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In this paper we present the experimental results of the neural networkcontrol of a servo-system in order to control its speed. The control strategyis implemented by using an inverse-model control based on Artificial NeuralNetworks (ANNs). The network training was performed using two learningalgorithms: Levenberg-Marquardt and Bayesian regularization. We evaluate thegeneralization capability for each method according to both the correctoperation of the controller to follow the reference signal, and the controlefforts developed by the ANN-based controller.

Control Neuronal por Modelo Inverso de un Servosistema Usando Algoritmos de Aprendizaje Levenberg-Marquardt y Bayesiano