Title :
GA optimisation using elitism in fuzzy logic control of a solar power plant
Author :
Luk, Patrick C K ; Economou, John T.
Author_Institution :
Dept. of Aerosp. Power & Sensors, Cranfield Univ., Shrivenham, UK
Abstract :
A genetic algorithm (GA) using elitism is formulated to optimise the membership functions of a fuzzy logic controller (FLC) for a solar power plant. The input and output variables are represented by sets of seven fuzzy subsets on an appropriate universe of discourse. Each point of a fuzzy subset is encoded in the gene of a chromosome. Evaluation of the fitness of the chromosome is based on the response time of the plant. Considerable improvement of plant performance is shown after some 80 generations of evolution of the chromosomes.
Keywords :
encoding; fuzzy control; fuzzy set theory; genetic algorithms; solar power stations; GA optimisation; chromosome evolution; elitism; encoding; fuzzy logic controller; fuzzy subsets; genetic algorithm; membership functions; solar power plant; Biological cells; Control systems; Delay; Fuzzy logic; Fuzzy sets; Genetic algorithms; Petroleum; Production; Solar energy; Solar power generation;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1384581
