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

(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
Subjects: Petroleum
Department: College of Computing and Mathematics > Mathematics
Depositing User: Mr. Admin Admin
Date Deposited: 24 Jun 2008 13:19
Last Modified: 01 Nov 2019 14:03
URI: https://eprints.kfupm.edu.sa/id/eprint/14012