AI Based Rotor Position Estimation Techniques for Switched Reluctance Motor Drives

Vol.1 No.3

Year: 2008

Issue: Jan-Mar

Title: AI Based Rotor Position Estimation Techniques for Switched Reluctance Motor Drives

Author Name: M. Marsaline Beno, N.S. Marimuthu   

Synopsis:  

   This paper presents artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) based rotor position estimation techniques for switched reluctance motor (SRM) drive system. The techniques estimate rotor position by measuring the three-phase voltages and currents and using magnetic characteristics of the SRM, with the aid of an ANN and ANFIS. The rotor position estimating techniques are used in a high-performance sensor less variable speed SRM drive. The results are compared with the measured values, and the error analyses are given to determine the performance of the developed method. The error analyses have shown great accuracy and successful rotor position estimation techniques for a 6/4 poleswitched reluctance motor using AI techniques.