Multiscale fuzzy system identification

Journal of Process Control

Volumn 15, Issue 7, 2005, Pages 763-770

  Nounou, Mohamed N ^a   Nounou, Hazem N ^a  

^a UNITED ARAB EMIRATES UNIVERSITY   (United Arab Emirates)

Author keywords

Multiscale models; System identification; Takagi Sugeno fuzzy models

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; DATA REDUCTION; FIR FILTERS; FUZZY CONTROL; MATHEMATICAL MODELS; SIGNAL FILTERING AND PREDICTION; SIGNAL PROCESSING; SIGNAL TO NOISE RATIO;

IDENTIFICATION MODELS; MULTISCALE MODELS; SYSTEMS IDENTIFICATION; TUKAGI-SUGENO FUZZY MODELS;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 21844465654     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jprocont.2005.03.005     Document Type: Article

References (19)

1. G.E.P. Box, and G.M. Jenkins Time Series Analysis, Forecasting and Control Revised ed. 1976 Holden-Day, McGraw-Hill Book Co. New York and Maidenhead
2. L. Ljung System Identification: Theory for Users 1987 Addison-Wesley Reading, MA
3. B.M. Wise, and N.L. Ricker Identification of finite impulse response models by principal component regression: Frequency-response properties Process Control Qual. 4 1992 77 86
4. B.S. Dayal, and J.F. McGregor Identification of finite impulse response models: Methods and Robustness issues Ind. Eng. Chem. Res. 35 1996 4078 4090
5. K.M. Passino, and S. Yurkovich Fuzzy Control 1998 Addison-Wesley Longman Menlo Park, CA
6. T. Johansen, R. Shorten, and R. Murray-Smith On the interpretation and identification of dynamic Takagi-Sugeno fuzzy models IEEE Trans. Fuzzy Syst. 8 3 2000 297 313
7. H. Ying Sufficient conditions on uniform approximation of multivariate functions by general Takagi-Sugeno fuzzy systems with linear rule consequent IEEE Trans. Man Cyber. 28 1998 515 520
8. H. Ying General SISO Takagi-Sugeno fuzzy systems with linear rule consequent are universal approximators IEEE Trans. Fuzzy Syst. 6 1998 582 587
9. H. Ying General Takagi-Sugeno fuzzy systems with simplified linear rule consequent are universal controllers J. Inf. Sci. 108 1998 91 107
10. K. Zeng, N. Zhang, and W. Xu A comparative study on sufficient conditions for Takagi-Sugeno fuzzy systems as universal approximators IEEE Trans. Fuzzy Syst. 8 6 2000 773 780
11. T. Takagi, and M. Sugeno Fuzzy Identification of systems and its application to modeling and control IEEE Trans. Syst., Man, Cyber. 15 1 1985 116 132
12. S. Palavajjhala, R. Motrad, and B. Joseph Process identification using discrete wavelet transform: Design of prefilters AIChE J. 42 3 1996 777 790
13. B.R. Bakshi Multiscale PCA with application to multivariate statistical process monitoring AIChE J. 44 7 1998 1596 1610
14. B.R. Bakshi Multiscale analysis and modeling using wavelets J. Chemom. 13 3-4 1999 415 434
15. A.N. Robertson, K.C. Park, and K.F. Alvin Extraction of impulse response data via wavelet transform for structural system identification J. Vib. Acoust. 120 1998 252 260
16. M. Nikolaou, and P. Vuthandam FIR model identification: Achieving parsimony through Kernel compression with wavelets AIChE J. 44 1 1998 141 150
17. N. Sureshbabu, and J.A. Farrell Wavelet based system identification for nonlinear control applications IEEE Trans. Autom. Control 44 2 1999 412 417
18. S.G. Mallat A theory of multiresolution signal decomposition: The wavelet representation IEEE Trans. Pattern Anal. Machine Intelligence 11 7 1989 764
19. M.N. Nounou, and B.R. Bakshi Online multiscale filtering of random and gross errors without process models AIChE J. 45 5 1999 1041 1058