Super-Twisting Sliding Mode Control with SVR Disturbance Observer for PMSM Speed Regulation
Source abstract
Abstract
Sliding mode control and disturbance compensation techniques are applied to a nonlinear speed control algorithm for a permanent magnet synchronous motor (PMSM). Optimizing the speed control performance of PMSM systems with various disturbances and uncertainties is challenging. To achieve a satisfactory performance, a sliding mode control method based on the super-twisting algorithm reaching law (STRL) is presented. STRL can adapt dynamically to the variations of a controlled system. The STRL maintains a high tracking performance of the controller and allows the control input to eliminate chattering. To estimate the uncertainties and compensate for disturbances, a support vector regression-disturbance observer (SVR-DOB) is presented. The estimated uncertainties were used to minimize modeling errors and improve the disturbance rejection. A controller using SVR-DOB achieves a high precision, and the simulation results demonstrated the validity of the proposed control approach.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Sensorless Control of Electric Motors · Iterative Learning Control Systems · Magnetic Bearings and Levitation Dynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea
Department of Smart Fab. Technology, Sungkyunkwan University, Suwon 16419, Korea
Funding
National Research Foundation of Korea
References (29)
Show source-provided references
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