On-line evolution of Takagi-Sugeno fuzzy models

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 37, Issue 16, 2004, Pages 67-72

  Angelov, Plamen ^a   Victor, José ^b,c   Dourado, António ^b   Filev, Dimitar ^d  

^a LANCASTER UNIVERSITY   (United Kingdom)

^b UNIVERSITY OF COIMBRA   (Portugal)

^c POLYTECHNIC INSTITUTE OF LEIRIA   (Portugal)

^d FORD MOTOR COMPANY   (United States)

Author keywords

Evolving Takagi Sugeno fuzzy models; Recursive clustering; RLS algorithm; Rule base evolution

Indexed keywords

FUZZY INFERENCE; VECTOR SPACES;

CHAOTIC TIME SERIES PREDICTION; EVOLVING TAKAGI-SUGENO; ON-LINE IDENTIFICATION; RECURSIVE CLUSTERING; RECURSIVE LEAST-SQUARES ESTIMATION; RLS ALGORITHMS; RULE BASE; TAKAGI SUGENO FUZZY MODELS;

CLUSTERING ALGORITHMS;

EID: 85064521344     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/S1474-6670(17)30852-2     Document Type: Conference Paper

References (9)

1. Angelov, P. (2002). Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems. Springer-Verlag, Heidelberg.
2. Angelov, P. and D. Filev (2004). An Approach to Online Identification of Takagi-Sugeno Fuzzy Models. IEEE Transactions on Systems, Man, and Cybernetics - Part B, 34(1), 484-498.
3. Angelov P., C. Xydeas and D. Filev (2004). On-line identification of MIMO evolving Takagi-Sugeno models. FUZZ-IEEE Conference, to appear.
4. Chiu, S. (1994). Fuzzy Model identification Based on Clustering Estimation. Journal of Intelligent and Fuzzy Systems, 2, 267-278.
5. Kasabov, N. and Q. Song (2002). DENFIS: Dynamic Evolving Neural-Fuzzy Inference System and Its Application for Time-Series Prediction. IEEE Transactions on Fuzzy Systems, 10(2), 144-154.
6. Victor, J. and A. Dourado (2003). Evolving Takagi-Sugeno Fuzzy Models. Technical Report, CISUC, http://cisuc.dei.uc.pt/acg/view_pub.php?id_p=760.
7. Takagi, T. and M. Sugeno (1985). Fuzzy Identification of Systems and Its Applications to Modeling and Control. IEEE Transactions on Systems, Man, and Cybernetics, 15(1), 116-132.
8. R. Yager and D. Filev (1993). Learning of Fuzzy Rules by Mountain Clustering, Proc. SPIE Conf. on Appl. of Fuzzy Logic Technology, Boston, MA, USA, 246-254.
9. Yager, R. and D. Filev (1994). Essentials of Fuzzy Modeling and Control. John Wiley, NY.