Genetic synthesis of fuzzy logic controllers in turning

Y. S. Tarng*, Z. M. Yeh, C. Y. Nian

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)


The paper presents an optimal fuzzy logic controller design using efficient robust optimization techniques called genetic algorithms. It is shown that genetic algorithms can automatically search input and output scaling factors, membership functions, and fuzzy rules of the fuzzy logic controllers based on a fitness function. As a result, fuzzy logic controllers with optimal control performance can be systematically constructed instead of using a time-consuming trial and error approach. An adaptive force control system in turning operations is then used to illustrate the proposed method. It is shown that the developed fuzzy logic controller can achieve an automatic adjustment of feed rate to optimize the production rate with a constant cutting force in turning operations.

Original languageEnglish
Pages (from-to)301-310
Number of pages10
JournalFuzzy Sets and Systems
Issue number3
Publication statusPublished - 1996


  • Engineering
  • Genetic algorithm
  • Process control
  • Turning

ASJC Scopus subject areas

  • Logic
  • Artificial Intelligence


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