Parameter Adaptive Control of the Virtual DC Machine Based on Sigmoid Function

Due to the lack of inertia and damping in DC microgrids, virtual DC machine (VDCM) control is applied to DC converters to enhance the ability of the bus voltage to suppress fluctuations. However, the conventional VDCM adopts fixed parameters, which makes it more difficult for the system to achieve good dynamic performance while obtaining inertia and damping support. To address this problem, a parameter adaptive control based on the sigmoid function is proposed in this paper. By establishing the connection between the rate of voltage change and the control parameter, an adaptive sigmoid function is designed so that the parameter can be adjusted more smoothly and adaptively in the case of power fluctuations. Simulations and experimental results show that the proposed control achieves smaller voltage drop and shorter recovery time compared with the conventional VDCM control.