Paper Info
Title
Synchronous generator control combining sliding modes and neural networks
Abstract
In this paper, we present a novel approach to control a single generator connected to a finite bus. Modifying published results for nonlinear identification using current neural networks, a triangular neural identifier is proposed. Based on this model a new control law, which combines sliding modes and state feedback linearization is derived. This new neural identifier and the proposed control law allows to reject external disturbances caused by generator terminal short circuits. Applicability of the approach is tested via simulations.
Year
DOI
Venue
2003
10.1109/ACC.2003.1240472
American Control Conference, 2003. Proceedings of the 2003
Keywords
DocType
Volume
adaptive control,identification,neurocontrollers,power system control,state feedback,synchronous generators,variable structure systems,adaptive indirect control,electro-mechanical systems,external disturbances,generator terminal short circuits,infinite bus,neural networks,nonlinear identification,power energy,recurrent neural networks,sliding modes,state feedback linearization,synchronous generator control,triangular neural identifier,synchronous generator,neural network,feedforward neural networks,power system simulation,sliding mode control,mechanical systems,power transmission lines
Conference
5
ISSN
ISBN
Citations 
0743-1619
0-7803-7896-2
0
PageRank 
References 
Authors
0.34
5
3
Name
Order
Citations
PageRank
Felix, R.A.100.34
Sanchez, Edgar N.2789.09
Loukianov, Alexander G.33010.04