well adapted to input-output data sets, which are obtained from nonlinear mathematical equations of tandem cold mill. Furthermore, deterministic H$\small{\infty}$ norm bounds on uncertainties including modeling errors and disturbances are quantitatively identified in the frequency domain. Finally, the results give a basic idea to determine weighting functions included in formulating some robust control problems of tandem cold mill
Keywords
System Identification;MOESP Algorithm;Tandem Cold Mill;Robust Control;Uncertainty;
Language
Korean
Cited by
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