A novel continuous control set model predictive control to guarantee stability and robustness for buck power converter in DC microgrids

Abstract

In this paper, an adaptive continuous control set model predictive control (CCS-MPC) is proposed to eliminate the instability problem caused by the constant power load (CPL) in DC–DC​ buck converter applied in DC microgrids. Based on the dynamic model of energy storage elements(inductor and capacitor) in circuit, a parallel feedforward algorithm (PFA) is designed to estimate the variation of the load and input voltage. By supplying the information of the variation to the CCS-MPC controller, the large signal stability and fast recovery performance can be ensured under the existence of disturbances. To verify the control robustness of the adaptive CCS-MPC controller, the MATLAB simulations, hardware-in-loop (HIL) experiments and rapid-control-prototype (RCP) experimental results are conducted. Moreover, the comparative simulations and HIL experiments towards other nonlinear controller are conducted to investigates its dynamic performance.