Accurate speed and flux estimation are important conditions for achieving high-performance and low-cost control. Therefore, this study first constructs a mathematical model and space vector pulse width modulation control method for asynchronous motors. Then, a simple speed estimator, an extended Kalman filter speed estimator, and a full-order magnetic flux observer speed estimator are established in the speed estimation module. Finally, based on the Euler voting algorithm, a fault diagnosis and fault-tolerant control method for speed sensors is designed. The results showed that under low-speed conditions, the average mean square errors of the speed estimators of the simple, extended Kalman filter, and full-order magnetic flux observer were 0.7969, 0.9134, and 2.2526, respectively. The first two speed estimators had better performance, while under medium to high-speed conditions, the latter two speed estimators had a lower average mean square error and better performance. When various faults occurred, the research method could quickly determine the best performing speed estimator for feedback and effectively display the speed fluctuations caused by the faults. Finally, it smoothly switched to the speed sensorless mode and controlled the speed error within -5r/min-5r/min.
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