Title :
Design of a fuzzy controller for the deep drawing process by using GAs
Author :
Lorenzo, R. Di ; Perrone, G. ; La Diega, S. Noto
Author_Institution :
Dipt. di Tecnologia e Produzione Meccanica, Palermo Univ., Italy
Abstract :
Presents a genetic algorithm based approach to design a fuzzy control system for the deep drawing process. A fuzzy controller has been built up based on additive fuzzy set theory. Such a system has proved its ability to cope with the uncertainties characterising process conditions in the deep drawing operation. The knowledge base necessary to train the fuzzy controller has been obtained by finite element (FE) simulations of the process. Finally, the designed controller response has been tested proving its effectiveness
Keywords :
control system synthesis; drawing (mechanical); finite element analysis; fuzzy control; fuzzy set theory; genetic algorithms; process control; additive fuzzy set theory; deep drawing process; finite element simulations; genetic algorithm based approach; Algorithm design and analysis; Control systems; Electric variables control; Fuzzy control; Fuzzy set theory; Fuzzy systems; Genetic algorithms; Process control; Proportional control; Uncertainty;
Conference_Titel :
Knowledge-Based Intelligent Electronic Systems, 1998. Proceedings KES '98. 1998 Second International Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-4316-6
DOI :
10.1109/KES.1998.725959
