Parameters identification with the multiple model adaptive estimation (MMAE) algorithm

  • Authors:

  • João C. Martins

  • Affiliations:

  • Escola Superior de Tecnologia e Gestão/INESC-ID, Instituto Politécnico de Beja, Beja, Portugal

  • Venue:
  • MIC'06 Proceedings of the 25th IASTED international conference on Modeling, indentification, and control
  • Year:
  • 2006

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Abstract

The performance of the Multiple-Model Adaptive Estimation (MMAE)in the identification of the parameters of a physical system using different noise scenarios is reported in this paper. The experiments target a second order mechanical system, representative of the physical systems appearing in many engineering situations. The MMAE algorithm performance is evaluated using the steady-state and time-varying form of the Kalman filters used by it. Then, a recursive algorithm for the re-discretization of the unknown parameters, in order to obtain an approximation of the true parameter when none of the models matches the system, is presented and its results reported for the steady-state case.