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

© The Institution of Engineering and Technology
Received 18/01/2018, Accepted 04/05/2018, Revised 05/04/2018, Published 10/05/2018

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.

Inspec keywords: angular velocity control; observers; variable structure systems; rotors; magnetic levitation; sensorless machine control; stability; parameter estimation; model reference adaptive control systems; induction motor drives; linear induction motors; machine vector control; Lyapunov methods

Other keywords: LIM drives; Lyapunov stability theory; stability analysis; parallel secondary resistance online identification; speed estimation algorithm; single-manifold SMO; conventional speed estimation scheme; speed estimation scheme performance; sliding-mode observer-based speed-sensorless-vector control; sliding mode observer; ensorless-vector-controlled linear induction motor drives; sliding mode model reference adaptive system observer; dynamic end effect; state space-vector model; Popov hyperstability theory; medium–low-speed maglev applications; secondary resistance estimation algorithms; hardware-in-the-loop tests

Subjects: Self-adjusting control systems; Stability in control theory; Drives; Asynchronous machines; Multivariable control systems; Transportation; Velocity, acceleration and rotation control; Control of electric power systems

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