Induction machine PWM control using PI and ANFIS

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Induction machine PWM control using PI and ANFIS

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The control of an induction machine is a complex process that requires careful consideration of many factors. One method of control is pulse width modulation (PWM), which uses a pulse signal to control the power supplied to the machine. However, this method alone may not be sufficient for achieving optimal performance. To improve the control of the induction machine, a proportional-integral (PI) controller can be implemented. The PI controller continuously adjusts the PWM signal to maintain a constant output voltage, even in the presence of disturbances.

Another approach that can be used to improve the performance of the induction machine is adaptive neuro-fuzzy inference systems (ANFIS). ANFIS uses a combination of neural network and fuzzy logic techniques to create a system that can learn from input-output data. This approach can be used to improve the accuracy of the control system and make it more robust to changes in the operating conditions of the machine. By combining PWM, PI, and ANFIS, a comprehensive control system can be developed that can achieve high levels of performance in controlling an induction machine.