Work place: LRP & LEA Labs. Electronics department, Faculty of Technology, Batna University, Chahid M.ohamed Belhadi Boukhlouf Road, Batna, Algeria
E-mail: yabdes@yahoo.fr
Website:
Research Interests: Process Control System, Robotics, Computer Vision
Biography
Abdessemed Yassine was born on January, 28th 1959 at Batna, Algeria. He carried out under-graduated studies at the University of Constantine, Algeria from 1978 till 1980 and has obtained the degree of bachelor of engineering from the university of Algiers-ENPA-Algiers, Algeria in June 1983. From 1985 till 1990 he carried out post- graduated and research studies in power electronics and real-time control of AC electrical drives.
He was awarded the PhD degree from the department of electrical engineering of the University of Bristol, Great-Britain, in January 1991. Ha has the HDR degree from the University of Batna in 2007. He has been associate lecturer during five years at the electrical department, Faculty of Engineering of Bristol. He is now an associate professor in applied electronics, power electronics and control at the Department of Electronics of Batna. He has supervised many final year graduate projects and master by research thesis in electrical engineering and applied electronics, control and robotics. He is currently supervising many doctor’s and master’s thesis in different areas of power electronics and robotics. He has published five international papers in the real-time control of mobile robots, data fusion for the mobile robots localization, fault diagnosis and tolerant control of tele-operated robot arms, and solar photovoltaic energy control. His current main research work areas are power electronics, the neuro-fuzzy logic applied to the control of mobile robots and robot arms, and vision control of robot arms. He is a member of the artificial intelligence team in Productics Research Laboratory (LRP).
By M.T. Makhloufi M.S. Khireddine Y. Abdessemed A. Boutarfa
DOI: https://doi.org/10.5815/ijisa.2014.12.03, Pub. Date: 8 Nov. 2014
Photovoltaic generation is the technique which uses photovoltaic cell to convert solar energy to electric energy. Nowadays, PV generation is developing increasingly fast as a renewable energy source. However, the disadvantage is that PV generation is intermittent because it depends considerably on weather conditions.
This paper proposes an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and solar irradiation conditions. In this paper, a simulation study of the maximum power point tracking (MPPT) for a photovoltaic system using an artificial neural network is presented. The system simulation is elaborated by combining the models established of solar PV module and a DC/DC Boost converter. Finally performance comparison between artificial neural network controller and Perturb and Observe method has been carried out which has shown the effectiveness of artificial neural networks controller to draw much energy and fast response against change in working conditions.
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