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
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;
Conference_Titel :
Southeastcon, 2012 Proceedings of IEEE
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-1374-2
DOI :
10.1109/SECon.2012.6196962
