GA optimisation using elitism in fuzzy logic control of a solar power plant

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.