A NOVEL ARTIFICIAL HYDROCARBON NETWORKS BASED SPACE VECTOR PULSE WIDTH MODULATION CONTROLLER FOR INDUCTION MOTORS
- 1 Graduate School of Engineering, Tecnológico de Monterrey, Campus Ciudad de México, 14380, Mexico City, Mexico
Abstract
Most of machine-operated industrial processes implement electric machinery as their work sources, implying the necessary improvement of control techniques and power electronics drivers. Many years have passed since the control conflicts related to induction motors have been overcome through torque-flux control techniques so their advantages over direct current motors have made them to be the most common electric actuator found behind industrial automation. In fact, induction motors can be easily operated using a Direct Torque Control (DTC). Since, it is based on a hysteresis control of the torque and flux errors, its performance is characterized by a quick reaching of the set point, but also a high ripple on both torque and flux. In order to enhance that technique, this study introduces a novel hybrid fuzzy controller with artificial hydrocarbon networks (FMC) that is used in a Space Vector Pulse Width Modulation (SVPWM) technique, so-called FMC-SVPWM-DTC. In fact, this study describes the proposal and its design method. Experimental results over a velocity-torque cascade topology proved that the proposed FMC-SVPWM-DTC responses highly effective almost suppressing rippling in torque and flux. It also performed a faster speed response than in a conventional DTC. In that sense, the proposed FMC-SVPWM-DTC can be used an alternative approach for controlling induction motors.
DOI: https://doi.org/10.3844/ajassp.2014.789.810
Copyright: © 2014 Hiram Ponce, Luis Ibarra, Pedro Ponce and Arturo Molina. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Direct Torque Control
- Spatial Vector PWM
- Artificial Hydrocarbon Networks