Digital Self-tuning Control for Pressure Process

Gediminas Liaucius, Vytautas Kaminskas

Abstract

Two digital control systems - Self-tuning PID (Proportional-Integral-Derivative) Control and Predictor-based self-tuning control with constraints - for the continuous-time pressure process control are presented in this paper. The digital self-tuning PID control with optimization of closed-loop parameters and sampling period is proposed. The multidimensional optimization problem of closed-loop parameters and sampling period is solved by subcomponent search method that enables dividing the problem to one-dimensional optimization problems. The golden section search is adjusted to solve those – one-dimensional - optimization problems. The predictor-based self-tuning control with constraints is adapted for both minimum-phase and nonminimum-phase process models. The control quality of pressure process of both control systems has been experimentally investigated. The results of experimental analysis demonstrate that the digital self-tuning PID control with optimization is more efficient as compared to predictive-based self-tuning control with constraints for pressure process.

References

  1. Åström, K., J., Hagglund, T., 1995. PID Controllers: Theory, Design, and Tuning, Research Triangle Park, North Carolina.
  2. Åström, K., J., Hagglung, T., 2001. The future of PID control. In Control Engineering Practice, vol. 9, no. 11, pp. 1163-1175. ScienceDirect.
  3. Åström, K., J., Wittenmark, B., 1980. Self-tuning controller based on pole-zero placement. In IEE Proceedings D, vol. 127, pp. 120-130. IEEEXplore.
  4. Åström, K., J., Wittenmark B., 1997. ComputerControllers Systems: Theory and Design, Prentice Hall, New Jersey, 3rd edition.
  5. Bobál, B., Böhm, J., Fessl, J., Machácek J., 2005. Digital Self-tuning Controllers, Springer-Verlag. London, 2nd edition.
  6. Boucher, A., R., Cox, C., S., Doonan, A., 1989. Sampling Time Selection and its Effect on Direct Digital Adaptive Control Algorithm Implementation. In IEE Colloquium on Implementation Problems in Digital Control, pp. 5/1-5/8. IEEEXplore.
  7. Isermann, R., 1991. Digital Control Systems, SpringerVerlag. London, 2nd edition.
  8. Kaminskas, V., 1982. Dynamic system identification via discrete-time observation: Part 1. Statistical method foundation. estimation in linear systems, Mokslas Publishers. Vilnius (in Russian).
  9. Kaminskas, V., 2007. Predictor-Based Self Tuning Control with Constraints. In Book Series Springer Optimization and Its Applications, Model and Algorithms for Global Optimization, vol. 4, p. 333- 341.
  10. Kosorus, H., Hollrigl-Binder, M., Allmer, H., Kung, J., 2012. On the Identification of Frequencies and Damping Ratios for Structural Health Monitoring Using Autoregressive Models. In 23rd International Workshop on Database and Expert Systems Applications (DEXA), pp. 23-27. IEEEXplore.
  11. Levine, W., S., 1999. The Control Handbook. CRC Press, Mumbai.
  12. Levine, W., S., 2011. The Control Handbook, Second Edition: Control System Fundamentals, CRC Press. London, 2nd edition.
  13. Liaucius. G., Kaminskas, V., Liutkevicius, R., 2011. Digital Self-Tuning PID Control of Pressure Plant with Closed-Loop Optimization. In Information Technology and Control, vol. 40, no. 3, pp. 202 209.
  14. Liaucius, G., Kaminskas, V., 2012. Adaptive digital PID control of pressure process. In Power Engineering, vol. 58, no. 3, pp. 158-165. EBSCO.
  15. Liaucius, G., Kaminskas, V., 2012. Closed-Loop Optimization Algorithms in Digital Self-Tuning PID Control of Pressure Process. In ECT2012 - the 9th International Conference on Electrical and Control Technologies, pp. 25-29.
  16. Ortega, R., Kelly, R., 1984. PID self-tuners. Some theoretical and practical aspects. In IEEE Transaction of Industrial Electronics, vol. 31, pp. 332-338. IEEEXplore.
  17. Vu, V., H., Thomas, M., Lakis, A., A., Marcouiller, L., 2007. Multi-autoregressive model for structural output only modal analysis. In Proceedings of the 25th Seminar on machinery vibration, Canadian Machinery Vibration Association, pp. 41-1.
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Paper Citation


in Harvard Style

Liaucius G. and Kaminskas V. (2014). Digital Self-tuning Control for Pressure Process . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-039-0, pages 612-619. DOI: 10.5220/0005012106120619


in Bibtex Style

@conference{icinco14,
author={Gediminas Liaucius and Vytautas Kaminskas},
title={Digital Self-tuning Control for Pressure Process},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2014},
pages={612-619},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005012106120619},
isbn={978-989-758-039-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Digital Self-tuning Control for Pressure Process
SN - 978-989-758-039-0
AU - Liaucius G.
AU - Kaminskas V.
PY - 2014
SP - 612
EP - 619
DO - 10.5220/0005012106120619