Title: Incorporation of system steady state properties into subspace identification algorithm

Authors: Samuel Prívara; Jiří Cigler; Zdeněk Váňa; Lukáš Ferkl

Addresses: Department of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Karlovo námĕstí 13, Czech Republic. ' Department of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Karlovo námĕstí 13, Czech Republic. ' Department of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Karlovo námĕstí 13, Czech Republic. ' Department of Control Engineering, Faculty of Electrical Engineering, Czech Technical University in Prague, Karlovo námĕstí 13, Czech Republic.

Abstract: Most of the industrial applications are multiple-input multiple-output (MIMO) systems that can be identified using the knowledge of the system's physics or from measured data employing statistical methods. Currently, there is the only class of statistical identification methods capable of handling the issue of the vast MIMO systems – subspace identification methods. These methods, however, as all the statistical methods, need data of a certain quality, i.e., excitation of the corresponding order, no data corruption, etc. Nevertheless, combination of the statistical methods and a physical knowledge of the system could significantly improve system identification. This paper presents a new algorithm which provides remedy to the insufficient data quality of a certain kind through incorporation of the prior information, namely a known static gain and an input-output feed-through. The presented algorithm naturally extends classical subspace identification algorithms, that is, it adds extra equations into the computation of the system matrices. The performance of the algorithm is shown on a case study and compared to the current methods, where the model is used for an MPC control of a large building heating system.

Keywords: subspace identification; prior information; steady state properties; MPC; model predictive control; building heating systems.

DOI: 10.1504/IJMIC.2012.047123

International Journal of Modelling, Identification and Control, 2012 Vol.16 No.2, pp.159 - 167

Published online: 31 May 2012 *

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