TY - GEN
T1 - Finite Control Set Model Predictive Control with Kalman Filter Estimation for LCL-Type Grid-Tied Inverter
AU - Zhang, Bingtao
AU - Wu, Weimin
AU - Gao, Ning
AU - Koutroulis, Eftichios
AU - Chung, Henry Shu-Hung
AU - Blaabjerg, Frede
PY - 2021/11
Y1 - 2021/11
N2 - As one of the most effective control strategies for LCL-type grid-tied inverters (GTIs), the finite control set model predictive control (FCS-MPC) strategy can achieve accurate tracking of the reference value and handle a variety of constraints at the same time. Therefore, it has been employed in industrial applications. However, in order to achieve a better control effect, the traditional FCS-MPC requires multiple voltage and current sensors, which greatly increases the system cost. In addition, sensor failures occur frequently in practical applications, which will significantly reduce the overall performance of the system. Therefore, this paper proposes an improved FCS-MPC strategy (KFE-MPC) based on Kalman filter (KF). The proposed KFE-MPC strategy can reduce the number of sensors and improve the system's ability to resist sensor failures effectively by utilizing a Kalman filter to estimate voltage and current. A three-phase / 110V LCL-type grid-tied inverter model is established to verify the feasibility and effectiveness of the proposed control strategy.
AB - As one of the most effective control strategies for LCL-type grid-tied inverters (GTIs), the finite control set model predictive control (FCS-MPC) strategy can achieve accurate tracking of the reference value and handle a variety of constraints at the same time. Therefore, it has been employed in industrial applications. However, in order to achieve a better control effect, the traditional FCS-MPC requires multiple voltage and current sensors, which greatly increases the system cost. In addition, sensor failures occur frequently in practical applications, which will significantly reduce the overall performance of the system. Therefore, this paper proposes an improved FCS-MPC strategy (KFE-MPC) based on Kalman filter (KF). The proposed KFE-MPC strategy can reduce the number of sensors and improve the system's ability to resist sensor failures effectively by utilizing a Kalman filter to estimate voltage and current. A three-phase / 110V LCL-type grid-tied inverter model is established to verify the feasibility and effectiveness of the proposed control strategy.
KW - finite control set model predictive control (FCS-MPC)
KW - Grid-Tied inverters (GTIs)
KW - Kalman filter (KF)
UR - https://www.scopus.com/pages/publications/85125756959
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85125756959&origin=recordpage
U2 - 10.1109/PRECEDE51386.2021.9680968
DO - 10.1109/PRECEDE51386.2021.9680968
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781665425582
T3 - IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE
SP - 964
EP - 969
BT - The 6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE 2021)
PB - IEEE
T2 - 6th IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics (PRECEDE 2021)
Y2 - 20 November 2021 through 22 November 2021
ER -