Adaptive Composite Model Predictive Predictive Control for DC/DC Boost Converters Feeding CPLs

In this paper, an adaptive composite model predictive control strategy is proposed to mitigate the instability problem caused by the negative impedance characteristics of constant power loads and to enhance transient performance of the system during source-load side disturbances in DC microgrids. The proposed controller has a feedback loop consisting of adaptive proportional-integral and model predictive control for tracking the voltage reference value, and a feed-forward loop of nonlinear disturbance observer for online estimation and feed-forward compensation of the load disturbance currents, which significantly enhances the robustness of the system based on the stabilization control of the boost converter. Moreover, the large-signal stability analysis based on the mixed potential theory shows that the proposed control algorithm can ensure the large-signal stability of the controlled object when it deviates from the rated operating state due to uncertainty and when the constant power load is highly permeable. Finally, the effectiveness and superiority of the proposed control strategy is verified by HIL experiments under multiple scenarios.