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

Autor: Nguyen Ngoc Nam, Ngoc-Duc Nguyen, Changwoo Yoon, Young Il Lee
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: IEEE Access, Vol 9, Pp 109793-109805 (2021)
Druh dokumentu: article
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2021.3102628
Popis: 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.
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