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Method for estimation of continuous-time models of linear time-invariant systems via the bilinear transform

In this thesis, we develop a technique which is capable of identifying and rejecting the sampling zeros for continuous-time linear time-invariant systems. The method makes use of the MOESP family of identification algorithms (59), (60), (61), (62) to obtain a discrete-time model of the system. Since, the structure and parameters of discrete-time models are difficult to relate to the underlying continuous-time system of interest it is necessary to compute the continuous-time equivalent from the discrete-time model. The bilinear transform (19), (54) does this effectively but also converts extraneous system zeros (the so-called process or sampling zeros) to the continuous-time model. Here, we present an approach to distinguish which of the system zeros are due to sampling effects and which are truly part of the model's dynamics. Dropping sampling zeros yields an accurate description of the system under test. Digital simulations demonstrate that this method is robust in the presence of measurement noise. Moreover, series of experiments performed on a known, physical, linear system validate the simulation results. Finally, an investigation of the passive dynamics of the ankle was used to demonstrate the applicability of this method to a physiological system.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.27486
Date January 1996
CreatorsKukreja, Sunil L.
ContributorsKearney, R. E. (advisor), Galiana, H. L. (advisor)
PublisherMcGill University
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Formatapplication/pdf
CoverageMaster of Engineering (Department of Biomedical Engineering.)
RightsAll items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated.
Relationalephsysno: 001548842, proquestno: MQ29861, Theses scanned by UMI/ProQuest.

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