An adaptive backstepping control to ensure the stability and robustness for boost power converter in DC microgrids

• Published in: Energy reports Vol. 8; pp. 1110 - 1124
• Main Authors: Zhang, Zehua, Song, Guiying, Zhou, Jiyao, Zhang, Xiaolu, Yang, Bowei, Liu, Chang, Guerrero, Josep M.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2022; Elsevier
• Subjects: Backstepping control; Boost converter; Constant power load; DC microgrid; Extended nonlinear disturbance observer; Large signal stability; Backstepping control; DC microgrid; Boost converter; Constant power load; Large signal stability; Extended nonlinear disturbance observer
• ISSN: 2352-4847; 2352-4847
• DOI: 10.1016/j.egyr.2022.02.024

In recent years, the power electronic load infiltrates into the microgrid in the form of constant power, and its negative impedance characteristics threaten the stability of the system. To alleviate the instability caused by constant power loads (CPLs) and constant impedance loads (CILs) of the boost power converter in the DC microgrid, an adaptive backstepping control (BSC) method is designed. Firstly, based on the dynamic model of boost converter, an input voltage estimator is designed, which is introduced into backstepping control to improve the robustness to the change of input voltage. In addition, to improve the anti-interference performance of the system and ensure the static error free tracking of the output voltage, an extended nonlinear disturbance observer (ENDO) is used to compensate for the influence caused by mismatched disturbance and model uncertainty, the optimized BSC uses fewer initial parameters to ensure its operation. Finally, the large-signal stability of the proposed control is verified by using Lyapunov stability theory, which ensures the global trajectory tracking of the reference voltage and fast dynamic control. Through MATLAB simulation and hardware in the loop experiment (HIL), the proposed control is compared with BSC+NDO to verify the effectiveness and superiority of the proposed algorithm.