Disturbance Observer-Based Model Predictive Super-Twisting Control for Soft Open Point.

This paper presents a disturbance observer-based model predictive of super-twisting control for Soft Open Point (SOP). First, with the consideration of the disturbances caused by parameter mismatches and unmodelled dynamics, a super-twisting sliding-mode observer (STO) is proposed to observe the disturbances, and the observed disturbances are introduced into the inner-loop as the compensation to improve the anti-disturbance of SOP system. Second, the outer-loop controller is designed by applying the super-twisting sliding-mode control (STC) approach to improve the dynamic performance and robustness. Third, to deal with large current harmonics by traditional model predictive control (MPC), a Three-Vector-based MPC (TV-MPC) is proposed to increase the number of voltage vectors in a sampling time. Finally, it is verified by simulations that the proposed method can reduce current harmonics, DC-side voltage setting time and improve the dynamic performance of SOP system effectively. In case of parameter mismatches, the proposed observer can observe the disturbances correctly to enhance the robustness of the SOP system. [ABSTRACT FROM AUTHOR]