An ANFIS Control Approach of a Bi-Directional Buck-Boost used for a Battery Charger

In this work, a neuro-fuzzy regulator based on ANFIS is designed for the current control of a Bidirectional Buck-Boost chopper battery charger. First, a PI regulator is used in the control loop. Data from the PI regulator is extracted and then used to train ANFIS. The performances of the two PI and neuro-fuzzy commands were evaluated under the MATLAB/SIMULINK environment. According to the simulation results, it was found that the neuro-fuzzy regulator ANFIS is more effective in improving the current response by reducing the response time. In conclusion, the neuro-fuzzy control gives a better performance compared to the PI control

A review on energy consumption in the residential and commercial buildings located in tropical regions of Indian Ocean: A case of Madagascar island

The aim of this research is to review the status and current trends on energy consumption, but also to assess the cooling energy in some buildings in Madagascar. To achieve this objective, but due to a lack of data regarding energy consumption in buildings in this region, experimental and subjective studies were carried out in 1272 residential buildings and 51 commercial buildings, distributed in 12 cities in the tropical region of Madagascar. A specific questionnaire was designed to collect these data. A total of 1323 questionnaires were distributed during dry and rainy seasons. The results showed that energy consumption varied by both function of design and occupants' behaviors. Cooling energy demand was the highest in modern buildings, while 60% of occupants found their environment uncomfortable. Good indoor air and optimal worker’s performance were watched in buildings with local materials. Although Madagascar has an important source of renewable energy, electricity production remains heavily dependent on more than 80% of fossil fuel sources