A method of vector control system based on genetic algorithm

The performance of vector control (VC) system for induction motor is depended on the rotor flux estimation in a large degree. Extended Kalman filter (EKF) is useful to estimate state variables when the measured signal is mixed with noise. A flux linkage estimation method for induction motor based on EKF theory is presented in this paper, where, the stator current, as well as flux linkage are regarded as the state variables to be estimated by joint filtering. For the sake of improving the accuracy of the filtering, genetic algorithm (GA)is introduced to optimize the noise matrix in EKF. The closed loop system composed by vector controller and the proposed flux linkage observer with optimized filtering parameter has better estimating accuracy and dynamic speed performance than ordinary vector control scheme. The effectiveness is verified by simulation and experimental results.