Title :
Estimation of the electrical parameters of an induction motor with the TLS EXIN neuron
Author :
Cirrincione, Maurizio ; Pucci, Marcello ; Cirrincione, Giansalvo
Author_Institution :
Centro Ricerche Sistemi Elettrici di Potenza, C.N.R, Palermo, Italy
fDate :
6/24/1905 12:00:00 AM
Abstract :
This paper presents the solution for the on-line identification of an induction motor by using the total least-squares (TLS) algorithm. In particular the TLS EXIN neuron has been employed as it is the only algorithm which solves for the TLS problem in a simple recursive way. The results thus obtained are compared with those obtained with an OLS (ordinary least-square) algorithm to show the substantial equivalence of the two techniques if no noise is present in the measurements. This is the first step for facing up to the estimation of electrical parameters of induction machines in noisy environments (EMC problems), for example in industrial environments.
Keywords :
electric machine analysis computing; electromagnetic compatibility; electromagnetic interference; induction motors; least squares approximations; neural nets; recursive estimation; EMC problems; OLS algorithm; TLS EXIN neuron; algorithm equivalence; electrical parameters estimation; induction motor; industrial environments; noise; noisy environments; on-line identification; ordinary least-square algorithm; total least-squares algorithm; Electromagnetic compatibility; Equations; Induction machines; Induction motors; Neurons; Parameter estimation; Rotors; Signal processing algorithms; Stators; Working environment noise;
Conference_Titel :
Devices, Circuits and Systems, 2002. Proceedings of the Fourth IEEE International Caracas Conference on
Print_ISBN :
0-7803-7380-4
DOI :
10.1109/ICCDCS.2002.1004091
