Call for Paper - May 2023 Edition
IJCA solicits original research papers for the May 2023 Edition. Last date of manuscript submission is April 20, 2023. Read More

Decoupling Control Approach for Neonate Incubator System

Print
PDF
 
Download Full Text
International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 47 - Number 2
Year of Publication: 2012
Authors:
Elyes Feki
M. Aymen Zermani
Abdelkader Mami
10.5120/7164-9851

Elyes Feki, Aymen M Zermani and Abdelkader Mami. Article: Decoupling Control Approach for Neonate Incubator System. International Journal of Computer Applications 47(2):49-57, June 2012. Full text available. BibTeX

@article{key:article,
	author = {Elyes Feki and M. Aymen Zermani and Abdelkader Mami},
	title = {Article: Decoupling Control Approach for Neonate Incubator System},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {47},
	number = {2},
	pages = {49-57},
	month = {June},
	note = {Full text available}
}

Abstract

This paper presents an adaptive decoupling temperature and humidity control for neonatal incubator process by exploiting an active humidification system. The neonatal incubator is a Two-Input Two-Output process (TITO) with characteristics of strong coupling and time variation. The coupling problem is treated by the weight adjustment of the output error to reduce the effect of coupling and to enhance control performance. In addition, an Adaptive Decoupling strategy based on Generalized Predictive Control (ADGPC) with Multivariable Recursive Extended Least-Squares (MVRELS) parameters estimator is used. The simulation and real results demonstrate that the decoupling by error dependent tuning of the weighting factor can eliminate the coupling influence with better control performance and can be easily generalized to the Multiple-Input – Multiple-Output (MIMO) systems.

References

  • D. W. Clarke, C. Mohtadi and P. S. Tuffs, "Generalized Predictive Control - Part I and II", Automatica, 23(2), pp. 137-160, 1987.
  • G. Li, D. P. Stoten and J. -Y. Tu, "Model predictive control of dynamically substructured systems with application to a servohydraulically actuated mechanical plant", IET Control Theory Appl. , 4(2), pp. 253–264, 2010.
  • A. Ogunnaike and W. H. Ray, "Process Dynamics, Modeling, and Control", Oxford Univ. Press, 1994.
  • Bego, O. Peric, N. I. Petrovic, "Decoupling multivariable GPC with reference observation", 10th Mediterranean Electrotechnical Conference , vol. 2, pp. 819 – 822, 2000.
  • P. R. Maurath, D. E. Seborg and D. A. Mellichamp, "Achieving decoupling with predictive controllers", Proc. Amer. Control Conf. , Seattle, pp. 1372-1377, 1986,
  • F. Telliez, V. Bach, S. Delanaud, H. M. Baye, A. Leke, A. Apdoh and M. Abidiche, "Influence du niveau d'humidité de l'air sur le sommeil du nouveau-né en incubateur", RBM. Revue européenne de biotechnologie médicale, vol. 21, pp. 171-176, 1999.
  • Gler and M. Burunkaya, "Humidity control of an incubator using the microcontroller-based active humidifier system employing an ultrasonic nebulizer", Journal of Medical Engineering and Technology, vol. 26, pp. 82-88, 2002.
  • D. W. Clarke, "Application of Generalized Predictive Control to Industrial Processes", IEEE Control System Magazine, vol. 8, pp. 49-55, 1988.
  • J. Richalet, D. O'Donavan, "Elementary Predictive Functional Control", Springer Verlag, Berlin, 201-105, 2009.
  • J. T. J. Richalet, A. Rault and J. Papon, "Model predictive heuristic control: Applications to industial processes", Automatica, vol. 14, pp. 413–428, 1978.
  • C. C. Tsai and C. H. Huang, "Model reference adaptive predi- ctive control for a variable-frequency oil-cooling machine", IEEE Trans. Ind. Electron, 51,vol. 2, pp. 330-339, 2004.
  • K. J. Astrom, "Theory and applications of adaptive control-A survey", Automatica, vol. 19, pp. 471-486,1983.
  • D. M. Mathelin and R. Lozano, "Robust adaptive identification of slowly time-varying parameters with bounded disturbances", Automatica, vol. 35, pp. 1291-1305, 1999.
  • M. A. Zermani, E. Feki and A. Mami, "Application of Adaptive Predictive Control to a Newborn Incubator", American J. of Engineering and Applied Sciences, 4 (2), pp. 235-243, 2011.
  • U. Schmitz, R. Haber, F. Arousi and R. Bars, "Decoupling predictive control by error-dependent tuning of the weighting factor". AT&P Journal PLUS 2, pp. 131-140, 2007.
  • L. Zhang and R. Zhou, "Design of an incubator for premature infant based on labview", Conf Proc IEEE Eng Med Biol Soc, vol. 4, pp. 4079–4082, 2005.
  • Drager Medical Systems, "Drager isolette c2000 infant incubator brochure", April 2004.
  • J. L. Costa, C. S. Freire, B. A. Silva, M. P. Cursino, R. Oliveira, A. M. Pereira and F. L. Silva, "Humidity control system in newborn incubator", XIX IMEKO World Congress Fundamental and Applied Metrology, 2009.
  • M. A. Zermani, E. Feki and A. Mami, "Application of Genetic Algorithms in identification and control of a new system humidification inside a newborn incubator", International Conference on Communications, Computing and Control Applications, pp. 1-6, 2011.
  • A. K Abbas and S. Leonhardt, "System Identification of neonatal incubator based on adaptive ARMAX technique", IFMBE Proc, vol. 22, pp. 2515-2519, 2009.
  • A. Hagenblad and L. Ljung, "Maximum likelihood identification of Wiener models with a linear regression initialization", Proc. 37th IEEE Conference on Decision and Control, USA, 1998.