A high resolution speed and position identification algorithm, suitable for brushless DC drives, is presented in this paper. In particular, the algorithm is proposed for BLDC （brushless DC） machines that are charact...A high resolution speed and position identification algorithm, suitable for brushless DC drives, is presented in this paper. In particular, the algorithm is proposed for BLDC （brushless DC） machines that are characterized by an un-ideal trapezoidal emfs shape. The algorithm, which is developed basing upon the MRAS technique （model reference adaptive system） and the Popov＇s hyperstability criterion, guarantees the convergence of the estimated rotor speed and position signals to their corresponding actual values. The identification procedure can be performed starting from the knowledge of low resolution rotor position signals, phase currents and the BLDC emfs shape. The identification algorithm is properly tested on a BLDC drive controlled by a predictive algorithm, by performing a simulation study in the Matlab-Simulink environment. The corresponding results have highlighted the effectiveness of the proposed sensorless predictive control system, at both low and high speed operation.展开更多
文摘A high resolution speed and position identification algorithm, suitable for brushless DC drives, is presented in this paper. In particular, the algorithm is proposed for BLDC （brushless DC） machines that are characterized by an un-ideal trapezoidal emfs shape. The algorithm, which is developed basing upon the MRAS technique （model reference adaptive system） and the Popov＇s hyperstability criterion, guarantees the convergence of the estimated rotor speed and position signals to their corresponding actual values. The identification procedure can be performed starting from the knowledge of low resolution rotor position signals, phase currents and the BLDC emfs shape. The identification algorithm is properly tested on a BLDC drive controlled by a predictive algorithm, by performing a simulation study in the Matlab-Simulink environment. The corresponding results have highlighted the effectiveness of the proposed sensorless predictive control system, at both low and high speed operation.
