Disturbance Observer-Based Robust Model Predictive Control for a Voltage Sensorless Grid-Connected Inverter With an LCL Filter

• Main Authors: Nguyen Ngoc Nam, Ngoc-Duc Nguyen, Changwoo Yoon, Young Il Lee
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Access
• Subjects: Sensorless model predictive control (MPC); disturbance observer; three-phase inverters; inductive-capacitive-inductive (LCL)
• Online Access: https://ieeexplore.ieee.org/document/9507463/

This paper proposes a disturbance observer-based robust model predictive control (MPC) for a voltage sensorless grid-connected inverter with an inductive-capacitive-inductive (LCL) filter. A full-state estimator and a grid voltage observer are designed to reduce the number of sensors. A lumped disturbance observer, considering the parameter mismatch along with the grid impedance variation, is also designed to eliminate the steady-state error. A cost function, which consists of the error state and control input, is employed in the MPC design. Based on the Lyapunov stability, the full-state observer, voltage estimation, lumped disturbance observer, and the robust controller gains are obtained by solving an optimization problem based on linear matrix inequality (LMI). A frequency response analysis of the entire system is conducted to verify the reference tracking and disturbance rejection outcomes. As a result, the state and grid voltage observer outcomes converge to the actual values as rapidly as possible. The effectiveness of the proposed control method is demonstrated in comparison with the proportional-integral (PI) approach and with a controller recently proposed in the literature. Simulation and experimental results are presented to verify the effectiveness of the proposed method under LCL parameter uncertainties and grid impedance variations.