Control loop performance assessment. 2. Hammerstein model approach for stiction diagnosis

Industrial and Engineering Chemistry Research

Volumn 44, Issue 17, 2005, Pages 6719-6728

  Srinivasan, Ranganathan ^a   Rengaswamy, Raghunathan ^a,d   Narasimhan, Shankar ^b   Miller, Randy ^c  

^a Clarkson University   (United States)

^b INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

^c HONEYWELL   (United States)

^d CLARKSON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONTROL LOOPS; HAMMERSTEIN MODELS; QUANTIFICATION; STICTION MODELS;

COMPUTER SIMULATION; CONTROL EQUIPMENT; IDENTIFICATION (CONTROL SYSTEMS); MATHEMATICAL MODELS; OPTIMIZATION;

STICTION;

CHEMICAL ENGINEERING;

EID: 24144473899     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie049026f     Document Type: Article

References (24)

1. Srinivasan, R.; Rengaswamy, R.; Miller, R. M. Control loop performance assessment. 1. A qualitative pattern matching approach for stiction diagnosis. Ind. Eng. Chem. Res. 2005, 44, 6708.
2. Armstrong-Hèlouvry, B.; Dupont, P.; De Wit, C. C. A survey of models, analysis tools and compensation methods for the control of machines with friction. Automatica 1994, 30 (7), 1083.
3. Narendra, K. S.; Gallman, P. G. An iterative method for the identification of hammerstein model. IEEE Trans. Autom. Control 1966, 11, 546.
4. Billings, S. A.; Fakhouri, S. Y. Nonlinear system identification using the hammerstein model. Int. J. Syst. Sci. 1979, 10 (5), 567.
5. Lakshminarayanan, S.; Shah, S. L.; Nandakumar, K. Identification of hammerstein models using multivariate statistical tools. Chem. Eng. Sci. 1995, 50, 3599.
6. Stoica, P.; Soderstorm, T. Instrumental-variable methods for identification of hammerstein systems. Int. J. Control. 1982, 35(3), 459.
7. Eskinat, E.; Johnson, S. H.; Luyben, W. L. Use of hammerstein models in identification of nonlinear systems. AIChE J. 1991, 37 (2), 255.
8. Bai, E.-W. An optimal two-stage identification algorithm for hammerstein-wiener nonlinear systems. Automatica 1998, 34, 333.
9. Stoica, P. On the convergence of an iterative algorithm used for hammerstein system identification. IEEE Trans. Autom. Control 1981, 26 (4), 967.
10. Olsson, H. Control-systems with friction. Ph.D. Dissertation, Department Automatic Control, Lund Institute of Technology, Sweden, 1996.
11. Choudhury, M. A. A. S.; Thornhill, N. F.; Shah, S. L. Modeling valve stiction. Control Eng. Pract. 2005, 13, 641.
12. McMillan, G. K. Improve control valve response. Chem Eng. Prog. 1995, 6, 76.
13. Piipponen, J. Controlling processes with nonideal valves: Tuning of loops and selction of valves. Proceedings of Control Systems, Halifax, Nova Scotia, Canada, 1996, 179-86.
14. Hagglund, T. Private communication, 2005.
15. Stenman, A.; Gustafsson, F.; Forsman, K. A segmentation-based approach for detection of stiction in control valves. Int. J. Adap. Control Signal Process. 2003, 17, 625.
16. Singhal, A.; Salsbury, T. I. A simple method for detecting valve stiction in oscillating control loops. J. Process Control. 2005, 15, 371.
17. Ljung, L. 2nd ed.; Prentice Hall: Englewood Cliffs, NJ, 1999.
18. Bai, E.-W. Decoupling the linear and nonlinear parts in in hammerstein model identification. Automatica 2004, 40, 671.
19. Bai, E.-W. Identification of linear systems with hard input nonlinearities of known structure. Automatica 2002, 38, 853.
20. Ruhe, A.; Wedin, P. Algorithms for separable nonlinear least sqaures problem. SIAM Rev. 1980, 22, 318.
21. Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Control 1974, 19, 716.
22. Forssell, U.; Ljung, L. Closed-loop identification revisited. Automatica 1999, 35, 1215.
23. Ninness, B.; Gibson, S. Quantifying the accuray of hammerstein model estimation. Automatica 2002, 38, 2037.
24. Guo, L.; Ljung, L. The role of model validation for assessing the size of unmodeled disturbance. Proceedings of the 33rd Conference on decision and control, Lake Buena Vista, FL, 1994.