Open AccessAdaptive super‐twisting sliding mode control of three‐phase power rectifiers in active front end applications
Author(s) -
Luo Wensheng,
Zhao Tongyu,
Li Xiaolei,
Wang Zhenhuan,
Wu Ligang
Publication year - 2019
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2018.6141
Subject(s) - control theory (sociology) , front and back ends , sliding mode control , phase (matter) , three phase , power (physics) , mode (computer interface) , computer science , active power filter , control engineering , engineering , ac power , control (management) , physics , electrical engineering , voltage , artificial intelligence , nonlinear system , operating system , quantum mechanics
A robust control approach for three‐phase two‐level grid‐connected power converters using an adaptive super‐twisting algorithm (ASTA) is studied. A cascaded structure of the proposed control method is employed, which consists of two control loops, the dc‐link capacitor voltage regulation loop (outer loop) and the grid phase current tracking loop (inner loop). In the outer control loop, a proportional controller using H ∞technique is considered, which is designed to regulate the dc‐link capacitor voltage to some desired value. An extended state observer used to asymptotically estimate the external disturbance is integrated into the outer control loop. For the inner control loop, two ASTA‐based controllers are implemented that force the grid phase currents to their desired values in finite time. Lyapunov analysis is provided to show the finite time convergence of the closed‐loop system. With the help of ASTA, a priori knowledge of the upper bounds of the derivative of the disturbances is not required. Illustrative simulation results in comparison with the linear proportional–integral control method are provided to demonstrate the effectiveness and robustness of the proposed ASTA, in the presence of load variation and parametric uncertainty.