An approach to online identification of Takagi-Sugeno fuzzy models

  title={An approach to online identification of Takagi-Sugeno fuzzy models},
  author={P. Angelov and D. P. Filev},
  journal={IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)},
An approach to the online learning of Takagi-Sugeno (TS) type models is proposed in the paper. It is based on a novel learning algorithm that recursively updates TS model structure and parameters by combining supervised and unsupervised learning. The rule-base and parameters of the TS model continually evolve by adding new rules with more summarization power and by modifying existing rules and parameters. In this way, the rule-base structure is inherited and up-dated when new data become… CONTINUE READING
Highly Influential
This paper has highly influenced 114 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 758 citations. REVIEW CITATIONS
396 Citations
42 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 396 extracted citations

758 Citations

Citations per Year
Semantic Scholar estimates that this publication has 758 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 42 references

Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems

  • P. P. Angelov
  • Heidelberg, Germany: Springer-Verlag
  • 2002
Highly Influential
7 Excerpts

Rule-base guided adaptation for mode detection in process control,

  • D. P. Filev
  • Proc. Joint 9th IFSA World Congr./20th NAFIPS…
  • 2001
Highly Influential
6 Excerpts

Intelligent control for automotive manufacturing-rule based guided adaptation,

  • D. P. Filev, T. Larsson, L. Ma
  • in Proc. IEEE Conf. IECON’00,
  • 2000
Highly Influential
6 Excerpts

Similar Papers

Loading similar papers…