Implementation of an Adaptive Neural Network Identifier for Effective Control of Turbogenerators

Ganesh K. Venayagamoorthy, Missouri University of Science and Technology
Ronald G. Harley

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Abstract

This paper describes an on-line identification technique for modelling a turbogenerator system. The dynamics of a single turbogenerator infinite bus system are modelled using an adaptive artificial neural network identifier (AANNI) based on continual online training (COT). This paper goes further to show that multilayered perceptrons with deviation signals as inputs and outputs trained using the standard backpropagation algorithm retain past learned information despite COT. Simulation and practical results are presented.