Fuzzy inference using piecewise polynomial interpolation and its application to model-reference fuzzy logic controller

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

A new fuzzy inference based on piecewise polynomial interpolation similar to the spline technique is proposed. The signed membership function which can encode more information than the usual membership function is also introduced and used together with this new inference method. The fuzzy system using this inference method is more compact compared to other types of fuzzy systems. The computational load when implementing this inference method is almost comparable to the singleton method even if high-order polynomial series are used. A training algorithm similar to the back-propagation algorithm is also proposed to tune these polynomials if numerical training data is available. In contrast to neural network where the trained network is only a function of training data, here, both the heuristic prior knowledge and available training data are used. A simulation example is given to show how this new fuzzy inference can be applied in a model reference closed-loop control system.

Original languageEnglish
Pages (from-to)257-270
Number of pages14
JournalFuzzy Sets and Systems
Volume118
Issue number2
DOIs
Publication statusPublished - 1 Mar 2001
Externally publishedYes

Fingerprint

Fuzzy Inference
Fuzzy Logic Controller
Polynomial Interpolation
Piecewise Polynomials
Fuzzy inference
Reference Model
Fuzzy logic
Interpolation
Polynomials
Fuzzy systems
Membership functions
Controllers
Membership Function
Fuzzy Systems
Closed loop control systems
Backpropagation algorithms
Splines
Polynomial
Training Algorithm
Back-propagation Algorithm

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems and Management
  • Statistics, Probability and Uncertainty
  • Electrical and Electronic Engineering
  • Statistics and Probability

Cite this

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