Sensorless Rotor Position Estimation of Switched Reluctance Motor Drive Using Computational Intelligence Techniques
S.kanagavalli1, A.Rajendran2

1S.kanagavalli, PG Scholar, Department of Electrical Engineering, Sona College of Technology, Salem, India.
2A.Rajendran, Department of Electrical Engineering, Sona College Of Technology, Salem, India.
Manuscript received on April 05, 2013. | Revised Manuscript received on April 27, 2013. | Manuscript published on May 05, 2013. | PP: 83-87 | Volume-3, Issue-2, May 2013. | Retrieval Number: B1435053213/2013©BEIESP
Open Access | Ethics and Policies | Cite
© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (

Abstract: This paper deals with an accurate method to detect the rotor position, which is used for high performance operation of Switched Reluctance Motor (SRM). Earlier, a several type of position sensors were used to detect the rotor position but this has many disadvantages like additional cost, electrical connections, mechanical alignment problems, and unreliability. To overcome these disadvantages several sensor less schemes were proposed for the SR Motor in the recent years, there by facilitating the elimination of the rotor position sensor. Here, the sensor fewer schemes is proposed based on fuzzy technique and also using adaptive Neuro fuzzy inference system (ANFIS) which it overcomes the disadvantages of sensor scheme and also it does not require any mathematical models and large lookup tables to predict the position angle. Then position estimation based on fuzzy and ANFIS are compared. In this paper, the rotor position or angle is estimated by using the relationship between flux linkage and phase current based on fuzzy rule base. ANFISbased model reference system is continuously tuned by using Back Propagation method with actual value of SRM. The simulation results for novel sensorless schemes is described and developed in MATLAB and shown the effectiveness of this sensor less Scheme.
Keywords: ANFIS, SRM, Sensorless Rotor Position Scheme, Fuzzy Logic Estimator.