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 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
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 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.
