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Proceedings of the 14th Mediterranean Conference on Control and Automation (2006)
Ancona
June 28, 2006 to June 30, 2006
ISBN: 0-9786720-1-1
pp: 1-6
Fotis P. Kopsaftopoulos , Stochastic Mechanical Systems & Automation (SMSA) Group, Department of Mechanical & Aeronautical Engineering, University of Patras, GR 26500, Patras, Greece. Tel/fax: +30 2610 997 405. E-mail: fkopsaf@mech.upatras.gr, Internet: http://www.mech.upatras.gr/~sms
Spilios D. Fassois , Stochastic Mechanical Systems & Automation (SMSA) Group, Department of Mechanical & Aeronautical Engineering, University of Patras, GR 26500, Patras, Greece. Tel/fax: +30 2610 997 405. E-mail: fassois@mech.upatras.gr, Internet: http://www.mech.upatras.gr/~sms
ABSTRACT
The problem of identifying stochastic systems under multiple operating conditions, by using excitation-response signals obtained from each condition, is addressed. Each operating condition is characterized by several measurable variables forming a vector operating parameter. The problem is tackled within a novel framework consisting of postulated vector dependent functionally pooled ARX (VFP-ARX) models, proper data pooling techniques, and statistical parameter estimation. Least squares (LS) and maximum likelihood (ML) estimation methods are developed. Their strong consistency is established and their performance characteristics are assessed via a Monte Carlo study
INDEX TERMS
autoregressive processes, least mean squares methods, maximum likelihood estimation, Monte Carlo methods, stochastic systems, vectors
CITATION

F. P. Kopsaftopoulos and S. D. Fassois, "Identification of Stochastic Systems Under Multiple Operating Conditions: The Vector Dependent FP-ARX Parametrization," Mediterranean Conference on Control and Automation(MED), Ancona, 2009, pp. 1-6.
doi:10.1109/MED.2006.328813
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