DTC Control of Induction Motors Employing Advanced Control Techniques

Abstract

Conventional Proportional Integral controllers require precise mathematical model of the system and proper tuning of controllers to achieve high performance drive. Induction motor drives controlled by Field Oriented Control are mainly employed in high performance industrial applications, instead of dc motors. Field Oriented Control is very sensitive to flux predominantly affected by variation in parameters. It allows control of both torque and flux by decoupling the stator current into two orthogonal components. The primary limitation of FOC relies on parameter identification to achieve the expected performance. An alternative control method called Direct Torque Control has been developed for electrical machine. The DTC method is characterized by its simple implementation and a fast dynamic response Using this method, Stator voltage vectors can be determined according to the difference between the reference & actual torque and stator flux linkage. With this approach the inverter is directly controlled by the algorithm instead of a modulation technique for the inverter. The key benefit of DTC method is absence of coordinate transformation and also separate voltage modulation is not required. However, high torque ripple and slow transient response to the step changes in torque during start-up also adds to disadvantages of conventional DTC. In order to overcome this issue the soft computing techniques can be employed. The paper proposed the implementation of Induction motor control using Fuzzy logic and Artificial Neural Network methods .