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Identification of errors-in-variables model with observation outliers based on Minimum-Covariance-Determinant

ALMutawa, J. (2007) Identification of errors-in-variables model with observation outliers based on Minimum-Covariance-Determinant. American Control Conference, 2007. ACC '07, 1.

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Abstract

In this paper, we develop a subspace system identification algorithm for the errors-in-variables (EIV) model subject to observation noise with outliers. By using the minimum covariance determinant (MCD), we identify and delete the outliers, and then apply the classical EIV subspace system identification algorithms to get state space models. In order to solve the MCD problem for the EIV model we propose a random search algorithm. The proposed algorithm has been applied to a heat exchanger data.



Item Type:Article
Date:July 2007
Date Type:Publication
Subjects:Petroleum
Divisions:College Of Sciences > Mathematical Science Dept
Creators:ALMutawa, J.
Email:jaafarm@kfupm.edu.sa
ID Code:14012
Deposited By:KFUPM ePrints Admin
Deposited On:24 Jun 2008 16:19
Last Modified:12 Apr 2011 13:14

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