Speed and torque control of induction motor using adaptive neuro-fuzzy interference system with DTC

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Abstract

Every industry needs speed and torque ripple control of induction motor in large number of applications. The number of induction motor takes more time during starting, settling and transient period. As more time is taken by the motor so there are more losses, more heat, less efficiency and more ripples are produced. To overcome these drawback, direct torque control technique known as conventional technique, is used with induction motors, but with up to certain limits the drawbacks are reduced. In this paper a new technique an Adaptive Neuro-Fuzzy Interference System (ANFIS) with DTC is proposed to overcome the drawbacks of conventional DTC technique. Now by implementing and comparing the proposed technique ANFIS with conventional one it is seen that the system becomes less complicated, the performance of the speed and torque control of the induction motor is also improved. It is also seen that as we compared the proposed technique with conventional one the rise time is reduced by 256 ms settling time is reduced by 687 ms and transient time is reduced by 202 ms and torque ripples are also reduced and the overall performance of the induction motor is improved.

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Bindal, R. K., & Kaur, I. (2019). Speed and torque control of induction motor using adaptive neuro-fuzzy interference system with DTC. In Communications in Computer and Information Science (Vol. 955, pp. 815–825). Springer Verlag. https://doi.org/10.1007/978-981-13-3140-4_73

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