Abstract
This paper presents an application of artificial neural networks (ANN) as a controller for a synchronous machine excitation system. A hierarchical architecture of an ANN is adopted for the controller design, which is used for data mapping and control respectively, based on the backpropagation algorithm (BPA). The controller's operation does not require a reference model or an inverse system model and it can produce more acceptable control signals than are obtained by using plant errors during its training. The input-output mapping of synchronous machines using ANN's has been investigated and the controller has been implemented on a complex synchronous machine model. The simulation results are given, showing satisfactory control performance and illustrate the potential of the ANN controller as useful for practical purposes. >
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