Comparison of MLP and RBF Neural Networks Using Deviation Signals for Indirect Adaptive Control of a Synchronous Generator

Jung-Wook Park
Ganesh K. Venayagamoorthy, Missouri University of Science and Technology
Ronald G. Harley

This document has been relocated to http://scholarsmine.mst.edu/ele_comeng_facwork/931

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Abstract

This paper compares the performances of a multilayer perceptron neurocontroller and a radial basis function neurocontroller for backpropagation through time based indirect adaptive control of the synchronous generator. Also, the neurocontrollers are compared with the conventional controller for small as well as large disturbances to the power system