A new T-S fuzzy-modeling approach to identify a boiler-turbine system

Expert Systems with Applications

Volumn 37, Issue 3, 2010, Pages 2214-2221

  Li, Chaoshun ^a   Zhou, Jianzhong ^a   Li, Qingqing ^a   An, Xueli ^a   Xiang, Xiuqiao ^a  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Boiler turbine; Fuzzy c regressive model; Fuzzy model; System identification

Indexed keywords

BOILER TURBINE SYSTEM; FUZZY C-REGRESSION MODELS; FUZZY C-REGRESSIVE MODEL; FUZZY MODEL; FUZZY MODELING; FUZZY STRUCTURES; MODELING APPROACH; NEW APPROACHES; ORTHOGONAL LEAST SQUARES; SIMULATION EXAMPLE; SYSTEM IDENTIFICATION; T-S FUZZY;

BOILERS; CLUSTERING ALGORITHMS; ENGINES; IDENTIFICATION (CONTROL SYSTEMS); NONLINEAR SYSTEMS; PREDICTIVE CONTROL SYSTEMS; REGRESSION ANALYSIS; STEAM TURBINES; TURBINE RINGS;

SIMULATORS;

EID: 70449519150     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2009.07.052     Document Type: Article

References (27)

1. Bagis A. Fuzzy rule base design using tabu search algorithm for nonlinear system modeling. ISA Transactions 47 1 (2008) 32-44
2. Box G.E.P., and Jenkins G.M. Time series analysis, forecasting and control (1970), Holden Day, San Francisco, CA
3. Chen J.Q., Xi Y.G., and Zhang Z.J. A clustering algorithm for fuzzy model identification. Fuzzy Sets and Systems 98 (1998) 319-329
4. Chiang J.H., and Hao P.Y. Support vector learning mechanism for fuzzy modeling: A new approach. IEEE Transactions on Fuzzy Systems 12 (2004) 1-12
5. Chiu S. Selecting input variables for fuzzy models. Journal of Intelligent and Fuzzy Systems 4 (1996) 243-256
6. Deng L.C., Wang G.J., Chen H., et al. Fuzzy identification on inverse dynamic process of steam temperature object of boiler [J]. Proceedings of the CSEE 27 20 (2007) 76-80 (in Chinese)
7. Evsukoff A., Branco A.C.S., and Galichet S. Structure identification and parameter optimization for non-linear fuzzy modeling. Fuzzy Sets Systems 132 (2002) 173-188
8. Hathaway R.J., and Bezdek J.C. Switching regression models and fuzzy clustering. IEEE Transactions on Fuzzy Systems 1 3 (1993) 195-204
9. Kim E., Lee H., Park M., and Park M. A simply identified Sugeno-type fuzzy model via double clustering. Information Science 110 (1998) 25-39
10. Kim E., Park M., Ji S., and Park M. A new approach to fuzzy modeling. IEEE Transactions on Fuzzy Systems 5 3 (1997) 328-337
11. Kim E., Park M., Kim S., and Park M. A transformed input-domain approach to fuzzy modeling. IEEE Transactions on Fuzzy Systems 6 (1998) 596-604
12. Kroll A. Identification of functional fuzzy models using multidimensional reference fuzzy sets. Fuzzy Sets and Systems 80 (1996) 149-158
13. Kung C.C., and Su J.Y. Affine Takagi-Sugeno fuzzy modelling algorithm by fuzzy c-regression models clustering with a novel cluster validity criterion. IET Control Theory Applications 1 5 (2007) 1255-1265
14. Li, C. S., Zhou, J. Z., An, X. L., et al. (2008). T-S fuzzy model identification based on chaos optimization. In Proceedings of ISNN (pp. 786-795).
15. Lin Y., and Cunningham G.A. A new approach to fuzzy-neural modeling. IEEE Transactions on Fuzzy Systems 3 (1995) 190-197
16. Liu, J. Z., Chen, Y. Q., Zeng, D. L., et al. (2002). Identification of a boiler-turbine system using T-S fuzzy model. In Proceedings of IEEE Tencon, Beijing (pp. 1278-1281).
17. Malay K.P., Sanghamitra B., and Ujjwal M. A study of some fuzzy cluster validity indices, genetic clustering and application to pixel classification [J]. Fuzzy Sets and Systems 155 (2005) 191-214
18. Nakamori Y., and Ryoke M. Identification of fuzzy prediction models through hyper-ellipsoidal clustering. IEEE Transactions on Systems Man and Cybernetics 24 (1994) 1153-1173
19. Pedrycz W. An identification algorithm in fuzzy relational systems. Fuzzy Sets Systems 13 (1984) 153-167
20. Sugeno M., and Yasukawa T. A fuzzy-logic-based approach to qualitative modeling. IEEE Transactions on Fuzzy Systems 1 (1993) 7-31
21. Takagi T., and Sugeno M. Fuzzy identification of systems and its applications to modeling and control. IEEE Transactions on Systems Man and Cybernetics 15 (1985) 116-132
22. Tong R.M. The evaluation of fuzzy models derived from experimental data. Fuzzy Sets Systems 4 (1980) 1-12
23. Tsekouras G.E. On the use of the weighted fuzzy c-means in fuzzy modeling. Advances in Engineering Software 36 5 (2005) 287-300
24. Wang L.X., and Mendel J.M. Fuzzy basis functions, universal approximation, and orthogonal least squares learning. IEEE Transactions on Neural Networks 3 (1992) 807-814
25. Wang Y., Rong G., and Wang S. Hybrid fuzzy modeling of chemical processes. Fuzzy Sets and Systems 130 (2002) 265-275
26. Xu C.W., and Lu Y.Z. Fuzzy model identification and self-learning for dynamic systems. IEEE Transactions on Systems Man and Cybernetics 17 (1987) 683-689
27. Zhu H.X., Shen J., and Li Y.G. A novel dynamic clustering algorithm and its application in fuzzy modeling for thermal processes [J]. Proceedings of the CSEE 25 7 (2005) 34-40 (in Chinese)