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This paper presents a rotor position estimation technique for a 6/4 switched reluctance machine based on Adaptive Neuro fuzzy Inference System (ANFIS). This technique is applied for modelling the nonlinear rotor position of SRM using the magnetization characteristics of the machine. ANFIS has a strong nonlinear approximation ability which could be used for nonlinear modelling and its real time implementations. In this paper, the best features of ANFIS is utilised to develop the computationally efficient rotor position model θ (I,ψ) for SRM. Mathematical model for θ (I,ψ) using ANFIS has been successfully arrived, tested and presented for various values of phase currents (Iph) and phase flux linkage(ψ) of a non linear SRM. It is observed that ANFIS is highly suitable for rotor position θ (I,ψ) modelling of SRM which is tested to be in good agreement with the training and checking data used for modelling.

Rotor Position Estimation for a Switched Reluctance Machine from Phase Flux Linkage