Discrete-Time Backstepping Neural Control for Synchronous Generators

Author

Alanis, Alma Y. ; Sanchez, Edgar N. ; Loukianov, Alexander G.

Author_Institution

CINVESTAV, Unidad Guadalajara, Guadalajara

fYear

2007

fDate

12-17 Aug. 2007

Firstpage

2569

Lastpage

2574

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2007. IJCNN 2007. International Joint Conference on

Conference_Location

Orlando, FL

ISSN

1098-7576

Print_ISBN

978-1-4244-1379-9

Electronic_ISBN

1098-7576

Type

conf

DOI

10.1109/IJCNN.2007.4371363

Filename

4371363