A Parameter Identification Method for Robust Model Predictive Control of Virtual Synchronous Generator Based on Two Sliding Mode Observers

The conventional model predictive control (MPC) method for virtual synchronous generator (VSG) is sensitive to the parameter uncertain changes, resulting in poor voltage control performance. To solve this problem, in this paper, a parameter identification method for robust MPC of VSG based on two sliding mode observers is proposed. In this paper, the theories of the VSG as well as the MPC are first reviewed. Next, based on the mathematical model of the inverter with a LC filter, a current sliding mode observer and a voltage sliding mode observer are designed. Then, by analyzing the parameter sensitivity of the proposed current and voltage sliding mode observer to the filter capacitance and inductance, a capacitance as well as an inductance closed-loop identification method are designed using proportional-integral controller. Eventually, dynamic state experimental studies are con-ducted, which verify the effectiveness of proposed parameter identification method and the parameter identification-based robust MPC method for VSG.