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

부분공간법을 이용한 연속 냉간압연기의 상태공간모델 규명

  • Published : 2000.02.01


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$\infty$ 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.


System Identification;MOESP Algorithm;Tandem Cold Mill;Robust Control;Uncertainty


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