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Estimation and Identification of Mass-Spring-Dashpot Systems Using Multiple-Model Adaptive Algorithms

[+] Author Affiliations
Sajjad Fekri Asl, Michael Athans, Antonio Pascoal

Instituto Superior Técnico, Lisboa, Portugal

Paper No. IMECE2002-33442, pp. 499-506; 8 pages
  • ASME 2002 International Mechanical Engineering Congress and Exposition
  • Dynamic Systems and Control
  • New Orleans, Louisiana, USA, November 17–22, 2002
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 0-7918-3629-0 | eISBN: 0-7918-1691-5, 0-7918-1692-3, 0-7918-1693-1
  • Copyright © 2002 by ASME


We present performance evaluations of different configuration for state estimation and identification of a complex Mass-Spring-Dashpot (MSD) system using Multiple-Model Adaptive Estimation (MMAE) algorithms. The algorithms compare two distinct MMAE strategies using either constant-gain or time-varying-gain Kalman filters to identify the correct model of the MSD system. Simulation results, for a variety of noisy measurement assumptions, illustrate the behaviour of the MMAE algorithms which are robust to mass uncertainties.

Copyright © 2002 by ASME



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