Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
9652062 | International Journal of Electrical Power & Energy Systems | 2005 | 8 Pages |
Abstract
Application of wavelet networks for the identification of a synchronous generator is described in this paper. Parameter adaptation laws are used to track the variations in the parameters, following changes in the generator operating conditions. The adaptation laws have been developed using a Lyapunov function. This guarantees the stability of the identification algorithm and also ensures the convergence of parameters and variables. The proposed method has been tested on a synchronous machine. Experimental results show good accuracy of the identified model and robustness of the algorithm following severe changes in the operating conditions.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
M. Karrari, O.P. Malik,