Inverse Optimal Control with Speed Gradient for a Power Electric System Using a Neural Reduced Model. (16th March 2014)

• Record Type: Journal Article
• Authors: Alanis, Alma Y.; Lastire, Enrique A.; Arana-Daniel, Nancy; Lopez-Franco, Carlos
• Other Names: Karimi Hamid R. Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2014(2014)
• Publication Date: 2014-03-16
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2014/514608
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : This paper presented an inverse optimal neural controller with speed gradient (SG) for discrete-time unknown nonlinear systems in the presence of external disturbances and parameter uncertainties, for a power electric system with different types of faults in the transmission lines including load variations. It is based on a discrete-time recurrent high order neural network (RHONN) trained with an extended Kalman filter (EKF) based algorithm. It is well known that electric power grids are considered as complex systems due to their interconections and number of state variables; then, in this paper, a reduced neural model for synchronous machine is proposed for the stabilization of nine bus system in the presence of a fault in three different cases in the lines of transmission.