A review of performance monitoring and assessment techniques for univariate and multivariate control systems

Journal of Process Control

Volumn 9, Issue 1, 1999, Pages 1-17

  Harris, T J ^a   Seppala, C T ^a   Desborough, L D ^b  

^a QUEEN S UNIVERSITY   (Canada)

^b HONEYWELL   (United States)

Author keywords

Controller performance; Minimum variance control; Multivariate systems

Indexed keywords

CONTROL SYSTEM ANALYSIS; MULTIVARIABLE CONTROL SYSTEMS; STOCHASTIC CONTROL SYSTEMS;

MULTIPLE-INPUT MULTIPLE-OUTPUT (MIMO) CONTROL SYSTEM; SINGLE-INPUT SINGLE-OUTPUT (SISO) CONTROL SYSTEM;

PROCESS CONTROL;

EID: 0033080258     PISSN: 09591524     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0959-1524(98)00031-6     Document Type: Review

References (79)

1. W.L. Bialkowski, Dreams versus reality: a view from both sides of the gap, Pulp and Paper Canada 94 (11) (1993) 19.
2. D. Ender, Process control performance: not as good as you think, Control Engineering, September (1993) 180.
3. N. Rinehart, F. Jury, How control valves impact process optimization, Hydrocarbon Processing June (1997) 53.
4. K. Åström, Computer control of a paper machine - an application of linear stochastic control theory, IBM Journal July (1967) 389.
5. W.R. DeVries, S.M. Wu, Evaluation of process control effectiveness and diagnosis of variation in paper basis weight via multivariate time series analysis, IEEE Trans. Auto. Cont. 23 (4) (1978) 702.
6. D.J. Kozub, C.E. Garcia, Monitoring and diagnosis of automated controllers in the chemical process industries, Proc. AIChE Annual Meeting, St. Louis, November 1993.
7. D.J. Kozub, Controller performance monitoring and diagnosis: experiences and challenges, AIChE Symposium Series 93 (316) (1997) 83.
8. N. Stanfelj, T.E. Marlin, J.F. MacGregor, Monitoring and diagnosing process control performance: the single-loop case, Ind. Eng. Chem. Res. 32 (1993) 301.
9. L.D. Desborough, T.J. Harris, Control performance assessment, Pulp & Paper Canada 94 (11) (1994) 441.
10. C.B. Lynch, G.A. Dumont, Control loop performance monitoring, IEEE Trans. Control Sys. Tech. 4 (2) (1996) 185.
11. P. Jofriet, C. Seppala, M. Harvey, B. Surgenor, T.J. Harris, An expert system for control loop performance, Pulp and Paper Canada 97 (1996) 207.
12. J.G. Owen, D. Read, H. Blekkenhorst, A.A. Roche, A mill prototype for automatic monitoring of control loop performance, Proc. Control Systems '96, Halifax, NS, 171.
13. B. Huang, S.L. Shah, Performance limits: practical control loop performance assessment, Proc. AIChE Annual Meeting, Chicago, November, 1996.
14. N.F. Thornhill, R. Sadowski, J.R. Davis, P. Fedenczuk, M.J. Knight, P. Prichard, D. Rothenberg, Practical experiences in refinery control loop performance assessment, Proc. UKACC '96.
15. M. Perrier, A.A. Roche, Towards mill-wide evaluation of control loop performance, Proc. Control Systems '92, Whistler, BC, 205.
16. M.L. Tyler, M. Morari, Performance monitoring of control systems using likelihood methods, Automatica 32 (1996) 1145.
17. T.J. Harris, Assessment of control loop performance, Canadian Journal of Chemical Engineering 67 (1989) 856.
18. K. Åström, Introduction to Stochastic Control Theory, Academic Press, New York, 1970.
19. G.E.P. Box, G.M. Jenkins, Time Series Analysis: Forecasting and Control, Holden-Day, Englewood Cliffs, N.J., 1976.
20. T.J. Harris, One step optimal controllers for nonsymmetric and nonquadratic cost functions, Technometrics 34 (1992) 298.
21. M. Foley, T.J. Harris, Performance and structure of H∞ controllers, Journal of Optimal Control: Applications and Methods 13 (1992) 1.
22. C. Pryor, Autocovariance and power spectrum analysis: derive new information from process data, Control Eng. 2 (1982) 103.
23. G.C. Nobleza, A.A. Roche, A.P. Croteau, Time series analysis techniques: a practical tool for mill-wide quality improvements, Pulp and Paper Canada 91 (7) (1990) 76.
24. K. Ohtsu, G. Kitagawa, Statistical analysis of the AR type ship's autopilot system, Journal of Dyn. Syst. 106 (1984) 193.
25. B.S. Dayal, J.F. MacGregor, Identification of finite impulse response models: methods and robustness issues, Ind. Eng. Chem. Res. 35 (1996) 4078.
26. L.D. Desborough, T.J. Harris, Performance assessment measures for univariate feedback control, Canadian Journal of Chemical Engineering 70 (1992) 1186.
27. N.F. Thornhill, M. Oettinger, P. Fedenczuk, Refinery-wide control loop performance assessment, submitted to Journal of Process Control. September, 1997.
28. L.G. Bergh, J.F. MacGregor, Constrained minimum variance controllers: internal model structure and robustness properties, Ind. Eng. Chem. Res. 26 (1987) 1558.
29. T.J. Harris, J.F. MacGregor, Design of multivariable linear-quadratic controllers using transfer functions, AIChE Journal 33 (1987) 1481.
30. P.P. Laurie, Cramér-Wold factorization, Applied Statistics 31 (1) (1982) 86.
31. B. Huang, S.L. Shah, K.E. Kwok, Good, bad, or optimal? Performance assessment of multivariable processes, Automatica 33 (6) (1997) 1175.
32. L.D. Desborough, T.J. Harris, Performance assessment measures for univariate feedforward/feedback control, Canadian Journal of Chemical Engineering 71 (1993) 605.
33. T.J. Harris, F. Boudreau, J.F. MacGregor, Performance assessment of multivariable feedback controllers, Automatica 32 (1996) 1505.
34. P-G. Eriksson, A.J. Isaksson, Some aspects of control loop performance monitoring. 3rd IEEE Conference on Control Applications 1994, Glasgow, Scotland, 1029.
35. A.J. Isaksson, PID controller performance assessment, Proc. Control Systems '96, Halifax, NS, p. 163.
36. D.C. Montgomery, Introduction to Statistical Quality Control. Wiley, New York, 1985.
37. T.J. Harris, W.H. Ross, Statistical process control procedures for correlated observations, Canadian Journal of Chemical Engineering 69 (1991) 48.
38. K. Åström, Assessment of achievable performance of simple feedback loops, Int. Journal of Adaptive Control and Signal Processing 3 (1991) 3.
39. S.J. Rendra, A. Cinar, Controller performance assessment by frequency domain techniques, Journal of Process Control 7 (3) (1997) 181.
40. B. Abraham, Intervention analysis and multiple time series, Biometrica 67 (1980) 73.
41. G.E.P. Box, G.C. Tiao, Intervention analysis with applications to economic and environmental problems, Journal of the American Statistical Society 70 (1975) 70.
42. L. Krishnamurthi, J. Narayan, S.P. Raj, Intervention analysis using control series and exogenous variables in a transfer function model, International Journal of Forecasting 5 (1989) 21.
43. W.W.S. Wei, Time Series Analysis: Univariate and Multivariate Methods, Addison Wesley, Redwood City, CA, 1990.
44. G.E.P. Box, W.G. Hunter, J.S. Hunter, Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building, Wiley, New York, 1978.
45. V.K. Rohatgi, An Introduction to Probability Theory and Mathematical Statistics, Wiley, New York, 1976.
46. M. Basseville, A. Benveniste, Detection of Abrupt Changes in Signals and Dynamical Systems, Springer-Verlag, Berlin, 1980.
47. R. Patton, P. Frank, R. Clark, Fault Diagnosis in Dynamic Systems: Theory and Applications, Prentice Hall, New York, 1989.
48. R.L.H. Lam, D.G. Watts, Profile summaries for ARIMA time series model parameters, Journal of Time Series Analysis 12 (1991) 225.
49. N.F. Thornhill, T. Hagglund, Detection and diagnosis of oscillation in control loops, Control. Eng. Practice 5 (10) (1997) 1343.
50. H. Wang, Z.J. Huang, S. Daley, On the use of adaptive updating rules for actuator and sensor fault diagnosis, Automatica 33 (2) (1997) 217.
51. T.Y. Miao, D.E. Seborg, A monitoring strategy for flow and pressure control loops, Proc. Asia-Pacific Conf. on Control and Measurement, Wuhan-Chongquing, China, June, 1995.
52. P.S. Fasolo, D.E. Seborg, Monitoring and fault detection for an HVAC control system, HVAC&R Research 1 (3) (1995) 177.
53. S. Bittanti, M. Campi, S.M. Savaresi, Unbiased estimation of a sinusoid in colored noise via adapted notch filters, Automatica 33 (2) (1997) 209.
54. T. Hãgglund, A control-loop performance monitor, Control Eng. Practice 5 (11) (1995) 1543.
55. R.R. Rhinehart, A watchdog for controller performance monitoring, Proc. ACC, June 1995, p. 2239.
56. T.J. Harris, C.T. Seppala, P.J. Jofriet, B.W. Surgenor, Plant-wide feedback control performance assessment using an expert system framework, Control Eng. Practice 4 (1996) 1297.
57. P.J. Jofriet, W.L. Bialkowski, Process Knowledge: The key to online monitoring of process variability and control loop performance, Proc. Control Systems '96, Halifax, NS, p. 187.
58. B. Weinstein, A sequential approach to the evaluation and optimization of control system performance, Proc. ACC, Chicago, 1992, p. 2354.
59. B. Huang, S.L. Shah, K.E. Kwok, J. Zurcher, Performance assessment of multivariate control loops on a paper machine headbox, Canadian Journal of Chemical Engineering 75 (1997) 134.
60. R.M. Miller, B. Huang. Perspectives on multivariate feedforward/feedback controller performance measures for process diagnosis, Proc. IFAC Adchem 97, Banff, Alberta, p. 435.
61. A. Vishnubhotla, S.L. Shah, B. Huang, Feedback and feedforward performance analysis of the Shell industrial closed loop data set. Proc. IFAC Adchem 97, Banff, Alberta, p. 295.
62. L. Dugard, G.C. Goodwin, X. Xianya, Automatica 20 (1984) 701.
63. G.C. Goodwin, K.S. Sin, Adaptive Filtering Prediction and Control, Prentice-Hall, Englewood Cliffs, N.J., 1984.
64. C.A. Tsiligiannis, S.A. Svoronos, Dynamic interactors in multivariable process control-I: the general time delay case, Chem. Eng. Sci. 43 (1988) 339.
65. Y. Mutho, R. Ortega, Interactor structure estimation for adaptive control of discrete-time multivariable nondecouplable systems, Automatica 29 (1993) 635.
66. M.W. Rogozinski, A.P. Paplinski, M.J. Gibbard, An algorithm for calculation of a nilpotent interactor matrix for linear multivariable systems, IEEE Trans. Auto. Control 32 (1987) 2234.
67. B. Huang, S.L. Shah, H. Fujii, Proc. Identification of the time delay/interactor matrix for MIMO systems using closed loop data, 13th IFAC World Congress, Vol. M, San Francisco, 1996, p. 355.
68. B. Huang, S.L. Shah, H. Fujii, The unitary interactor matrix and its estimation using closed loop data, Journal of Process Control 7 (3) (1997) 195.
69. T.J. Harris, J.H. Davis, An iterative method for matrix spectral factorization, SIAM Journal of Statistical and Scientific Computing 13 (1992) 531.
70. V. Kucera, Discrete Linear Control: The Polynomial Equation Approach, Wiley, New York, 1979.
71. B. Friedlander, A lattice algorithm for factoring the spectrum of a moving average process, IEEE Trans. Auto. Control AC-28 (11) (1983) 1051.
72. J. Rissanen, Algorithm for triangular decomposition of block Hankel and Toeplitz matricies with applications to factoring positive matrix polynomials, Math Comp 27 (1973) 147.
73. D.C. Youla, N.N. Kazanjian, Bauer-type factorization of positive matrices and the theory of matrix polynomials orthogonal on the unit circle, IEEE Trans. Circuits and Systems 25 (1978) 57.
74. Y. Peng, M. Kinnaert, Explicit solution to the singular LQ regulation problem, IEEE Trans. Auto. Control 37 (1992) 633.
75. S. Bittanti, P. Colaneri, M.F. Mongiovi, The spectral interactor matrix for the singular Riccatti equation, Proc. 33rd CDC 1994, p. 2165.
76. B. Huang, S.L. Shah, The role of the unitary interactor matrix in the explicit solution of the singular LQ output feedback control problem, Automatica 33 (11) (1997) 2071.
77. B. Huang, S.L. Shah, K.E. Kwok, K.E., Online control performance monitoring of MIMO processes, Proc. 1995 American Control Conference, Seattle, Washington, 1250.
78. B. Huang, S.L. Shah, Practical issues in multivariate feedback control performance assessment, Proc. IFAC Adchem 97, Banff, Alberta, p. 429.
79. P. Kesavan, J.H. Lee, Diagnostic tools for multivariable model-based control systems. To appear in IE&C Research, 1998.