Adaptive multivariable fuzzy logic controller

Zong Mu Yeh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


This paper presents a systematic methodology to the design of a multivariable fuzzy logic controller (MFLC) for large-scale nonlinear systems. A new general method which is based on a performance index of sliding motion is used to generate a fuzzy control rule base. Reducible input variables obtained from sliding motion are adopted as input variable of the fuzzy controller and the output scale factors of the MFLC are tuned by the switching variable. Thus, the determination of the input/output scale factors becomes easier and the system performance is significantly improved. The simulation results of a Puma 560 system and a two-inverted pendulum system demonstrate that the attractive features of this proposed approach include a smaller residual error and robustness against nonlinear interactions.

Original languageEnglish
Pages (from-to)43-60
Number of pages18
JournalFuzzy Sets and Systems
Issue number1
Publication statusPublished - 1997


  • Adaptive control
  • Fuzzy control
  • Learning algorithm
  • Sliding mode

ASJC Scopus subject areas

  • Logic
  • Artificial Intelligence


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