Maximum Power Point Tracking Using FLC Tuned with GA
The pursuit of the MPPT has led to the development of many kinds of controllers, one of which is the Fuzzy Logic controller, which has proven its worth. To further tune this controller this paper will discuss and analyze the use of Genetic Algorithms to tune the Fuzzy Logic Controller. It will provide an introduction to both systems, and test their compatibility and performance.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1338182Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2365
 Quang, M. H. (2013). Optimisation de la production de l'électricitérenouvelable pour site isolé. Reims: University Reims.
 Bodenhofer, U. (1996). Tuning Of Fuzzy Systems.austria.
 CAO.Y. J, Q. (1999). Teaching genetic algorithm using MATLAB. Manchester: Int. J. Elect. Enging. Educ.
 Jun Srisutapan, B. K. (2001). Fuzzy Logic and Genetic Algorithm for optimizing the approximate match of rules based on backpropagation neural networks. IEEE.
 K.Rajangam, V. P. (2012). Fuzzy logic controlled genetic algorithm to solve the economic load dispatch for thermal power station.European Scientific Journal, 172-184.