Advanced control with extended Kalman filter and disturbance observer

Abstract

This paper describes a novel fuzzy tracking control for permanent magnet synchronous motors (PMSM) using an extended Kalman filter (EKF) and disturbance observer (DO). The goal is to create a robust controller able to drive the system’s states to track a virtual reference model and provide a low disturbance effect on the synchronous machine. First, the PMSM is represented using a fuzzy model Takagi-Sugeno (T-S) attended by the load torque variation. Next, To simplify the construction of a virtual reference model and nonlinear tracking control, a fuzzy tracking control based on virtual desired variables (VDVs) is proposed. Using this concept, a two-stage design procedure is developed: i) determine the VDVs using the desired output and the load torque, which can be estimated using DO and EKF and ii) calculate the fuzzy controller gains by solving linear matrix inequalities (LMIs). The efficiency of the suggested strategy is eventually shown through simulation results