Fuzzy Controller and Neural Estimator Applied to Control a System Powered by Three-Phase Induction Motor

Élida Fernanda Xavier Júlio, Simplício Arnaud da Silva, Cícero da Rocha Souto, Isaac Soares de Freitas
2015 International Journal of Artificial Intelligence & Applications  
In this study, a control strategy is presented to control the position and the feed rate of a table of a milling machine powered by three-phase induction motor, when machining pieces constituted by different types of materials: steel, brass and nylon. For development of the control strategy, the vector control technique was applied to drive the three-phase induction machines. The estimation of the electromagnetic torque of the motor was used to determine the machining feed rate for each type of
more » ... te for each type of material. The speed control was developed using fuzzy logic Takagi-Sugeno (TS) model and the estimation of the electromagnetic torque using the artificial neural network (ANN) of the least mean square (LMS) algorithm type. The induction motor was fed by a three-phase voltage inverter hardware driven by a digital signal processor (DSP). Experimental results are presented.
doi:10.5121/ijaia.2015.6402 fatcat:lkyideqbpjappep5ij5qnvq2va