Title :
Parameter estimation of stochastic linear systems subject to colored noise
Author_Institution :
Sch. of Quantitative Methods & Math. Sci., Univ. of Western Sydney, NSW, Australia
Abstract :
In this paper, a generalized version of the bias-eliminated least-squares (BELS) method is developed for the purpose of unbiased estimation of the system transfer function, without parametric modelling of the process disturbance acting on the system. Three weighting matrices are introduced to construct a new composite signal in terms of the delayed system inputs and the delayed system outputs. Identification of the corresponding new model provides an estimate of the colored-noise-induced bias, which is then removed from the least-squares parameter estimate. It is shown that several existing BELS-based methods are a special case of the developed method if the three weighting matrices are properly selected. The interplay between the developed method and the instrumental variables methods is also studied
Keywords :
delays; least squares approximations; linear systems; parameter estimation; random noise; stochastic systems; transfer function matrices; BELS method; bias-eliminated least squares method; colored noise-induced bias; composite signal construction; delayed system inputs; delayed system outputs; instrumental variables methods; model identification; parameter estimation; process disturbance; stochastic linear systems; unbiased system transfer function estimation; weighting matrices; Colored noise; Delay systems; Instruments; Linear systems; Parameter estimation; Parametric statistics; Size control; Stochastic resonance; Stochastic systems; Transfer functions;
Conference_Titel :
Decision and Control, 2001. Proceedings of the 40th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-7061-9
DOI :
10.1109/.2001.980643