DocumentCode
114895
Title
Ensuring stability in continuous time system identification instrumental variable method for over-parameterized models
Author
Huong Ha ; Welsh, James S.
Author_Institution
Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Newcastle, NSW, Australia
fYear
2014
fDate
15-17 Dec. 2014
Firstpage
2597
Lastpage
2602
Abstract
The aim of this paper is to develop constraints to ensure stability of the model in the continuous time, simplified refined instrumental variable system identification algorithm (SRIVC) for over-parameterized models. Specifically, a convex stability domain in the space of polynomial coefficients will be generated and the system parameters will be estimated within this domain. It is found that the model fit obtained using the proposed method offers an improvement to the typical SRIVC method. A Monte Carlo simulation is presented to illustrate the performance of the proposed approach.
Keywords
Monte Carlo methods; continuous time systems; convex programming; identification; polynomials; stability; Monte Carlo simulation; SRIVC; continuous time system identification; convex stability domain; instrumental variable method; over-parameterized model; polynomial coefficient; simplified refined instrumental variable system identification algorithm; system parameter; Instruments; Poles and zeros; Polynomials; Signal to noise ratio; Stability criteria; Continuous time identification; instrumental variable methods; least squares;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
Conference_Location
Los Angeles, CA
Print_ISBN
978-1-4799-7746-8
Type
conf
DOI
10.1109/CDC.2014.7039786
Filename
7039786
Link To Document