DocumentCode
2036818
Title
Least squares estimation of dynamic system parameters using LabVIEW
Author
Turner, Jonathan G. ; Samanta, Biswanath
Author_Institution
Dept. of Mech. & Electr. Eng., Georgia Southern Univ., Statesboro, GA, USA
fYear
2012
fDate
15-18 March 2012
Firstpage
1
Lastpage
4
Abstract
A precursor to control system design is the development of a mathematical model describing the behavior of a system to be controlled. This paper presents the utilization of a least squares technique to determine parameters of a system model using LabVIEW. The effect of noise on accurate determination of the system model parameters is discussed along with the method used to filter noise from the data. The procedure is illustrated using the dynamics of a DC motor. The simulated response of the identified system model is compared with the measured response of the physical plant to validate the identification process.
Keywords
DC motors; control engineering computing; control system synthesis; filtering theory; least squares approximations; machine control; noise; virtual instrumentation; DC motor; LabVIEW; control system design; dynamic system parameter; least squares estimation; least squares technique; mathematical model; noise effect; noise filtering; physical plant; system behavior; system identification; system model parameter; DC motors; Filtering algorithms; Heuristic algorithms; Low pass filters; Mathematical model; Permanent magnet motors; Software algorithms; least squares curve fitting; noise filtering; on-line estimation; system identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Southeastcon, 2012 Proceedings of IEEE
Conference_Location
Orlando, FL
ISSN
1091-0050
Print_ISBN
978-1-4673-1374-2
Type
conf
DOI
10.1109/SECon.2012.6196962
Filename
6196962
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