Control performance assessment for block-oriented nonlinear systems

2010 8th IEEE International Conference on Control and Automation, ICCA 2010

Volumn , Issue , 2010, Pages 1151-1156

  Yu, Wei ^a   Wilson, David ^b   Young, Brent ^a  

^a UNIVERSITY OF AUCKLAND   (New Zealand)

^b AUCKLAND UNIVERSITY OF TECHNOLOGY   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

BLOCK-ORIENTED NONLINEAR MODELS; CONTROL PERFORMANCE ASSESSMENT; FEEDBACK CONTROL LOOPS; LOWER BOUNDS; MINIMUM VARIANCE; SEMIPARAMETRIC; SIMULATION EXAMPLE;

LINEAR SYSTEMS; NONLINEAR SYSTEMS;

QUALITY CONTROL;

EID: 77957859801     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCA.2010.5524173     Document Type: Conference Paper

References (35)

1. T.J. Harris and W. Yu. Controller assessment for a class of nonlinear systems. J Prcess Control, 17:607-619,2007.
2. Wei Yu, David I. Wilson, and Brent R. Young. Control performance assessment in the presence of valve stiction. In K. Grigoriadis, editor, The Eleventh IASTED Interational Conference on Intelligent Systems and Contrl, ISC 2008, pages 379-384, Orlando, Florida, USA, 16-18 November 2008.
3. Wei Yu, David I. Wilson, and Brent R. Young. Eliminating Valve Stiction Nonlinearities for Control Performance Assessment. In Interational Symposium on Advanced Control of Chemical Processes ADCHEM 2009, pages 526-531, Istanbul, Trkey, 12-15 July 2009. Interational Federation of Automatic Control.
4. W. L. Bialkowski. Dreams versus reality: A view from both sides of the gap. Pulp & Paper Canada, 94(11):19, 1998.
5. L. Desborough and R. Miller. Increasing customer value of industrial control performance monitoring: Honeywells experience. In AIChE Symposium Series, volume 98, pages 153-186, 2002.
6. S. Joe Qin. Control performance monitoring - A review and assessment. Computers in Chemical Engineering, 23(2):173-186,1998.
7. T.J. Harris. A review of performance monitoring and assessment techniques for univariate and multivariate control systems. J Process Control, 9(1):1-17, 1999.
8. B. Huang and S.L. Shah. Perorance Assessment of Control Loops: Theor and Applications. Springer,1999.
9. M. Jelali. An overview of control performance assessment technology and industrial applications. Control Engineering Practice, 14(5):441-466, 2006.
10. W. Yu, D.I. Wilson, and B.R. Young. Nonlinear control performance assessment in the presence of valve stiction. Submitted, 2009.
11. R. Harber and H. Unbehauen. Structural identification of nonlinear dynamic systems - A survey on input/output approaches. Automatica, 26(4):651-677, 1990.
12. G. Hashcmacher and W. Marquardt. A multi-variate Hammerstein model for process with input directionality. Journal of Process Control, 17:539-550,2007.
13. E. Eskinat, S.H. Johnson, and W.L. Luyben. Use of Hammer-stein models in identifcation of nonlinear systems. AlChE Journal, 37(2):255-268, 1991.
14. S.N. Jyothi and M. Chidambaram. Identificaiton of Hammerstein model for bioreactors with inpout multiplicityes. Bioprocess Engineering, 23:323-326, 2000.
15. K. Hunt, M. Munih, N. Donaldson, and F. Barr. Investigation of the Hammerstein hypothesis in the modelling of electrically stimulated muscle. IEEE Trans. Biomed. Eng., 8:998-1009, 1998.
16. H. Bloemen, C. Chou, T. van den Boom, V. Verdult, M. Verhaegen, and T. Backx. Wiener model identification and predictive control for dual composition control of a distillation column. J. Process Control, 11:601-620, 2001.
17. Q. Zheng and E. Zafiriou. Volterra-Laguerre models for nonlinear process identification with appliation to a fluid cracker unit. Industrial and Enginnering Chemistr Researh, 43:340-348, 2004.
18. S. Norquy, A. Palazoglu, and J. Romagnoli. Application of Wiener model predictive control (WMPC) to a pH neutralization experiment. IEEE Trans. Control Syst. Technol., 7:437-445,1999.
19. J.C. Gomez and E. Baeyens. Identification of block-oriented nonlinear systems using orthonormal bases. Journal of Process Control, 14:685-697, 2004.
20. I.W. Hunter and M.J. Korenberg. The identification of nonlinear biological systems: Wiener and Hammerstein cascade models. Biological Cyberetics, 55:134-144, 1986.
21. Y.K. Zhang and E.W. Bai. Simulation of spring discharge from a limestone aquifer in Iowa. Hydrogeol. J., 4:41-54, 1996.
22. G. R. Averin. The Hammerstein-Wiener Model for Iden-tification of Stochastic Systems. Autom. Remote Control, 64(9):1418-1431, 2003.
23. S.W. Sung, C.H. Je, J. Lee, and D.H. Lee. Improved system identificaiton method for Hammerstein-Wiener processes. Korean J Chem. Eng., 25:631-636, 2008.
24. J. Schoukens, R. Pintelon, and M. Enqvis. Study of the LTI relations between the outputs of two coupled Wiener systems and its application to the generation of initial estimates for Wiener-Hammerstein systems. Automatica, 7:1654-1665, 2008.
25. R. K. Pearson. Discrete-Time Dynamic Models. Oxford University Press, New York,1999.
26. K. J. Åström. Intrduction to Stochastic Control Theory. Academic Press, New York,1970.
27. G. E. P. Box and G. M. Jenkins. Time Series Analysis Forecasting and Contrl. Holden-Day, San Francisco,1970.
28. M. J. Grimble. Non-linear generalized minimum variance feedback, feedforward and tracking control. Automatica, 41:957-969, 2005.
29. Wei Yu, David I. Wilson, and Brent R. Young. Nonlinear Control Performance Assessment in the Presence of Valve Stiction. J Prcess Control, August 2009. Submitted.
30. F. Ding and T. Chen. Identificaiton of Hammerstein nonlinear ARMAX system. Automatica, 41:1479-1489,2005.
31. A. Billings and S.Y. Fakhouri. Identification of a class of nonlinear systems using the Wiener model. Electrnics Letters, 13:502-504,1978.
32. L. Ljung. "System Identification Toolbox 7: User's Guide". "The MathWorks",2009.
33. C. De Boor. A practical guide to splines. Springer-Verlag, New York, 1978.
34. C.H. Reinsch. Smoothing by spline fnctions. II. Numerische Mathematik, 16(5):451-4, 1971.
35. Melvin J. Hinich. Testing for Gaussianity and linearity of a stationary time series. Journal of Time Series Analysis, 3(13):169-176, 1982.