Comparison of the speed estimation by an adaptive observer and by a dynamic neural network observer for an asynchronous machine

Author

Ghouili, J. ; Chériti, A.

Author_Institution

Dept. de Genie Electr. et Genie Inf., Quebec Univ., Trois-Rivieres, Que., Canada

Volume

2

fYear

2000

fDate

2000

Firstpage

1197

Abstract

The article compares and characterises two nonlinear state observers for estimating the rotation speed of an asynchronous machine. The first is a deterministic adaptive observer based on dynamic modelling. The second is a dynamic neural net observer. A comparison is made of the dynamics, the convergence, the stability, the robustness and the ease of implementation of each observer. Finally, the simulations obtained with an asynchronous machine are presented in support of this comparative study

Keywords

electric machine analysis computing; machine theory; neural nets; observers; parameter estimation; squirrel cage motors; adaptive observer; asynchronous machine; deterministic adaptive observer; dynamic modelling; dynamic neural net observer; dynamic neural network observer; nonlinear state observers; robustness; rotation speed estimation; speed estimation; squirrel cage machine; stability; Asymptotic stability; Convergence; Electrical capacitance tomography; Resumes; Robust stability; Robustness; Stators;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2000 Canadian Conference on

Conference_Location

Halifax, NS

ISSN

0840-7789

Print_ISBN

0-7803-5957-7

Type

conf

DOI

10.1109/CCECE.2000.849653

Filename

849653