Open AccessApplication of genetic algorithms to the adjustment of the supports of fuzzy sets in a mamdani controller
Author(s) -
M.M. Mazzucco,
Ariovaldo Bolzan,
Ricardo Miranda Barcia,
Ricardo Antônio Francisco Machado
Publication year - 2000
Publication title -
brazilian journal of chemical engineering/brazilian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.313
H-Index - 52
eISSN - 1678-4383
pISSN - 0104-6632
DOI - 10.1590/s0104-66322000000400027
Subject(s) - controller (irrigation) , fuzzy logic , fuzzy control system , computer science , fuzzy set operations , defuzzification , set (abstract data type) , variation (astronomy) , pid controller , control theory (sociology) , genetic algorithm , neuro fuzzy , fuzzy set , fuzzy classification , fuzzy number , algorithm , artificial intelligence , control (management) , control engineering , machine learning , engineering , temperature control , physics , astrophysics , agronomy , biology , programming language
The development of control systems based on fuzzy rules facilitates the solving of problems when insufficient phenomenological information is available. The most common way of grouping fuzzy rules to form a controller is known as Mamdani controller. This controller consists of a set of rules with two premises, the error and the error variation, and one conclusion, the control action variation. One of the most delicate phases of the project of fuzzy systems is the definition of the supports (range) of each fuzzy qualifiers. This work apply genetic algorithms, together with some model of the system, to the adjustment of the supports of the fuzzy sets used in a Mamdani controller. The results show that the automatic adjustment is faster and more efficient that the manual one. Finally, the results are compared with a PID that was also adjusted with genetic algorithms