Sliding-mode observer-based speed-sensorless vector control of linear induction motor with a parallel secondary resistance online identification

This study proposes a speed estimation scheme for the sensorless-vector-controlled linear induction motor (LIM) drives for medium-low-speed maglev applications, which is composed of two parts: (i) a sliding mode model reference adaptive system observer for speed estimation; and (ii) a parallel secondary resistance online identification for achieving the improvements of the proposed speed estimation scheme performance. The sliding mode observer (SMO) is established on the basis of the state space-vector model of the LIM considering the dynamic end effect. Based on SMO, both speed and secondary resistance estimation algorithms are obtained by utilising Popov's hyperstability theory. Moreover, the Lyapunov stability theory is adopted for the stability analysis of the proposed speed estimation scheme. The effectiveness of the proposed speed estimation algorithm has been verified and compared with the performance of the conventional speed estimation scheme based on single-manifold SMO by the simulation and hardware-in-the-loop tests.