Improved sensorless backstepping controller using extended Kalman filter of a permanent magnet synchronous machine

Abstract

This paper deals with an improved backstepping control strategy for sensorless control of a permanent magnet synchronous motor (PMSM) based on field-oriented control (FOC), using a backstepping controller to improve its performances. However, this control requires the precise knowledge of some machine’s variables which could not be available. In electric drives control, sensors are generally used as the main devices for feedback information. Some practical constraints could affect the system performances, due to the lack of measurement material or maintenance difficulties caused by the dysfunction or faults of the used sensors such as: encoder or resolver sensors of speed-position. In this paper, a sensorless control is proposed based on a dynamic backstepping method and an extended Kalman filter (EKF) which uses the state space formulation with a set of mathematical equations to recursively estimate future observations and minimizes the mean square error of the estimated variables (rotor speed position and torque) to design controllers for nonlinear systems. The proposed control scheme achieves the asymptotically uniformed stability. The effectiveness of this method is illustrated by the stabilization and tracking numerical examples and the obtained simulation results show the effectiveness and the feasibility of the proposed controller using Lyapunov approach.