Design of Robust Adaptive Observer against Measurement Noise for Sensorless Vector Control of Induction Motor Drives

Abstract

Position control in electrical drives is a challenging problem which is complicated by sensor noise and unknown disturbances. This paper proposes a new cascade sensorless speed control technique for induction motor drives suitable for electric vehicle applications using the full-order adaptive Luenberger observer that is insensitive to measurement noise and parametric variation. The adaptive speed law is obtained by the Lyapunov method using the estimated currents and fluxes. This technique ensures the stability of the induction motor considered as nonlinear dynamic system. Since the Luenberger observer works on deterministic environment, and it is most effective when sensor noise is limited, the present study aims to design a robust observer insensitive to measurement noise and parametric variation integrated in a cascade structure. The observer allows the filtering of the measured currents. To highlight the advantages of the new scheme, a comparative study and spectrum analysis will be presented. The proposed structure is verified using MATLAB/Simulink.