Sensorless Speed Control of Induction Machine with Adaptive-Neuro Fuzzy Technique Integrated MRAS Module

Sensorless Speed Control of Induction Machine with Adaptive-Neuro Fuzzy Technique Integrated MRAS Module

© 2022 by IJETT Journal
Volume-70 Issue-7
Year of Publication : 2022
Authors : Sujeet Kumar Soni, Manish Khemariya, Anand Singh
DOI : 10.14445/22315381/IJETT-V70I7P242

How to Cite?

Sujeet Kumar Soni, Manish Khemariya, Anand Singh, "Sensorless Speed Control of Induction Machine with Adaptive-Neuro Fuzzy Technique Integrated MRAS Module" International Journal of Engineering Trends and Technology, vol. 70, no. 7, pp. 405-413, 2022. Crossref,

In new electrical power grid technology, advanced control techniques are adopted to control the generation of load parameters better. Artificial intelligence control modules are integrated to stabilize the system at the earliest for a faster response rate. This paper introduces a "sensorless speed control module" with ANFIS in a conventional MRAS estimator module for rapid stabilization of induction motor. The new controller is compared with conventional PI, PID, and fuzzy MRAS control modules. A parametric evaluation and comparison of induction motor speed graphs with all the mentioned controllers determines the best controller among them. Simulation validations of the modules as mentioned above are done using the MATLAB Simulink tool and comparison of graphs concerning peak value generation, ripple, and settling time of speed.

ANFIS (Adaptive-Neuro Fuzzy Interference System), "MRAS (Model Reference Adaptive System)," PI (Proportional-Integral), PID (Proportional-Integral-Derivative), Fuzzy, MATLAB (Matrix Laboratory).

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