Detail publikačního výsledku

Comparison of different approaches to continuous-time system identification from sampled data

TŮMA, M.; JURA, P.

Originální název

Comparison of different approaches to continuous-time system identification from sampled data

Anglický název

Comparison of different approaches to continuous-time system identification from sampled data

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

This article deals with different approaches to continuous-time system identification from sampled data. Continuous-time system identification is important problem in control theory. Continuous time models provide many advantages against discrete time models because of better physical insight into the system properties. The traditional approach with least squares method with state variable filters is presented. Two alternative approaches to continuous-time identification are proposed. The generalized Laguerre functions method and the method based on least squares estimation with numerical solution of differential equation are introduced. These three different approaches to continuous-time system identification from sampled data are compared on the example. It is shown that proposed alternative methods can give better results in terms of relative root mean square error of the outputs of the identified systems than the least squares method with state variable filters.

Anglický abstrakt

This article deals with different approaches to continuous-time system identification from sampled data. Continuous-time system identification is important problem in control theory. Continuous time models provide many advantages against discrete time models because of better physical insight into the system properties. The traditional approach with least squares method with state variable filters is presented. Two alternative approaches to continuous-time identification are proposed. The generalized Laguerre functions method and the method based on least squares estimation with numerical solution of differential equation are introduced. These three different approaches to continuous-time system identification from sampled data are compared on the example. It is shown that proposed alternative methods can give better results in terms of relative root mean square error of the outputs of the identified systems than the least squares method with state variable filters.

Klíčová slova

generalized Laguerre function, continuous-time LTI system, numerical integration, identification

Klíčová slova v angličtině

generalized Laguerre function, continuous-time LTI system, numerical integration, identification

Autoři

TŮMA, M.; JURA, P.

Rok RIV

2019

Vydáno

17.11.2017

ISBN

978-1-5386-2085-4

Kniha

2017 European Conference on Electrical Engineering and Computer Science (EECS) (2017)

Strany od

61

Strany do

65

Strany počet

5

BibTex

@inproceedings{BUT150205,
  author="Martin {Tůma} and Pavel {Jura}",
  title="Comparison of different approaches to continuous-time system identification from sampled data",
  booktitle="2017 European Conference on Electrical Engineering and Computer Science (EECS) (2017)",
  year="2017",
  pages="61--65",
  doi="10.1109/EECS.2017.21",
  isbn="978-1-5386-2085-4"
}