Advantages of Square-Root Extended Kalman Filter for Sensorless Control of AC Drives

Abstract

This paper is concerned with a fixed-point implementation of the extended Kalman filter (EKF) for applications in sensorless control of ac motor drives. The sensitivity of the EKF to round-off errors is well known, and numerically advantageous implementations based on the square-root decomposition of covariance matrices have been developed to address this issue. However, these techniques have not been applied in the EKF-based sensorless control of ac drives yet. Specific properties of the fixed-point implementation of the EKF for a permanent-magnet synchronous motor (PMSM) drive are presented in this paper, and suitability of various square-root algorithms for this case is discussed. Three square-root algorithms—Bierman–Thorton, Carlson–Schmidt–Givens, and Carlson–Schmidt–Householder—were implemented, and their performances are compared to that of the standard implementation based on full covariance matrices. Results of both simulation studies and experimental tests performed on a developed sensorless PMSM drive prototype of rated power of 10.7 kW are presented. It was confirmed that the square-root algorithms improve the behavior of the sensorless control in critical operating conditions such as low speeds and speed reversal. In particular, the Carlson–Schmidt–Givens algorithm was found to be well suited for the considered drive.