# Super-Twisting Sliding Mode Control with SVR Disturbance Observer for PMSM Speed Regulation
###### 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. sliding mode control; support vector regression; machine learning; PMSM; super-twisting algorithm +
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methods have been proposed to eliminate the chattering. Selecting an appropriate switching gain for the SMC law is an effective method for chattering reduction. Another method is feedforward disturbance compensation using a disturbance observer [14]. [PERSON] [15] suggested a feedforward compensation that selects an appropriate value for switching the gain of the SMC. [PERSON] [16] designed a parameter uncertainty compensation algorithm that can simply estimate the switching gain. [PERSON] [17] proposed a proportional-switching SMC that can determine the control value without information on the exact system parameters. However, the high-frequency switching function induces a discontinuous input into the control strategies. Another effective method was proposed to eliminate the chattering phenomenon [18], and suitable reaching law was introduced as a direct method for further improving the dynamic response [19]. The discontinuous control law and frequent switching action cause a chattering phenomenon, which is an obvious disadvantage of the sliding mode control method. Many researchers have suggested different methods for solving the chattering problem. Continuous control inputs efficiently reduce the effects of chattering, preserving the sliding mode and restraining high-frequency chattering [20; 21]. Higher-order sliding mode control has been proposed as another method of chattering reduction; this eliminates the discontinuous term in the control input. The reaching law induces control law, which is used to attenuate chattering. In this study, a robust controller was designed for a speed loop through the introduction of the super-twisting algorithm reaching law (STRL). The super-twisting algorithm has an integrator that can smooth discontinuous signals. It achieves an adaptive tracking performance and reduces chattering [22]. The reaching law was used to design a speed controller for a PMSM. A PMSM sliding mode speed controller based on STRL shows a higher tracking performance and more robust characteristics of speed system than conventional PI controller. The simulation results validate the proposed method. Moreover, to overcome the uncertainties and disturbances, support vector regression-disturbance observer (SVR-DOB) is proposed. The SVR-DOB is trained with correlation data between disturbances and feedback current. Based on the trained SVR-DOB, the disturbances are estimated and compensated. In the simulation, the controller with SVR-DOB presents an improved performance compared to the control law with no observers. The main contribution of this paper is to introduce STRL-SMC and SVR-DOB that improve the speed tracking performance. We showed the chattering reduction and anti-disturbance ability of proposed methods for a PMSM system. The remainder of this paper is organized as follows: In Section 2, a dynamic model of the PMSM and SMC are introduced. STRL-SMC and SVR-DOB are presented in Section 3.