Title :
Discrete-Time Backstepping Neural Control for Synchronous Generators
Author :
Alanis, Alma Y. ; Sanchez, Edgar N. ; Loukianov, Alexander G.
Author_Institution :
CINVESTAV, Unidad Guadalajara, Guadalajara
Abstract :
This paper deals with adaptive tracking for discrete-time MIMO nonlinear systems in presence of bounded disturbances. In this paper, a high order neural network structure is used to approximate a control law designed by the backstepping technique, applied to a block strict feedback form (BSFF). The learning algorithm for the HONN is based on an extended Kalman filter (EKF). This paper also includes the respective stability analysis, using the Lyapunov approach. The viability of the proposed approach is tested via simulations, by its application to synchronous generators control.
Keywords :
Kalman filters; Lyapunov methods; MIMO systems; discrete time systems; neurocontrollers; nonlinear control systems; stability; synchronous generators; Lyapunov approach; block strict feedback form; discrete-time MIMO nonlinear system; discrete-time backstepping neural control; extended Kalman filter; learning algorithm; stability analysis; synchronous generator; Adaptive control; Backstepping; Control systems; Neural networks; Neurofeedback; Nonlinear control systems; Nonlinear systems; Programmable control; Recurrent neural networks; Synchronous generators;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4371363
