Skip to main content
Log in

Actuator fault monitoring and fault tolerant control in distillation columns

  • Research Article
  • Published:
International Journal of Automation and Computing Aims and scope Submit manuscript

Abstract

This paper presents, from a practical viewpoint, an investigation of real-time actuator fault detection, propagation and accommodation in distillation columns. Addressing faults in industrial processes, coupled with the growing demand for higher performance, improved safety and reliability necessitates implementation of less complex alternative control strategies in the events of malfunctions in actuators, sensors and or other system components. This work demonstrates frugality in the design and implementation of fault tolerant control system by integrating fault detection and diagnosis techniques with simple active restructurable feedback controllers and with backup feedback signals and switchable reference points to accommodate actuator fault in distillation columns based on a priori assessed control structures. A multivariate statistical process monitoring based fault detection and diagnosis technique through dynamic principal components analysis is integrated with one-point control or alternative control structure for prompt and effective fault detection, isolation and accommodation. The work also investigates effects of disturbances on fault propagation and detection. Specifically, the reflux and vapor boil-up control strategy used for a binary distillation column during normal operation is switched to one point control of the more valued product by utilizing the remaining healthy actuator. The proposed approach was implemented on two distillation processes: a simulated methanol-water separation column and the benchmark Shell standard heavy oil fractionation process to assess its effectiveness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Bureau of Labor Statistics. Occupational injuries and illnesses in the United States by Industry, Washington, USA: Government Printing Office, 1990.

  2. McGraw-Hill Economics. Survey of Investment in Employee Safety and Health, 13th ed., NY, USA: McGraw-Hill Publishing Co., 1985.

  3. National Safety Council. Injury Facts, 1999 Edition, Chicago, USA: National Safety Council, 1999.

  4. V. Venkatasubramanian, R. Rengaswamy, K. Yin, S. N. Kavuri. A review of process fault detection and diagnosis: Part I: Quantitative model-based methods. Computers and Chemical Engineering, vol. 27, no. 3, pp. 293–311, 2003.

    Article  Google Scholar 

  5. R. Isermann. Fault diagnosis of machines via parameter estimation and knowledge processing–Tutorial paper. Automatica, vol. 29, no. 4, pp. 815–835, 1993.

    Article  MathSciNet  MATH  Google Scholar 

  6. V. Venkatasubramanian, R. Rengaswamy, S. N. Kavuri. A review of process fault detection and diagnosis: Part II: Qualitative models and search strategies. Computers and Chemical Engineering, vol. 27, no. 3, pp. 313–326, 2003.

    Article  Google Scholar 

  7. R. C. Arkin, G. Vachtsevanos. Qualitative fault propagation in complex systems. In Proceedings of the 29th IEEE Conference on Decision and Control, IEEE, Honolulu, USA, pp. 1509–1510, 1990.

    Chapter  Google Scholar 

  8. V. Venkatasubramanian, R. Rengaswamy, S. N. Kavuri, K. W. Yin. A review of process fault detection and diagnosis: Part III: Process history based methods. Computers and Chemical Engineering, vol. 27, no. 3, pp. 327–346, 2003.

    Article  Google Scholar 

  9. J. Zhang. Improved on-line process fault diagnosis through information fusion in multiple neural networks. Computers and Chemical Engineering, vol. 30, no. 3, pp. 558–571, 2006.

    Article  Google Scholar 

  10. Y. Chetouani. Model selection and fault detection approach based on Bayes decision theory: Application to changes detection problem in a distillation column. Process Safety and Environmental Protection, vol. 92, no. 3, pp. 215–223, 2014.

    Article  Google Scholar 

  11. Y. D. Shu, J. S. Zhao. Fault diagnosis of chemical processes using artificial immune system with vaccine transplant. Industrial and Engineering Chemistry Research, vol. 55, no. 12, pp. 3360–3371, 2016.

    Article  Google Scholar 

  12. C. H. Zhao, W. D. Zhang. Reconstruction based fault diagnosis using concurrent phase partition and analysis of relative changes for multiphase batch processes with limited fault batches. Chemometrics and Intelligent Laboratory Systems, vol. 130, pp. 135–150, 2014.

    Article  Google Scholar 

  13. J. Yu, J. Y. Chen, M. M. Rashid. Multiway independent component analysis mixture model and mutual information based fault detection and diagnosis approach of multiphase batch processes. AIChE Journal, vol. 59, no. 8, pp. 2761–2779, 2013.

    Article  Google Scholar 

  14. F. Harrou, M. N. Nounou, H. N. Nounou, M. Madakyaru. PLS-based EWMA fault detection strategy for process monitoring. Journal of Loss Prevention in the Process Industries, vol. 36, pp. 108–119, 2015.

    Article  Google Scholar 

  15. Y. M. Zhang, J. Jiang. Bibliographical review on reconfigurable fault-tolerant control systems. Annual Review in Control, vol. 32, no. 2, pp. 229–252, 2008.

    Article  Google Scholar 

  16. D. Chilin, J. F. Liu, D. Muñoz de la Peña, P. D. Chritofides, J. F. Davis. Detection, isolation and handling of actuator faults in distributed model predictive control systems. Journal of Process Control, vol. 20, no. 9, pp. 1059–1075, 2010.

    Article  Google Scholar 

  17. D. Chilin, J. F. Liu, J. F. Davis, P. D. Christofides. Data-based monitoring and reconfiguration of a distributed model predictive control system. International Journal of Robust and Nonlinear Control, vol. 22, no. 1, pp. 68–88, 2012.

    Article  MathSciNet  MATH  Google Scholar 

  18. A. Mirzaee, K. Salahshoor. Fault diagnosis and accommodation of nonlinear systems based on multiple-model adaptive unscented Kalman filter and switched MPC and Hinfinity loop-shaping controller. Journal of Process Control, vol. 22, no. 3, pp. 626–634, 2012.

    Article  Google Scholar 

  19. L. F. Lao, M. Ellis, P. D. Christofides. Proactive faulttolerant model predictive control. AIChE Journal, vol. 59, no. 8, pp. 2810–2820, 2013.

    Article  Google Scholar 

  20. J. MacGregor, A. Cinar. Monitoring, fault diagnosis, faulttolerant control and optimization: Data driven methods. Computer and Chemical Engineering, vol. 47, pp. 111–120, 2012.

    Article  Google Scholar 

  21. J. Love. Process Automation Handbook: A Guide to Theory and Practice, London, UK: Springer-Verlag, pp. 243–260, 2007.

    MATH  Google Scholar 

  22. T. E. Marlin. Process Control: Designing Processes and Control Systems for Dynamic Performance, 2nd ed., New York, USA: McGraw Hill, 2000.

    Google Scholar 

  23. W. L. Luyben. Practical Distillation Control, New York, USA: Springer, 1992.

    Google Scholar 

  24. P. B. Deshpande. Distillation Dynamics and Control. Carolina, USA: ISA, 1985.

    Google Scholar 

  25. J. Zhang, R. Agustriyanto. Multivariable inferential feedforward control. Industrial and Engineering Chemistry Research, vol. 42, no. 18, pp. 4186–4197, 2003.

    Article  Google Scholar 

  26. M. T. Tham, F. Vagi, A. J. Morris, R. K. Wood. Online multivariable adaptive control of a binary distillation column. The Canadian Journal of Chemical Engineering, vol. 69, no. 4, pp. 997–1009, 1991.

    Article  Google Scholar 

  27. M. T. Tham, F. Vagi, A. J. Morris, R. K. Wood. Multivariable and multirate self-tuning control: A distillation column case study. IEE Proceedings D: Control Theory and Applications, vol. 138, no. 1, pp. 9–24, 1991.

    Article  MATH  Google Scholar 

  28. S. A. Lawal, J. Zhang. Actuator fault monitoring and fault tolerant control in distillation columns. In Proceedings of the 21st International Conference on Automation and Computing, IEEE, Glasgow, USA, pp. 1–6, 2015.

    Google Scholar 

  29. D. M. Prett, M. Morari. The Shell Process Control Workshop, London, UK: Butterworths, 1987.

    Google Scholar 

  30. C. Vlachos, D. Williams, J. B. Gomm. Solution to the Shell standard control problem using genetically tuned PID controllers. Control Engineering Practice, vol. 10, no. 2, pp. 151–163, 2002.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sulaiman Ayobami Lawal.

Additional information

The work was supported by the EU FP7 (No.PIRSES-GA-2013- 612230).

Recommended by Guest Editor Dongbing Gu

Sulaiman Ayobami Lawal received the B. Sc. degree in chemical engineering from Ladoke Akintola University of Technology, Nigeria in 2003, and the M. Sc. degree in applied process control from Newcastle University, UK in 2006. He is a lecturer at the Chemical Engineering Department of the University of Lagos, Yaba in Nigeria, and currently a Ph. D. degree candidate at Newcastle University, UK.

His research interest include actuator and sensor fault detection, diagnosis and fault tolerant control systems.

ORCID iD: 0000-0002-0485-9141

Jie Zhang received the B. Sc. degree in control engineering from Hebei University of Technology, China in 1986 and the Ph.D. degree in control engineering from City University, UK in 1991. He is a senior lecturer in the School of Chemical Engineering and Advanced Materials, University of Newcastle, UK. He has published over 250 papers in international journals, books, and conferences. He is a senior member of IEEE, a member of the IEEE Control Systems Society, and IEEE Computational Intelligence Society. He is on the editorial boards of a number of journals including Neurocomputing published by Elsevier.

His research interests include the general areas of process system engineering including modelling, batch process control, process monitoring, and computational intelligence.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lawal, S.A., Zhang, J. Actuator fault monitoring and fault tolerant control in distillation columns. Int. J. Autom. Comput. 14, 80–92 (2017). https://doi.org/10.1007/s11633-016-1037-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11633-016-1037-8

Keywords

Navigation