Single input cerebellar model articulation controller (CMAC) based maximum power point tracking for photovoltaic system

Abstract

In this paper, a single-input cerebellar model articulation controller (CMAC)-based maximum power point tracking (MPPT) for PV system is proposed. As a type of neural network based controller with simple computation that results in fast learning, it is more suitable for hardware implementation. The single-input CMAC control system adopts two learning stages. During off-line learning stage the CMAC controller learns about the control surface of single input fuzzy logic controller (S-FLC). At the end of this stage, the CMAC controller is capable to approximate and imitate the behavior of S-FLC. Then, an on-line learning follows this process to improve the system stability. The linear interpolation is also used to improve its performance. Simulation results show that the proposed method can be used effectively to track the MPP of solar panel, provides fast response due to temperature and solar irradiation changing and has good performance at steady state.