A speed sensorless vector control system of induction motor with estimated rotor speed and rotor flux using a new reduced order extended Kalman filter is proposed. With this method, two rotor flux components are sele...A speed sensorless vector control system of induction motor with estimated rotor speed and rotor flux using a new reduced order extended Kalman filter is proposed. With this method, two rotor flux components are selected as the state variables, and the rotor speed as an estimated parameter is regarded as an augmented state variable. The algorithm with reduced order decreases the computational complexity and makes the proposed estimator feasible to be implemented in real time. The simulation results show high accuracy of the estimation algorithm and good performance of speed control, and verify the usefulness of the proposed algorithm.展开更多
The key of speed sensorless vector control system lies in the accurate orientation of magnetic field. In some field-oriented algorithms, the integrator of observers and the dead-time effect bring in system errors duri...The key of speed sensorless vector control system lies in the accurate orientation of magnetic field. In some field-oriented algorithms, the integrator of observers and the dead-time effect bring in system errors during the estimation of field position. In this paper, a saturated feedback integrator is used, and the dead-time effect is compen- sated by current positive feedback. Experiments were carried out on the hardware platform of MCK2407, with chip TMS320LF2407 from TI Company. The results show that the prooosed method is simole and effective, and the accuracy of field position is improved.展开更多
A method of improving the stability of multiple-motor drive system fed by a 3-leg single inverter has been devised that employs the averages and differences of estimated parameters for field-oriented control. The para...A method of improving the stability of multiple-motor drive system fed by a 3-leg single inverter has been devised that employs the averages and differences of estimated parameters for field-oriented control. The parameters of each motor (stator current, rotor flux, and speed) are estimated using adaptive rotor flux observers to achieve sensorless control. The validity and effective of the proposed method have been demonstrated through simulations and experiments.展开更多
文摘A speed sensorless vector control system of induction motor with estimated rotor speed and rotor flux using a new reduced order extended Kalman filter is proposed. With this method, two rotor flux components are selected as the state variables, and the rotor speed as an estimated parameter is regarded as an augmented state variable. The algorithm with reduced order decreases the computational complexity and makes the proposed estimator feasible to be implemented in real time. The simulation results show high accuracy of the estimation algorithm and good performance of speed control, and verify the usefulness of the proposed algorithm.
文摘The key of speed sensorless vector control system lies in the accurate orientation of magnetic field. In some field-oriented algorithms, the integrator of observers and the dead-time effect bring in system errors during the estimation of field position. In this paper, a saturated feedback integrator is used, and the dead-time effect is compen- sated by current positive feedback. Experiments were carried out on the hardware platform of MCK2407, with chip TMS320LF2407 from TI Company. The results show that the prooosed method is simole and effective, and the accuracy of field position is improved.
文摘A method of improving the stability of multiple-motor drive system fed by a 3-leg single inverter has been devised that employs the averages and differences of estimated parameters for field-oriented control. The parameters of each motor (stator current, rotor flux, and speed) are estimated using adaptive rotor flux observers to achieve sensorless control. The validity and effective of the proposed method have been demonstrated through simulations and experiments.
