TY - JOUR
T1 - Fuzzy T-S Observer Control for Maximum Power Point Tracking in PV Systems under Dynamic Weather Conditions
AU - Fernando Diaz
AU - Lucia Morales
AU - Diego Perez
AU - Valeria Soto
JF - Journal of Smart Grids, Energy Analytics and Optimization
JO - J Smart Grids Energy Anal Optim
Y1 - 2024
VL - 3
IS - 2
SP - 86
N2 - In this study, an observer-based fuzzy controller design approach is presented to enhance the efficiency and performance of a photovoltaic (PV) system. The targeted controller is developed by integrating linear matrix inequalities (LMIs). The system comprises a photovoltaic generator (PVG) linked to a boost converter, with a battery connected to the converter to store surplus energy for later utilization. A fuzzy controller incorporating a Takagi–Sugeno (T–S) fuzzy observer is proposed, ensuring predefined performance levels while achieving maximum power point tracking (MPPT) under varying weather conditions. To maintain maximum power operation, the system must follow an optimal trajectory. For this purpose, a dedicated reference fuzzy model is introduced to generate the desired trajectories. This technique enables accurate replication of the system dynamics across a wide operating range. Overall, the T–S fuzzy framework proposed in this paper aims to maximize energy recovery during battery charging under partially shaded conditions, thereby achieving higher system efficiency. The suggested approach is implemented and simulated in MATLAB/SIMULINK, with realistic reference trajectories applied while accounting for climatic variations. Simulation analysis, along with comparisons with two widely adopted methods, demonstrates that the proposed strategy successfully reduces tracking time and eliminates the oscillations typically observed around the maximum power point (MPP).
UR - https://isespub.com/e966545312
ER -