• 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