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Identification of Continuous-Time Systems with Multiple Unknown Time Delays Using an Output Error Method from Sampled Data

Identification of Continuous-Time Systems with Multiple Unknown Time Delays Using an Output Error... This paper deals with simultaneous identification of continuous systems with multiple unknown time delays from sampled input–output data. In order to estimate, simultaneously, the parameters and the time delays of the system, an output errors method using a nonlinear programming algorithm based on sensitivity functions is discussed. Nevertheless, the initial values of the adjustable parameters should be determined from physical insight or guessed by previous methods. The convergence of the proposed method has been analyzed with theorems and proofs. The simulation example indicates that the proposed algorithm can generate highly accurate parameter estimates. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Circuits, Systems and Signal Processing Springer Journals

Identification of Continuous-Time Systems with Multiple Unknown Time Delays Using an Output Error Method from Sampled Data

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References (26)

Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Engineering; Circuits and Systems; Electrical Engineering; Signal,Image and Speech Processing; Electronics and Microelectronics, Instrumentation
ISSN
0278-081X
eISSN
1531-5878
DOI
10.1007/s00034-017-0588-4
Publisher site
See Article on Publisher Site

Abstract

This paper deals with simultaneous identification of continuous systems with multiple unknown time delays from sampled input–output data. In order to estimate, simultaneously, the parameters and the time delays of the system, an output errors method using a nonlinear programming algorithm based on sensitivity functions is discussed. Nevertheless, the initial values of the adjustable parameters should be determined from physical insight or guessed by previous methods. The convergence of the proposed method has been analyzed with theorems and proofs. The simulation example indicates that the proposed algorithm can generate highly accurate parameter estimates.

Journal

Circuits, Systems and Signal ProcessingSpringer Journals

Published: Jun 19, 2017

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