Control de Velocidad de Motor de Inducción con Observador Difuso y Controlador Neuronal

Abstract:

In this article the intelligent control of the induction motors is realized, using the Fuzzy Logic as state observer and the Artificial Neural Networks as controllers using nonlinear mathematical models of the motors as complex plants. The neural controller designed is in the space of artificial neural networks of the multi-layer perceptron type, with an input layer, a hidden layer and an output layer, The diffuse observer used is of the Takagi and Sugeno type, the discourse universe is considered as a function of the variance of the noise of the encoder power, the chosen relevance function is triangular with consequent of the linear differential equations type, the filtered observation strategy is carried out with a normalized weighted law adaptive. The results obtained in silico allow to observe that the information collected from a noisy optical encoder using an adaptive fuzzy estimator decreases the amplitude of the noisy signal …

Año de publicación:

2021

Keywords:

Fuente:

google