Title :
GA optimisation of rule base in a fuzzy logic control of a solar power plant
Author :
Luk, P.C.K. ; Lai, L.L. ; Tong, T.L.
Author_Institution :
Dept. of Electron., Commun. & Electr. & Eng., Hertfordshire Univ., Hatfield, UK
Abstract :
A genetic algorithm (GA) is formulated to optimise the rule base of a fuzzy logic controller (FLC) in a solar power plant. The rule base embodies an empirical set of 49 `if-then´ rules. The influence of each rule is scaled by a weighting factor which is encoded in the gene of a chromosome. The entire chromosome encodes all of the 49 weighting factors. Evaluation of the fitness of the chromosome is based on the response time of the plant. Considerably improvement of plant performance is shown after some 80 generations of evolution of the chromosome
Keywords :
control system analysis; control system synthesis; fuzzy control; genetic algorithms; knowledge based systems; power station control; solar power stations; GA optimisation; chromosome; control performance; fuzzy logic control; genetic algorithm; if-then rules; response time; rule base; solar power plant; weighting factor; Biological cells; Communication system control; Delay; Fuzzy logic; Genetic algorithms; Petroleum; Power engineering and energy; Production; Solar energy; Temperature control;
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies, 2000. Proceedings. DRPT 2000. International Conference on
Conference_Location :
London
Print_ISBN :
0-7803-5902-X
DOI :
10.1109/DRPT.2000.855667
