Title :
Inverse optimal neural control with speed gradient for a power electric system with changes in loads
Author :
Lastire, E.A. ; Alanis, Alma Y. ; Sanchez, Edgar N.
Author_Institution :
CINVESTAV, Unidad Guadalajara, Jalisco, Mexico
Abstract :
In this paper an inverse optimal neural controller with speed gradient (SG) for discrete-time unknown nonlinear systems, in presence of external disturbances and parameter uncertainties is presented. It is based on a discrete-time recurrent high order neural network (RHONN) trained with an extended Kalman filter (EKF)-based algorithm. A reduced neural model for synchronous machine is proposed for the stabilization of nine bus system in the presence of a fault in a line of transmission with some variations in loads.
Keywords :
Kalman filters; angular velocity control; discrete time systems; gradient methods; machine control; neurocontrollers; nonlinear control systems; optimal control; reduced order systems; stability; synchronous machines; uncertain systems; EKF; RHONN; SG; discrete-time recurrent high order neural network; discrete-time unknown nonlinear systems; extended Kalman filter-based algorithm; external disturbances; inverse optimal neural control; load changes; nine bus system stabilization; parameter uncertainties; power electric system; reduced neural model; speed gradient; synchronous machine; Equations; Kalman filters; Neural networks; Optimal control; Synchronous generators; Training; Extended Kalman filter; High-order neural network; Optimal control; Synchronous generators;
Conference_Titel :
Electrical Engineering, Computing Science and Automatic Control (CCE), 2012 9th International Conference on
Conference_Location :
Mexico City
Print_ISBN :
978-1-4673-2170-9
DOI :
10.1109/ICEEE.2012.6421116
