Electromagnetic Torque Estimation of a Three-Phase Induction Motor for Setting the Feedrate of a Milling Machine

Abstract

In this paper, it presents a project of a fuzzy controller and a neural estimator to control a coordinate table powered by three-phase induction motor, aiming to implement an intelligent milling system. The position/speed control is performed using vector techniques of three-phase induction machines. The estimation of the motor electromagnetic torque is used for setting the feedrate of the table. The speed control is developed using TS (Takagi-Sugeno) fuzzy logic model and electromagnetic torque estimation using neural network type LMS (least mean square) algorithm. The induction motor is powered by a frequency inverter driven by a DSP (digital signal processor). Control strategies are implemented in DSP. Simulation results are presented for evaluating the performance of the system.