To solve the problem that the choice of softening factor in conventional adaptive strong tracking filter( STF) greatly relies on the experience and computer simulation,a new concept of softening factor matrix is intro...To solve the problem that the choice of softening factor in conventional adaptive strong tracking filter( STF) greatly relies on the experience and computer simulation,a new concept of softening factor matrix is introduced and a fuzzy adaptive strong tracking cubature Kalman filter( FASTCKF) based on fuzzy logic controller is proposed. This method monitors residual absolute mean and standard deviation of each measurement component with fuzzy logic adaptive controller( FLAC),and adjusts the softening factor matrix dynamically by fuzzy rules,which is capable to modify suboptimal fading factor of STF adaptively and improve the filter's robust adaptive capacity. The simulation results show that the improved filtering performance is superior to the conventional square root cubature Kalman filter( SCKF) and the strong tracking square root cubature Kalman filter( STSCKF).展开更多
This paper presents a sliding mode observer for sensorless operation of SRM （switched reluctance motor） drive. Design of such an observer depends mainly on the nonlinear model of SRM. In this technique, neither extr...This paper presents a sliding mode observer for sensorless operation of SRM （switched reluctance motor） drive. Design of such an observer depends mainly on the nonlinear model of SRM. In this technique, neither extra hardware nor huge memory space are not required but it only requires active phase measurements. Furthermore, PI （proportional integral） and adaptive FLPI （fuzzy logic PI） controllers are suggested to operate individually along with the SMO （sliding mode observer） to cover a full speed range of sensorless controller. Both controller schemes operate in PWM （pulse width modulation） control mode. The proposed observer is implemented and tested using a digital signal processor. All results obtained with both simulation and experimental investigations corroborate the superior performance of the adaptive fuzzy logic controller （FLPI） when compared with those of PI controller.展开更多
基金National Natural Science Foundations of China(Nos.51175082,60874092,51375088)
文摘To solve the problem that the choice of softening factor in conventional adaptive strong tracking filter( STF) greatly relies on the experience and computer simulation,a new concept of softening factor matrix is introduced and a fuzzy adaptive strong tracking cubature Kalman filter( FASTCKF) based on fuzzy logic controller is proposed. This method monitors residual absolute mean and standard deviation of each measurement component with fuzzy logic adaptive controller( FLAC),and adjusts the softening factor matrix dynamically by fuzzy rules,which is capable to modify suboptimal fading factor of STF adaptively and improve the filter's robust adaptive capacity. The simulation results show that the improved filtering performance is superior to the conventional square root cubature Kalman filter( SCKF) and the strong tracking square root cubature Kalman filter( STSCKF).
文摘This paper presents a sliding mode observer for sensorless operation of SRM （switched reluctance motor） drive. Design of such an observer depends mainly on the nonlinear model of SRM. In this technique, neither extra hardware nor huge memory space are not required but it only requires active phase measurements. Furthermore, PI （proportional integral） and adaptive FLPI （fuzzy logic PI） controllers are suggested to operate individually along with the SMO （sliding mode observer） to cover a full speed range of sensorless controller. Both controller schemes operate in PWM （pulse width modulation） control mode. The proposed observer is implemented and tested using a digital signal processor. All results obtained with both simulation and experimental investigations corroborate the superior performance of the adaptive fuzzy logic controller （FLPI） when compared with those of PI controller.
