Design of sophisticated fuzzy logic controllers using genetic algorithms

Kim Chwee Ng, Yun Li

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

50 Citations (Scopus)

Abstract

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.

LanguageEnglish
Title of host publicationProceedings of 1994 IEEE 3rd International Fuzzy Systems Conference
PublisherIEEE
Pages1708-1712
Number of pages5
Volume3
ISBN (Print)078031896X
DOIs
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

Conference

ConferenceProceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3)
CityOrlando, FL, USA
Period26/06/9429/06/94

Fingerprint

Fuzzy Logic Controller
Fuzzy logic
Genetic algorithms
Genetic Algorithm
Membership Function
Controllers
Directly proportional
Control System
Fuzzy Rule Base
Trial and error
PID Controller
Membership functions
Fuzzy Controller
Controller Design
Chromosome
High Performance
Strings
Nonlinearity
Gene
Engineering

Keywords

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

Cite this

Ng, K. C., & Li, Y. (1994). Design of sophisticated fuzzy logic controllers using genetic algorithms. In Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference (Vol. 3, pp. 1708-1712). IEEE. https://doi.org/10.1109/FUZZY.1994.343598
Ng, Kim Chwee ; Li, Yun. / Design of sophisticated fuzzy logic controllers using genetic algorithms. Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference. Vol. 3 IEEE, 1994. pp. 1708-1712
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Ng, KC & Li, Y 1994, Design of sophisticated fuzzy logic controllers using genetic algorithms. in Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference. vol. 3, IEEE, pp. 1708-1712, Proceedings of the 3rd IEEE Conference on Fuzzy Systems. Part 3 (of 3), Orlando, FL, USA, 26/06/94. https://doi.org/10.1109/FUZZY.1994.343598

Design of sophisticated fuzzy logic controllers using genetic algorithms. / Ng, Kim Chwee; Li, Yun.

Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference. Vol. 3 IEEE, 1994. p. 1708-1712.

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

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Ng KC, Li Y. Design of sophisticated fuzzy logic controllers using genetic algorithms. In Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference. Vol. 3. IEEE. 1994. p. 1708-1712 https://doi.org/10.1109/FUZZY.1994.343598