A Novel Passivity Model Predictive Control for Predefined-Time Feedforward Compensation in DC Microgrids Feeding Constant Power Loads

The negative incremental impedance of constant power loads (CPLs) adversely affects the stable operation of dc microgrids. On the other hand, the power electronic converter should exhibit excellent transient performance when dealing with source-load side disturbances. Hence, this article proposes an adaptive passivity model predictive controller for dc\dc boost converter feeding the CPLs of dc microgrids. First, the predefined-time nonlinear disturbance observer is designed to provide online estimation of unknown and time-varying input voltage and load power. It not only achieves free-setting upper bounds of convergence time, but also reduces sensor needs. Then, combining passivity-based and model predictive control, a composite control that adopts the advantages of both and compensates for the weaknesses of each is proposed. In addition, the proposed composite control loop avoids the complexity of needing to obtain nominal parameters and tuning of multiple-degree-of-freedom parameters, thus providing relatively simple and practical control structure. On this basis, the comprehensive system stability and controller parameter design guidelines are investigated using eigenvalue analysis and discrete-time model bifurcation diagram method. Finally, the simulation and experimental results under multiple scenarios indicate that the proposed control strategy exhibits excellent dynamic performance and robustness with less prior knowledge of the system.