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In this paper is presented an off-line trained artificial neural network controller with multilayer perceptron topology. It is trained by a genetic algorithm and applied to the direct power control of a doubly-fed induction generator under stator voltage dip. This controller dispenses the use of any other in the control system, and to our knowledge it is not found in the technical publications that...
This paper presents a Predictive Direct Power Control Applied to the Doubly Fed Induction Generator operating with or without voltage dip, in variable speed operation. The predictive controller is obtained from state-space DFIG model. The control law is derived by optimization of a cost function that considers the difference between the predicted outputs — stator active and reactive powers — and their...
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