Subspace identification of continuous time models for process fault detection and isolation

Journal of Process Control

Volumn 13, Issue 5, 2003, Pages 407-421

  Li, Weihua ^a,b   Raghavan, Harigopal ^a   Shah, Sirish ^a  

^a UNIVERSITY OF ALBERTA   (Canada)

^b MATRIKON INC   (Canada)

Author keywords

Multivariate continuous time systems; Numerical integration; Process fault detection and isolation; Subspace methods of identification

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; IDENTIFICATION (CONTROL SYSTEMS); INTEGRATION; MATHEMATICAL MODELS; OPTIMAL CONTROL SYSTEMS;

PROCESS FAULT DETECTION;

PROCESS ENGINEERING;

EID: 0037411787     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0959-1524(02)00066-5     Document Type: Article

References (29)

1. Bauer D. Order estimation for subspace methods. Automatica. 37:2001;1561-1573.
2. Chen T., Francis B. Optimal Sampled-Data Control Systems. 1995;Springer, Berlin.
3. Chou C., Johansson R., Verhaegen M. Continuous-time identification of SISO systems. IEEE Trans. Signal Processing. 47:1999;349-362.
4. Chou C., Verhaegen M. Subspace algorithms for the identification of multivariable dynamic errors-in-variables models. Automatica. 33:1997;1857-1869.
5. Chow E., Willsky A. Analytical redundancy and the design of robust failure detection systems. IEEE Trans. Auto. Cont. 29:1984;603-614.
6. Frank P. Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy - a survey and some new results. Automatica. 26:1990;459-474.
7. Ge W., Fang C. Detection of faulty components via robust observation. Int. J. Control. 47:1988;581-599.
8. J. Gertler, D. Singer, Augmented models for statistical fault isolation in complex dynamic systems, in: Proc. of the American Control Conference, 1985, pp. 317-322.
9. Gertler J., Singer D. A new structural framework for parity equation based failure detection and isolation. Automatica. 26:1990;381-388.
10. Johansson K. The quadruple-tank process. a multivariable laboratory process with an adjustable zero IEEE Trans. Cont. Sys. Tech. 8:2000;456-465.
11. Johansson R., Verhaegen M., Chou C. Stochastic theory of continuous-time state-space identification. IEEE Trans. Signal Processing. 47:1999;41-51.
12. Li W., Shah S. Structured residual vector-based approach to sensor fault detection and isolation. Journal of Process Control. 12:2002;429-443.
13. Liu B., Si J. Fault isolation filter design for linear time-invariant systems. IEEE Trans. Auto. Cont. 21:1997;704-707.
14. L. Ljung, System Identification: Theory for the User, Prentice-Hall, 1987.
15. Massoumnia M. A geometric approach to the synthesis of failure detection filter. IEEE Trans. Auto. Cont. 31:1986;1867-1888.
16. R. Middleton, G. Goodwin, Digital Control and Estimation, Prentice-Hall, 1990.
17. Moonen M., DeMoor B., Vandenberghe L., Vandewalle J. On and off-line identification of linear state-space models. Int. J. of Control. 49:1989;219-232.
18. Overschee P., De Moor B. N4SID. subspace algorithms for the identification of combined deterministic-stochastic systems Automatica. 30:1994;75-93.
19. Overschee P., De Moor B. A unifying theorem for three subspace system identification algorithms. Automatica. 31:1995;1853-1864.
20. Overschee P., De Moor B. Subspace Identification for Linear Systems-Theory, Implementation, Applications. 1996;Kluwer Academic Publisher.
21. Qin S., Li W. Detection and identification of faulty sensors in dynamic processes. AIChE J. 47:2001;1581-1593.
22. Sagara S., Zhao Z. Numerical integration approach to on-line identification of continuous-time systems. Automatica. 26:1990;63-74.
23. Verhaegen M., Dewilde P. Subspace model identification. part i: the output-error state-space model identification class of algorithms. Int. J. Control. 56:1992;1187-1210.
24. Verhaegen M., Dewilde P. Subspace model identification. part ii: analysis of the elementary output-error state-space model identification algorithm. Int. J. Control. 56:1992;1211-1241.
25. Viberg M. Subspace-based methods for the identification of linear time-invariant systems. Automatica. 31:1995;1835-1851.
26. Wang L., Gawthrop P. On the estimation of continuous transfer functions. Int. J. Control. 74:2001;889-904.
27. White J., Speyer J. Detection filter design. spectral theory and algorithms IEEE Trans. Auto. Cont. 32:1987;593-603.
28. Whitfield A., Messali N. Integral-equation approach to system identification. Int. J. Control. 45:1987;1431-1445.
29. Willsky A. A survey of design methods for failure detection in dynamic systems. Automatica. 12:1976;601-611.