Sensorless control of bearingless induction motor based on fuzzy dual sliding mode MRAS

To improve the speed estimation accuracy and robustness of Bearingless Induction Motors (BIM) in the control system, a sensorless control strategy based on a fuzzy dual sliding mode Model Reference Adaptive System (MRAS) is proposed. Two sliding mode surfaces are constructed using the flux linkage deviation between the reference model and the adjustable model based on the traditional MRAS method for speed adaptive estimation. Equivalent control is obtained through the sliding mode control algorithm, improving the original adaptive law of MRAS and thus enhances the accuracy of speed estimation. To mitigate the chattering phenomenon associated with sliding mode control, a fuzzy logic controller is designed. The states and change rates of the two sliding mode surfaces are used as inputs to dynamically adjust the sliding mode control gain parameters, resulting in the construction of a fuzzy dual sliding mode MRAS sensorless control system. Both simulation and experimental results demonstrate that the fuzzy dual sliding mode MRAS system not only enhances the rotor suspension performance of BIM but also improves speed estimation accuracy and robustness. The system's adaptability to parameter uncertainties and external disturbances is increased, enhancing the overall performance of the BIM.