Adaptive Neuro Fuzzy based dynamic simulation of induction motor drives

In the industrial sector especially in the field of electric drives & control, induction motors play a vital role. Without proper controlling of the speed, it is virtually impossible to achieve the desired task for a specific application. Basically AC motors, such as Induction Motors are of Squirrel-Cage type. They are simple, reliable, low cost and virtually maintenance-free electrical drives. Based on the inability of conventional control methods like PI, PID controllers to work under wide range of operation, artificial intelligent based controllers are widely used in the industry like ANN, Fuzzy controller, ANFIS, expert system, genetic algorithm. The main problem with the conventional fuzzy controllers is that the parameters associated with the membership functions and the rules depend broadly on the intuition of the experts. To overcome this problem, Adaptive Neuro-Fuzzy controller is proposed in this paper. The comparison between Conventional PI, Fuzzy Controller and Adaptive neuro fuzzy controller based dynamic performance of induction motor drive has been presented. Adaptive Neuro Fuzzy based control of induction motor will prove to be more reliable than other control methods.

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