Design of sophisticated fuzzy logic controllers using genetic algorithms

Kim Chwee Ng, Yun Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

57 Citations (Scopus)


Design of fuzzy logic controllers encounters difficulties in the selection of optimized membership functions and fuzzy rule base, which is traditionally achieved by a tedious trial-and error process. This paper develops genetic algorithms for automatic design of high performance fuzzy logic controllers using sophisticated membership functions that intrinsically reflect the nonlinearities encounter in many engineering control applications. The controller design space is coded in base-7 strings (chromosomes), where each bit (gene) matches the 7 discrete fuzzy value. The developed approach is subsequently applied to design of a proportional plus integral type fuzzy controller for a nonlinear water level control system. The performance of this control system is demonstrated higher than that of a conventional PID controller. For further comparison, a fuzzy proportional plus derivative controller is also developed using this approach, the response of which is shown to present no steady-state error.

Original languageEnglish
Title of host publicationProceedings of 1994 IEEE 3rd International Fuzzy Systems Conference
Number of pages5
ISBN (Print)078031896X
Publication statusPublished - 26 Jun 1994
EventProceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3) - Orlando, FL, USA
Duration: 26 Jun 199429 Jun 1994


ConferenceProceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3)
CityOrlando, FL, USA


  • fuzzy control
  • control system synthesis
  • genetic algorithms
  • level control
  • two-term control,
  • control nonlinearities
  • nonlinear control systems


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