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

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.