Fast Fixed-Time Model Predictive Large-Signal Stabilization for DC/DC Boost Converters in DC Microgrids Feeding Constant Power Loads

The dc/dc boost converter has been widely used in dc microgrids. However, the negative incremental impedance of constant power loads (CPLs) threats system stability margins. Besides, it should exhibit satisfactory control performance when facing source-load disturbances. To this end, this article proposes a novel model predictive controller (MPC) for dc/dc boost converter feeding CPLs to optimize steady-state and transient performance within global range. First, the fixed-time disturbance observer is constructed for estimating unknown and time-varying input voltage and output power within fixed time, while eliminate source-load coupling of coordinate transformation. Second, the receding horizon optimization problem is solved offline based on dual estimation variables, which leads to a robust nonlinear MPC scheme. Then, fixed-time control algorithm was first introduced into MPC framework by correcting the reference trajectory to yield fast fixed-time MPC (FFxTMPC). Moreover, a rigorous Lyapunov is proposed to verify fixed-time global stabilization of FFxTMPC irrespective the initial state of system, while the eigenvalue method is used to investigate the parameter sensitivity. Finally, to validate the feasibility and superiority of proposed control, various case studies are tested through simulations and experiments.