Data compression for estimation of the physical parameters of stable and unstable linear systems

  • Authors:

  • Peter J. Gawthrop;Liuping Wang

  • Affiliations:

  • Centre for Systems and Control and Department of Mechanical Engineering, University of Glasgow, Glasgow G12 8QQ, Scotland;Discipline of Electrical Energy and Control Systems, School of Electrical and Computer Engineering, RMIT University, Melbourne, Victoria 3000, Australia

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2005

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Abstract

A two-stage method for the identification of physical system parameters from experimental data is presented. The first stage compresses the data as an empirical model which encapsulates the data content at frequencies of interest. The second stage then uses data extracted from the empirical model of the first stage within a nonlinear estimation scheme to estimate the unknown physical parameters. Furthermore, the paper proposes use of exponential data weighting in the identification of partially unknown, unstable systems so that they can be treated in the same framework as stable systems. Experimental data are used to demonstrate the efficacy of the proposed approach.