Design of a neural adaptive power system stabilizer using dynamic back-propagation method

A neural adaptive power system stabilizer (NAPSS) is described in this pape r. The proposed structure consists of a neuro-identifier to track and ident ify the nonlinear plant in real-time, and a neuro-controller to damp the po wer plant oscillations. These two subnetworks are trained in an online mode utilizing the dynamic back-propagation method. The performance and effecti veness of the proposed controller are demonstrated by simulation studies fo r a variety of operating conditions and disturbances. (C) 1999 Published by Elsevier Science Ltd. All rights reserved.