Research on Low-Speed Performance of Sensorless Induction Motor using an Improved Stator Current Based MRAS

Owing to the elimination of physical sensors, sensorless speed control systems for induction motors are gaining increasing popularity. Nevertheless, the low-speed performance of these systems still warrants further enhancement. Speed sensorless control based on the model reference adaptive system (MRAS) has garnered widespread attention, primarily attributed to its robust adaptability and computational simplicity. This paper proposes an improved measure for induction motors, addressing the instability of traditional stator current based MRAS at low speeds. Based on Lyapunov stability theory, the adaptive law of MRAS is modified, and a coefficient is introduced to correct the rotor flux-producing current. The observer performance is further enhanced by configuring the feedback matrix. The feasibility and efficiency of the proposed method have been validated through both simulation and experimental measurement.