Model Predictive Control for a Voltage Sensorless Grid-Connected Inverter With LCL Filter Using Lumped Disturbance Observer

This article introduces a disturbance observer-based model predictive control (MPC) for a voltage sensorless grid-connected inverter (GCI), which minimizes the number of sensor measurements and eliminates the steady-state error by estimating the lumped disturbance in the presence of grid impedance variations. A full-state estimation and a lumped disturbance observer are obtained based on the Luenberger observer and gradient steepest descent method, respectively. A cost function, which consists of state error, is used for controller gain design. An optimal full-state observer and controller gains are obtained by solving an optimization problem based on linear matrix inequality (LMI). The discrete-time frequency responses analysis of open-loop and closed-loop systems is presented to demonstrate the filter resonance suppression. The robustness of the proposed control against grid impedance variation is analyzed through the pole-zero map approach. Simulations and experiments are conducted for a GCI under the grid impedance variation to demonstrate the theoretical analysis and the efficacy of the proposed control schemes.