INVESTIGADORES
ACOSTA Gerardo Gabriel
artículos
Título:
Genetic Algorithms and Fuzzy Control: a practical synergism for industrial applications
Autor/es:
ACOSTA, GERARDO G.; TODOROVICH, E.
Revista:
COMPUTERS IN INDUSTRY
Editorial:
Elsevier
Referencias:
Lugar: Amsterdam, The Netherlands; Año: 2003 vol. 52 p. 183 - 195
ISSN:
0166-3615
Resumen:
A way to automatically generate fuzzy controllers (FCs) that are optimized according to a merit figure is presented in thisarticle. To achieve this task, a procedure based on hierarchical genetic algorithms (HGA) was developed. This procedure and themanner in which fuzzy controllers are codified into chromosomes is described. Resorting to this tool, several fuzzy controllerswere constructed. The best three solutions obtained during simulation were selected for testing using an experimental prototype,which consists of an induction motor of variable load. These preliminary results are also included in the report. Based on theseresults, it is concluded that hierarchical genetic algorithms, though not the only, is a suitable artificial intelligence technique toface the problem of setting a fuzzy controller in a control loop without previous experience in controlling the plant. This is ofhelp in many situations at industrial environments.
