Abstract
Aiming at the problems of severe chattering and difficulty in low-speed operation of the surface-mounted permanent magnet synchronous motor (SPMSM) sensor-less speed control system based on the traditional sliding mode observer (SMO), this paper proposes a sensor-less control strategy of supertwisting sliding mode observer based on adaptive feedback gain (AFG-STA-SMO). This strategy combines the supertwisting algorithm (STA) with the equivalent feedback principle and designs an adaptive law to compensate for the rotor position error by adjusting the feedback gain coefficient online. Secondly, considering the ripple component in the back electromotive force (back-EMF), the Kalman filter gets a smoother back-EMF signal, further improving the rotor position estimation accuracy. The stability of the system is proved by using the Lyapunov function. Finally, the feasibility and effectiveness of the proposed control strategy are verified by MATLAB/Simulink simulation.
Highlights
Surface-mounted permanent magnet synchronous motor has a small size, high power density, high efficiency, low rotor loss, and solid environmental adaptability [1,2,3,4]
Accurate rotor position information can be obtained at all speeds, including zero speed, but it is only applicable to the built-in motor with much noise
In order to retain the advantages of the equivalent feedback sliding mode observer (SMO) and avoid using a lowpass filter (LPF), a new sliding mode speed sensor-less control method was designed in literature [23]
Summary
Surface-mounted permanent magnet synchronous motor has a small size, high power density, high efficiency, low rotor loss, and solid environmental adaptability [1,2,3,4]. The literature [16,17,18] proposed an SMO based on the supertwisting algorithm to observe back-EMF to solve this problem This method can effectively suppress the chattering phenomenon caused by the switching function, and a good control effect can be Journal of Sensors obtained in the medium and high-speed range. Based on the equivalent feedback sliding mode observer, a feedback gain adaptive algorithm is proposed in the literature [20, 21] to realize the rotor angle compensation at different speeds This method still needs to introduce an LPF and compensate for the rotor position delay, which increases the complexity of the system. The Kalman filter is used to filter out the ripple component in the back-EMF and further improve the sensor-less control precision; the Lyapunov function analyzes the system’s stability
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