DocumentCode :
2570317
Title :
Multivariable frequency domain identification using IV-based linear regression
Author :
Blom, Rogier S. ; Van den Hof, Paul M J
Author_Institution :
Precision & Microsyst. Eng., Delft Univ. of Technol., Delft, Netherlands
fYear :
2010
fDate :
15-17 Dec. 2010
Firstpage :
1148
Lastpage :
1153
Abstract :
Identification of output error models from frequency domain data generally results in a non-convex optimization problem. A well-known method to approach the output error minimum by iterative linear regression steps was formulated by Sanathanan and Koerner. A disadvantage of this approach is that in general convergence of the iterations only implies optimality under restrictive conditions. In the literature, an alternative iterative linear regression procedure is available, which ensures optimality upon convergence, also in case of undermodeling. This algorithm is known for time-domain identification as the Simplified Refined Instrumental Variable method (SRIV), and was recently formulated for frequency domain identification of SISO output error models. Here we generalize this formulation to MIMO identification of models in matrix fraction description. The effectiveness of the approach is demonstrated by its application to estimation of a parametric model of the multivariable dynamics of a spindle with Active Magnetic Bearings.
Keywords :
MIMO systems; concave programming; frequency-domain analysis; identification; iterative methods; linear systems; machine bearings; machine tool spindles; matrix algebra; multivariable control systems; optimal control; regression analysis; IV-based linear regression; MIMO identification; SISO output error model; active magnetic bearing; iterative linear regression; matrix fraction description; multivariable dynamics; multivariable frequency domain identification; nonconvex optimization; optimality; simplified refined instrumental variable method; spindle; time domain identification; Convergence; Cost function; Data models; Iterative algorithm; Linear regression; MIMO; Polynomials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
ISSN :
0743-1546
Print_ISBN :
978-1-4244-7745-6
Type :
conf
DOI :
10.1109/CDC.2010.5717297
Filename :
5717297
Link To Document :
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