Sensorless control for synchronous motors

Abstract

Permanent magnet synchronous motors are used in many industrial applications because they have several inherent advantages. However, information about the rotor position is necessary even to be able to control drive speed. Conventional speed and position detection uses encoder and resolver. These sensors significantly increase price, weight, and degrade reliability. Therefore many authors publish papers about algorithms for rotor position and speed estimation. One of state estimation possibility is using extended Kalman filter. Conventional algorithms based on EKF are developed using a simple model of permanent magnet synchronous motor, thereby provide bad performance in the low speed range. Extended Kalman filter using an interior permanent magnet synchronous motor model is described in this paper. This model makes possible for EKF to operate in low speeds. Second part of this paper describes an algorithm Model Reference Adaptive system (MRAS).