Title :
Identification of Stochastic Systems Under Multiple Operating Conditions: The Vector Dependent FP-ARX Parametrization
Author :
Kopsaftopoulos, Fotis P. ; Fassois, Spilios D.
Author_Institution :
Dept. of Mech. & Aeronaut. Eng., Patras Univ.
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
Keywords :
Monte Carlo methods; autoregressive processes; least mean squares methods; maximum likelihood estimation; stochastic systems; vectors; Monte Carlo method; data pooling technique; excitation-response signal; least square method; maximum likelihood estimation; multiple operating condition; statistical parameter estimation; stochastic system identification; vector dependent functionally pooled ARX parametrization model; vector operating parameter; Aerospace materials; Humidity; Least squares approximation; Mathematical model; Maximum likelihood estimation; Mechanical systems; Parameter estimation; Signal processing; Stochastic systems; Temperature;
Conference_Titel :
Control and Automation, 2006. MED '06. 14th Mediterranean Conference on
Conference_Location :
Ancona
Print_ISBN :
0-9786720-1-1
Electronic_ISBN :
0-9786720-0-3
DOI :
10.1109/MED.2006.328813
