J. A. T. Altuna

Implementation of a neuro-fuzzy direct torque and reactive power control for DFIM

This paper proposes a Takagi-Sugeno neurofuzzy inference system for direct torque and stator reactive power control applied to a doubly fed induction motor (DFIM). The control variables (d-axis and q-axis rotor voltages) are determined through a control system composed by a neuro-fuzzy inference system and a first order Takagi-Sugeno fuzzy logic controller. Experimental results are presented to validate the controller operation for variable speed under no-load and load conditions and stator reactive power variation under load condition. For this last validation, a PI controller is used to control the rotor speed, thereby its output is used to manipulate the torque in order to follow the demanded speed value.

Overvoltage Minimization in Induction Motors employing Long Cable PWM Drives

The employment of PWM drives in induction motors control has been widely used in industry. However, in some applications in hazardous areas, such as drilling, the PWM drive cannot be physically close to the motor, being necessary the use of long cable drives. This fact leads to the generation of overvoltage peaks on the induction motor terminals, which can cause interference in the speed control, reduction of equipment lifetime, or even, permanent damages. In this context, this work presents alternatives to minimize the overvoltage effect based on the use of transformers and analyzes the performance of the speed control of each proposed technique.