Artificial Intelligence Based Vector Controller for Switched Reluctance Motor (SRM)
Patti Ranadheer1, N.Prabakaran2
1Mr. Patti Ranadheer, Deparment of EEE, Sathyabama Institute of Science& Technology, Chennai, India.
2Dr. N. Prabakaran, Department of ECE, KLEF (Deemed to be University), Guntur, India.
Manuscript received on November 20, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 1350-1352 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B2533129219/2020©BEIESP | DOI: 10.35940/ijeat.B2533.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The prevalence of the Switched Reluctance Motors (SRMs) increments step by step because of its points of interest, for example, Simple structure, low cost, less weight, high effectiveness and high beginning torque when contrasted with regular motors. SRM is an electric motor which has invaluable highlights that qualifies it to be utilized in electric vehicle, aviation and industrial applications. In this paper, the switched reluctance motor is controlled using vector control by AI controller (fuzzy) so as to limit the torque ripples by directing torque inside indicated hysteresis band. AI Control of SRM encouraged through an irregular converter. The proposed AI controllers are executed in MATLAB SIMULINK for specified SRM parameters. As indicated by the attained outcomes the SRM behavior is better when impelled by AI controller in contrast with usual controllers.
Keywords: Switched Reluctance Motor (SRM), Artificial Intelligence, FLC.