Impact of Observability and Multi-objective Optimization on the Performance of Extended Kalman Filter for DTC of AC Machines

Abstract

It is well known that the selection of extended Kalman filter (EKF) covariance elements has a considerable bearing on the effectiveness of EKF performance. The observability at very low frequency is also an essential property for the selection of EKF elements. This paper investigates the optimization of the EKF covariance elements when zero frequency is included in the training profile for direct torque control (DTC) of induction motor. In addition, the paper studies the optimization of EKF by speed and torque fitness functions using a non-dominated sorting genetic algorithm-II at zero and high speeds under stable flux regulation. For this purpose, DTC with constant switching frequency controller which has the capability of establishing continuous flux rotation regardless of speed variation is used. The optimized results of EKF for both DTC motor drives and speed and torque cost functions are verified experimentally.