Design and Hardware Realization of an Asymmetrical Fuzzy Logic-based MPPT Control for Photovoltaic Applications

Artificial intelligence technique based on fuzzy logic is increasingly used for the design of controller for maximum power point tracking (MPPT) in order to harvest maximum energy from photovoltaic (PV) generators. In this paper, a detailed analysis of the literature review of relevant works of fuzzy logic based MPPT algorithms for PV applications is elaborated first. Fuzzy Logic (FL) based MPPT techniques available in the literature are classified into three categories: An adaptive FL-based MPPT, FL combined with a classical technique (HC, InC, P&O) and FL combined with another intelligent technique (PSO, ANFIS, GA). Then a Fuzzy Logic Control (FLC) based MPPT algorithm for PV system is proposed. The FLC scheme design and rule table are presented in detail and based on the concept of asymmetric membership functions. The proposed scheme is implemented in real time using a dSPACE DS1104 board. From the experimental results, it is found that the proposed MPPT algorithm is simple, accurate and provides faster convergence to the maximum power point compared to the FL methods available in the literature.

Automated summary

This paper analyzes the literature review of fuzzy logic-based MPPT algorithms, classifying them into three categories and proposing a new FLC-based MPPT algorithm. Experimental results show that the proposed algorithm is simple, accurate, and converges faster to the maximum power point compared to methods in the literature.