Real-time on-line parameter estimation of linear switched reluctance motor

The on-line least-square identification method is applied for the linear switched reluctance motor (LSRM) based closed-loop control system. Since switched reluctance motors have severe nonlinear characteristics, on-line system identification for model parameters is the basis for precise modeling and effective control algorithms. By on-line parameter identification of LSRM with least-square scheme, the parameter characteristics can be predicted despite of operation variations. The experimental results demonstrate the identification scheme has fast response and converging speed and the capability of effective parameter prediction under different conditions.