Robust Adaptive Back-Stepping Control Approach Using Quadratic Lyapunov Functions for MMC-Based HVDC Digital Twins
Liu, L. (TU Delft Intelligent Electrical Power Grids)
Lekic, A. (TU Delft Intelligent Electrical Power Grids)
Popov, M. (TU Delft Intelligent Electrical Power Grids)
Margaria, Tiziana (editor)
Steffen, Bernhard (editor)
Due to its excellent performance, VSC-based high voltage direct current (HVDC) power systems draw significant attention. They are being heavily used in modern industrial applications, such as onshore and offshore wind farms, and for interconnection between asynchronous networks. However, the traditional proportional-integral (PI) control method is not robust enough to track the reference signal quickly and accurately during significant system disturbances. This paper proposes a robust adaptive back-stepping control (BSC) method that secures vulnerable power-electronic equipment. The adaptive BSC controller regulates the sum of capacitor energy, and the AC grid current through decoupled and closed control-loop design. The major advantage of the proposed control approach is the smooth transient response and accurate tracking ability, which is superior to classical control methods. In addition, the proposed methods have the merits of systematic and recursive design methodology and demand a low processing burden for Lyapunov functions and control laws. Moreover, the implementation particularities of the proposed approach are illustrated and verified for a power system digital twin using real-time digital simulator (RTDS).
Adaptive back-stepping control
To reference this document use:
Nonlinear robust control
Leveraging Applications of Formal Methods, Verification and Validation. Practice - 11th International Symposium, ISoLA 2022, Proceedings
11th International Symposium on Leveraging Applications of Formal Methods, Verification and Validation, ISoLA 2022, 2022-10-22 → 2022-10-30, Rhodes, Greece
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 0302-9743, 13704 LNCS
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© 2022 L. Liu, A. Lekic, M. Popov