An enhanced sliding mode observer method applied to sensorless induction motor drives under stator resistance variation
DOI:
https://doi.org/10.20998/2074-272X.2026.4.05Keywords:
resistance variation, speed sensorless control, sliding mode observer, thermal effect, voltage modelAbstract
Introduction. Sliding mode observer (SMO), with its simplicity and efficiency, is one of the widely used sensorless control techniques in induction motor (IM) drive systems. However, this method’s performance is highly sensitive to changes in motor parameters, especially increases in stator resistance (Rs) due to thermal effects. Problem. As Rs increases due to thermal effects during operation, the estimation of rotor flux and virtual current becomes inaccurate, degrading the SMO method’s performance in generating estimated speeds for the controller. Goal. To develop an improved speed sensorless control scheme for IM drives that maintains high accuracy of estimation under variations in Rs. Methodology. SMO is first employed to estimate rotor speed from measured stator currents and voltages. Then, a Rs estimation mechanism based on a combined SMO-model reference adaptive system (SMO-MRAS) structure is proposed, in which the voltage model serves as the reference model and the SMO-based flux estimation acts as the adaptive model. The estimated resistance is obtained through a PI adaptation law. Results. Under 20 % and 40 % Rs increments, the proposed scheme reduces Integral Absolute Error (IAE) from 0.7699 to 0.4661, Integral Squared Error (ISE) from 0.555 to 0.4688, and Integral Time Squared Error (ITSE) from 0.6286 to 0.4502. The maximum stator current deviation decreases from 0.578 A to 0.005457 A, while stable speed tracking at 20 rad/s is preserved under load disturbance. Scientific novelty. The study proposes a structurally integrated SMO-MRAS framework that decouples speed estimation from MRAS while embedding resistance adaptation within the observer loop. Practical value. The proposed method enhances robustness against thermal parameter variation and improves the reliability of sensorless IM drives in real operating conditions. References 36, table 1, figures 9.
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