Reduced-order observer analysis in MBPC techniques applied to the six-phase induction motor drives

Abstract

Model-based predictive control techniques have been recently applied with success in power electronics, particularly in the fields of current control applied to AC multiphase electrical drives. In AC electrical drives control, most of state variables (i.e., rotor currents, rotor fluxes, etc.) cannot be measured, so they must be estimated. As a result of this issue, this chapter proposes a comparative study of reduced-order observers used to estimate the rotor currents in an model-based predictive current control applied to the six-phase induction motor. The proposed control techniques are evaluated using the Luenberger observer and the optimal estimator based on Kalman filter. Different operation modes are analyzed and are further compared in terms of statistical parameters of performance (i.e., covariance, standard deviation, mean square error, etc.). The effectiveness of proposed methods is verified by a set of comparative experiments obtained by using a six-phase induction motor system experimental setup.