Robust speed regulation of a DC motor using a data-driven method with RNA
Abstract
This work presents a data-driven control of a DC motor using artificial neural networks. The main components of the proposed control scheme are the numerical model of the plant, that includes as input the voltage supplied by the source, and an inverse moled which calculates the control signal, both implemented using Artificial Neural Networks (ANN). The main novelty of the proposed method is the incorporation of voltage in the state vector of the model which it is of interest due to its practical importance when modeling the DC motor. To validate the proposed scheme, experimental results on a commercial DC motor under time-varying perturbations are presented.
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References
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Copyright (c) 2024 Marco Antonio Castro-Liera, César Higuera-Verdugo, Jesús Alberto Sandoval-Galarza, Iliana Castro-Liera
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