Optimal recursive rotor current estimation applied to speed control of dual three-phase induction machine

Abstract

The Kalman Filter (KF) is a very powerful tool when it comes to controlling noisy systems, because it provides optimal filtering of the noise in measurement and inside the system if the covariance matrices of these noises are known. This paper addresses the study of the KF application to improve the estimation of states through an optimal estimation of the rotor current and proposes a speed control for a dual three-phase induction machine (DTPIM), by using a model-based predictive controller (MBPC). The KF equations are raised using a DTPIM model in stationary reference frame (α — β), considering as state variables the stator and rotor currents. Simulation results are provided to examine the effectiveness of the optimal estimation of the rotor current.