Monitoring, fault diagnosis, fault-tolerant control and optimization: Data driven methods

Computers and Chemical Engineering

Volumn 47, Issue , 2012, Pages 111-120

  MacGregor, John ^a,b   Cinar, Ali ^c  

^a PROSENSUS INC   (Canada)

^b MCMASTER UNIVERSITY   (Canada)

^c Illinois Institute of Technology   (United States)

Author keywords

Agent based systems; Batch processes; Control; Fault diagnosis; Fault tolerant control; Latent variable models; Multivariate statistical process monitoring; Optimization

Indexed keywords

AGENT-BASED SYSTEMS; BATCH PROCESS; FAULT TOLERANT CONTROL; LATENT VARIABLE MODELS; MULTIVARIATE STATISTICAL PROCESS MONITORING;

BATCH DATA PROCESSING; CONTROL; DIGITAL STORAGE; FAILURE ANALYSIS; OPTIMIZATION;

FAULT DETECTION;

EID: 84869508491     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2012.06.017     Document Type: Article

References (44)

1. Christofides P.D., El-Farra N. Control of nonlinear and hybrid process systems: Designs for uncertainty, constraints, and time-delays 2005, Springer-Verlag, New York.
2. Cinar A., Palazoglu A., ayihan F. Chemical process performance evaluation 2007, CRC Press, Boca Raton.
3. Du M., Gandhi R., Mhaskar P. An integrated fault-detection and isolation and safe-parking framework for networked process systems. Industrial and Engineering Chemistry Research 2011, 50:5667.
4. El-Farra N.H., Ghantasala S. Actuator fault isolation and reconfiguration in transport-reaction processes. AIChE Journal 2007, 2007(53):1518-1520.
5. El-Farra N.H., Gani A., Christofides P.D. Fault-tolerant control of process systems using communication networks. AIChE Journal 2005, 51:1665.
6. Flores-Cerillo J., MacGregor J.F. Within-batch and batch-to-batch inferential adaptive control of semi-batch reactors: A partial least squares approach. Industrial and Engineering Chemistry Research 2003, 42:3334.
7. Frank P.M. Disturbance diagnosis in dynamic systems using analytical and knowledge-based redundancy. Automatica 1990, 26:459.
8. Gertler J.J. Fault detection and diagnosis in engineering systems 1998, Marcel Dekker, New York.
9. Garcia-Munoz S., Kourti T., MacGregor J.F. Product transfer between sites using joint-Y PLS. Chemometrics and Intelligent Laboratory Systems 2005, 79:101.
10. Garcia-Munoz S., MacGregor J.F., Neogi D., Latshaw B.E., Mehta S. Optimization of batch operating policies. Part II: Incorporating process constraints and industrial applications. Industrial and Engineering Chemistry Research 2008, 47:4202.
11. Giridhar A., El-Farra N.H. A unified framework for detection, isolation and compensation of actuator faults in uncertain particulate processes. Chemical Engineering Science 2009, 64:2963.
12. Hu Y., El-Farra N.H. Robust fault detection and monitoring of hybrid process systems with uncertain mode transitions. AIChE Journal 2011, 57:2783.
13. Huang B., Shah S.L. Performance assessment of control loops: Theory and applications 1999, Springer-Verlag, New York.
14. Jackson J.E. A user's guide to principal components 1991, John Wiley, New York.
15. Kourti T., MacGregor J.F. Multivariate SPC methods for process and product monitoring. Journal of Quality Technology 1996, 28:409.
16. Krzanowski W.J. Between-groups comparison of principal components. Journal of the American Statistical Association 1979, 74:703.
17. Kendra S.J., Cinar A. Controller performance assessment by frequency domain techniques. Journal of Process Control 1997, 7:181-194.
18. Kendra S.J., Basila M.R., Cinar A. Intelligent process control with supervisory knowledge-based systems. Methods and applications of intelligent control 1997, 139-171. Kluwer Academic Publishers, The Netherlands. S. Tzafestas (Ed.).
19. Liu Z., Bruwer M.J., MacGregor J.F., Rathore S., Reed D.E., Champagne M.J. Scale-up of a roller compaction process using JY-PLS. Industrial and Engineering Chemistry Research 2011, 50:10696-10706.
20. Maciejowski J.M., Modelling and predictive control: Enabling technologies for reconfiguration Annual Reviews in Control 1999, 23:13.
21. Mhaskar P., Gani A., McFall C., Christofides P.D., Davis J.F. Fault-tolerant control of nonlinear process systems subject to sensor faults. AIChE Journal 2007, 53:654.
22. Mhaskar P., Gani A., El-Farra N.H., McFall C., Christofides P.D., Davis J.F. Integrated fault-detection and fault-tolerant control of process systems. AIChE Journal 2006, 52:2129.
23. Muteki K., MacGregor J.F., Ueda T. On the rapid development of new polymer blends: The optimal selection of materials and blend ratios. Industrial and Engineering Chemistry Research 2006, 45:4653.
24. Muteki K., MacGregor J.F., Ueda T. Mixture designs and models for the simultaneous selection of ingredients and their ratios. Chemometrics and Intelligent Laboratory Systems 2007, 86:17.
25. Negiz A., Cinar A. Statistical monitoring of multivariable dynamic processes with state space models. AIChE Journal 1997, 43:2002-2020.
26. Nomikos P., MacGregor J.F. Monitoring of batch processes using multi-way principal components analysis. AIChE Journal 1994, 40:1361.
27. Nomikos P., MacGregor J.F. Multi-way partial least squares in monitoring batch processes. Chemometrics and Intelligent Laboratory Systems 1995, 30:97.
28. Patton R.J., Frank P.M., Clark R.N. Fault diagnosis in dynamic systems - Theory and applications 1989, Prentice Hall, Englewood Cliffs, NJ.
29. Perk S., Teymour F., Cinar A. Statistical monitoring of complex chemical processes with agent-based systems. Industrial and Engineering Chemistry Research 2010, 49:5080-5093.
30. Perk S., Teymour F., Cinar A. An adaptive agent-based system for process fault classification and diagnosis. Industrial and Engineering Chemistry Research 2011, 50:9138-9155.
31. Perk S., Shao Q.M., Teymour F., Cinar A. An adaptive fault-tolerant control framework with agent-based systems. International Journal of Robust and Nonlinear Control 2012, 22:43-67.
32. Raich A., Cinar A. Multivariate statistical methods for monitoring continuous processes: Assessment of discrimination power of disturbance models and diagnosis of multiple disturbances. Chemometrics and Intelligent Laboratory Systems 1995, 30:37-48.
33. Raich A., Cinar A. Statistical process monitoring and disturbance diagnosis in multivariable continuous processes. AIChE Journal 1996, 42:995-1009.
34. Raich A., Cinar A. Diagnosis of process disturbances by statistical distance and angle measures. Computers & Chemical Engineering 1997, 21:661-673.
35. Rawlings J.B., Stewart B.T. Coordinating multiple optimization-based controllers: New opportunities and challenges. Journal of Process Control 2008, 18:1665.
36. Schaefer J., Cinar A. Multivariable MPC system performance assessment, monitoring and diagnosis. Journal of Process Control 2004, 14:113-129.
37. Tatara E., Cinar A. An intelligent system for multivariable statistical process monitoring and diagnosis. ISA Transactions 2002, 41:255-270.
38. Undey C., Ertunc S., Cinar A. Online batch/fed-batch process performance monitoring, quality prediction, and variable-contribution analysis for diagnosis. Industrial and Engineering Chemistry Research 2003, 42:4645-4658.
39. Wang Y., Yang Y., Zhou D., Gao F. Active fault tolerant control of nonlinear batch processes with sensor faults. Industrial and Engineering Chemistry Research 2007, 46:9158.
40. Venkatasubramanian V., Rengaswamy R., Kavuri S., Yin K.A. Review of process fault detection and diagnosis. Part III: Process history based methods. Computers & Chemical Engineering 2003, 27:327.
41. Yabuki Y., Nagasawa T., MacGregor J.F. An industrial experience with product quality control in semi-batch processes. Computers & Chemical Engineering 2000, 24:585-590.
42. Yacoub F., MacGregor J.F. Product optimization and control in the latent variable space of nonlinear PLS models. Chemometrics and Intelligent Laboratory Systems 2004, 70:63.
43. Yoon S., MacGregor J.F. Relationships between statistical and causal model-based approaches to fault detection and isolation. AIChE Journal 2000, 46:1813.
44. Zumoffen D., Basualdo M. From large chemical plant data to fault diagnosis integrated to decentralized fault tolerant control: Pulp mill process application. Industrial and Engineering Chemistry Research 2008, 47:1201.