Title :
Synchronous generator control combining sliding modes and neural networks
Author :
Felix, Ramon A. ; Sanchez, Edgar N. ; Loukianov, Alexander G.
Author_Institution :
CINVESTAV, Mexico City, Mexico
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.
Keywords :
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; Feedforward neural networks; Neural networks; Output feedback; Power system modeling; Power system reliability; Power system simulation; Power transmission lines; Sliding mode control; State feedback; Synchronous generators;
Conference_Titel :
American Control Conference, 2003. Proceedings of the 2003
Print_ISBN :
0-7803-7896-2
DOI :
10.1109/ACC.2003.1240472
