Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Block-wise Adaptive Predictive PLS using Block-wise Data Extraction

데이터 추출 과정을 적용한 Block-wise Adaptive Predictive PLS

  • 김성영 (경희대학교 환경응용화학부) ;
  • 정창복 (전남대학교 응용화학공학부) ;
  • 최수형 (전북대학교 화학공학부) ;
  • 이범석 (경희대학교 환경응용화학부)
  • Published : 2006.07.01
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Abstract

Recursive Partial Least Squares(RPLS) method has been used for processing the on-line available multivariate chemical process data and modeling adaptive prediction model for process changes. However, RPLS method is unstable in PLS model updating because RPLS method updates PLS model by merging past PLS model and new data. In this study, Adaptive Predictive Partial Least Squres(APPLS) method is suggested for more sensitive adaptation to process changes. By expanding APPLS method, block-wise Adaptive Predictive Partial Least Squares(block-wise APPLS) method is suggested for a lager scale data of chemical processes. APPLS method has been applied to predict the reactor properties and the product quality of a direct esterification reactor for polyethylene terephthalate(PTT), and block-wise APPLS method has been applied to predict the cetane number using NIR Diesel Spectra data. APPLS and block-wise APPLS methods show better prediction and updating performance than RPLS method.

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References

  1. K. Helland, H. E. Berntsen, O. S. Borgen, and H. Marten, 'Recursive algorithm for partial least squares regression,' Chemometrics and Intelligent Laboratory Systems, vol. 14, pp. 129-137, 1991 https://doi.org/10.1016/0169-7439(92)80098-O
  2. S. Qin, 'Recursive PLS algorithms for adaptive data modeling,' Computers Chem. Engng., vol. 22, no. 4/5, pp. 503-514, 1998 https://doi.org/10.1016/S0098-1354(97)00262-7
  3. P. Geladi and B. R. Kowalski, 'Partial least squares regression : A tutorial,' Analytica Chemica Acta, 185, pp. 1-17, 1986 https://doi.org/10.1016/0003-2670(86)80028-9
  4. S. Wold, 'Exponentially weighted moving principal component analysis and projection to latent structures,' Chemometrics and Intelligent Laboratory Systems, vol. 23, pp. 149-161, 1994 https://doi.org/10.1016/0169-7439(93)E0075-F
  5. N. B. Gallagher, B. M. Wise, S. W. Butler, D. D. White, and G. G. Barra, 'Development and benchmarking of multivariate stat.stical process control tools for a semiconductor etch process: improving robustness through model updating,' Proceedings of the ADCHEM 97, pp. 78-83, 1997
  6. M. J. Kim, Y.-H. Lee, and C. h. Han, 'Real-time classification of petroleum products using near-infrared spectra,' Computers Chem. Engng., vol. 24, pp. 513-517, 2000 https://doi.org/10.1016/S0098-1354(00)00522-6
  7. M. V. Garcia-Mencia, J. M. Andrade, P. Lopez-Mahia, and D. Prada, 'An empirical approach to update multivariate regression models intended for routine industrial use,' Fuel. vol. 79, pp. 1823-1832, 2000 https://doi.org/10.1016/S0016-2361(00)00046-6
  8. C. C. Felicio, L. P. Bras, J. A. Lopes, L. Cabrita, and J. C. Menezes, 'Comparison of PLS algorithms in gasoline and gas oil parameter monitoring with MIR and NIR,' Chemometrics and Intelligent Laboratory Systems. vol. 78, pp. 74-80, 2005 https://doi.org/10.1016/j.chemolab.2004.12.009
  9. 윤경우，이영학，한종훈，'블록들의 유사성을 고려한 Adaptive Block-wise PLS,' 화학공학，제41권，제5호，pp. 592-597, 2003
  10. J-Y Kim, H-Y Kim, and Y-K Yeo, 'Identification of kinetics of direct est erification reactions for PET synthesis based on a generic algorithm,' Korean J. of Chem. Eng., vol. 18, no. 4, pp. 432-441, 2001 https://doi.org/10.1007/BF02698287
  11. 강익중，정충섭，'국내 자동차용 경유의 성상과 세탄가' 화학공학，제38권，제3호， pp. 384-354，2000
  12. 최주환，정용진，최웅수，최영상，권오관，'C-NMR에 의해 결정된 탄소 유형별 구조적 조성으로부터 디이젤 연료의 세탄가의 예측에 관한 연구,' J. of Korean Ind. & Eng. Chemistry vol. 4， no. 4，pp. 709-714, 1993
  13. W. Li, H. H. Yue, S. Valle-Cervantes, and S. J. Qin, 'Recursive PCA for adaptive process monitoring,' Journal of Process Control, vol. 10, pp. 471-486, 2000 https://doi.org/10.1016/S0959-1524(00)00022-6
  14. B. S. Dayal and J. F. MacGregor, 'Recursive exponentially PLS and its application to adaptive control and prediction,' Journal of Process Control, vol. 7, no. 3, pp. 169-179, 1996
  15. X. Wang, U. Kruger, and B. Lennox, 'Recursive partial least squares algorithms for morutonng complex industrial processes,' Control Engineering Practice, vol. 11, pp. 613-632, 2003 https://doi.org/10.1016/S0967-0661(02)00096-5
  16. 김성영，이범석，정창복，최수형，'다변량 통계분석법을 이용한 PET 중합공정 중 직접 에스테르화 반응기의 거동 및 생산제품 예측' 제어 자동화 시스템공학 논문지，제11권， 제6호，pp. 550-557，2005 https://doi.org/10.5302/J.ICROS.2005.11.6.550
  17. http://www.evriwire.com/Data/SWRI/index.html