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 control platform of the induction motor （IM） with low costs is developed by using DSP MC56F8013 with a good performance/price rtaio. The control algorithm for the speed sensorless IM is studied based on the stat...The control platform of the induction motor （IM） with low costs is developed by using DSP MC56F8013 with a good performance/price rtaio. The control algorithm for the speed sensorless IM is studied based on the stator flux orientation （SFO）. The algorithm structure is simple to be implemented and cannot be influenced by motor parameters, The improved stator flux estimation is used to compensate errors caused by the low pass filter （LPF）. A new speed regulator is designed to ensure the system working with the maximal torque in the transient state. The system simulation and the prototype experiment are made. Results show that the con- trol system has good dynamic and static performance.展开更多
A fuzzy neural network controller with the teaching controller guidance and parameter regulations for vector-controlled induction motor is proposed. The design procedures of the fuzzy neural controller and the teachin...A fuzzy neural network controller with the teaching controller guidance and parameter regulations for vector-controlled induction motor is proposed. The design procedures of the fuzzy neural controller and the teaching controller are described. The parameters of the membership function are regulated by an on-line learning algorithm. The speed responses of the system under the condition, where the target functions are chosen as I qs and ω, are analyzed. The system responses with the variant of parameter moment of inertial J, viscous coefficients B and torque constant K tare also analyzed. Simulation results show that the control scheme and the controller have the advantages of rapid speed response and good robustness.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
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 speed-sensorless vector control system for induction machines （IMs）is presented, According to the vector control theory of IMs, the rotor flux is estimated based on a flux observer,and the speed is estimated throu...A speed-sensorless vector control system for induction machines （IMs）is presented, According to the vector control theory of IMs, the rotor flux is estimated based on a flux observer,and the speed is estimated through the method of q-axis rotor flux converging on zero with proportional integral regulator, A 0.75 kW,50 Hz,two-pole induction machine was used in the simulation and experimental verification, The simulation model was constructed in Matlab. A series of tests were performed in the field weakening region, for both no-load and loaded operation. The estimated speed tracks the actual speed well in the based speed region and field weakening region （ 1 per unit value to 4 per unit value）. The small estimation error of residual speed is due to the existence of slip.展开更多
This paper presents a speed sensorless vector control system for induction machine (IM),which is based on a flux observer. According to vector control theory of IM,the q-axis rotor flux converging on zero is utilized ...This paper presents a speed sensorless vector control system for induction machine (IM),which is based on a flux observer. According to vector control theory of IM,the q-axis rotor flux converging on zero is utilized for speed estimation. Additionally this system solved the online identification of stator resistance by d-axis flux error. The advantages of the proposed system are simplicity and avoidance of the problems caused by only using a voltage model. The effectiveness of the proposed system has been verified by simulation and experimentation.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 control platform of the induction motor （IM） with low costs is developed by using DSP MC56F8013 with a good performance/price rtaio. The control algorithm for the speed sensorless IM is studied based on the stator flux orientation （SFO）. The algorithm structure is simple to be implemented and cannot be influenced by motor parameters, The improved stator flux estimation is used to compensate errors caused by the low pass filter （LPF）. A new speed regulator is designed to ensure the system working with the maximal torque in the transient state. The system simulation and the prototype experiment are made. Results show that the con- trol system has good dynamic and static performance.
文摘A fuzzy neural network controller with the teaching controller guidance and parameter regulations for vector-controlled induction motor is proposed. The design procedures of the fuzzy neural controller and the teaching controller are described. The parameters of the membership function are regulated by an on-line learning algorithm. The speed responses of the system under the condition, where the target functions are chosen as I qs and ω, are analyzed. The system responses with the variant of parameter moment of inertial J, viscous coefficients B and torque constant K tare also analyzed. Simulation results show that the control scheme and the controller have the advantages of rapid speed response and good robustness.
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.
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 speed-sensorless vector control system for induction machines （IMs）is presented, According to the vector control theory of IMs, the rotor flux is estimated based on a flux observer,and the speed is estimated through the method of q-axis rotor flux converging on zero with proportional integral regulator, A 0.75 kW,50 Hz,two-pole induction machine was used in the simulation and experimental verification, The simulation model was constructed in Matlab. A series of tests were performed in the field weakening region, for both no-load and loaded operation. The estimated speed tracks the actual speed well in the based speed region and field weakening region （ 1 per unit value to 4 per unit value）. The small estimation error of residual speed is due to the existence of slip.
文摘This paper presents a speed sensorless vector control system for induction machine (IM),which is based on a flux observer. According to vector control theory of IM,the q-axis rotor flux converging on zero is utilized for speed estimation. Additionally this system solved the online identification of stator resistance by d-axis flux error. The advantages of the proposed system are simplicity and avoidance of the problems caused by only using a voltage model. The effectiveness of the proposed system has been verified by simulation and experimentation.
