Modeling and Analysis of Adaptive Neuro Fuzzy Inference System Based BLDC Motor under Different Operating Conditions
T. Bheemeswara Reddy1, K. Satyanarayana2, T. Himaja3
1Mr. T. Bheemeswara Reddy, M. Tech in power Electronics and Electrical Drives, Pragati Engineering College, Surampalem, (Andhra Pradesh), India.
2Dr. K. Satyanarayana, Professor and H.O.D. of E.E.E Department, Pragati Engineering College, Surampalem, (Andhra Pradesh), India.
3Ms. T. Himaja, M.Tech-Student in power electronics and electrical drives, Pragati Engineering College, Surampalem, (Andhra Pradesh), India.
Manuscript received on July 24, 2014. | Revised Manuscript received on August 05, 2014. | Manuscript published on August 30, 2014. | PP: 144-148 | Volume-3 Issue-6, August 2014. | Retrieval Number: F3353083614/2013©BEIESP
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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: In this paper the performance factors of adaptive neuro fuzzy inference system (ANFIS) based brushless direct current (BLDC) motor for controlling speed and torque under different operating conditions are analyzed. The above scheme has many characteristics like small torque ripple, strong robustness, good anti interference ability and reduction of starting currents. The dynamic characteristics of the brushless DC motor such as speed, torque, current and voltages of the inverter components are observed and analyzed. In order to verify the effectiveness of the controller, the simulation results are compared with PID controller. The simulation result show that the overall performance of ANFIS based BLDC motor is much better when compared to PID controller under different operating conditions.
Keywords: Brushless DC motor, Speed control, Torque control, PID controller and ANFIS controller.