Title :
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
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;
Conference_Titel :
Electrical and Computer Engineering, 2000 Canadian Conference on
Conference_Location :
Halifax, NS
Print_ISBN :
0-7803-5957-7
DOI :
10.1109/CCECE.2000.849653
