Statistical-learning control of multiple-delay systems with application to ATM networks

Chaouki T. Abdallah; Marco Ariola; Vladimir Koltchinskii

Kybernetika (2001)

  • Volume: 37, Issue: 3, page [355]-365
  • ISSN: 0023-5954

Abstract

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Congestion control in the ABR class of ATM network presents interesting challenges due to the presence of multiple uncertain delays. Recently, probabilistic methods and statistical learning theory have been shown to provide approximate solutions to challenging control problems. In this paper, using some recent results by the authors, an efficient statistical algorithm is used to design a robust, fixed-structure, controller for a high-speed communication network with multiple uncertain propagation delays.

How to cite

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Abdallah, Chaouki T., Ariola, Marco, and Koltchinskii, Vladimir. "Statistical-learning control of multiple-delay systems with application to ATM networks." Kybernetika 37.3 (2001): [355]-365. <http://eudml.org/doc/33540>.

@article{Abdallah2001,
abstract = {Congestion control in the ABR class of ATM network presents interesting challenges due to the presence of multiple uncertain delays. Recently, probabilistic methods and statistical learning theory have been shown to provide approximate solutions to challenging control problems. In this paper, using some recent results by the authors, an efficient statistical algorithm is used to design a robust, fixed-structure, controller for a high-speed communication network with multiple uncertain propagation delays.},
author = {Abdallah, Chaouki T., Ariola, Marco, Koltchinskii, Vladimir},
journal = {Kybernetika},
keywords = {multiple uncertain delays; statistical learning theory; multiple uncertain delays; statistical learning theory},
language = {eng},
number = {3},
pages = {[355]-365},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Statistical-learning control of multiple-delay systems with application to ATM networks},
url = {http://eudml.org/doc/33540},
volume = {37},
year = {2001},
}

TY - JOUR
AU - Abdallah, Chaouki T.
AU - Ariola, Marco
AU - Koltchinskii, Vladimir
TI - Statistical-learning control of multiple-delay systems with application to ATM networks
JO - Kybernetika
PY - 2001
PB - Institute of Information Theory and Automation AS CR
VL - 37
IS - 3
SP - [355]
EP - 365
AB - Congestion control in the ABR class of ATM network presents interesting challenges due to the presence of multiple uncertain delays. Recently, probabilistic methods and statistical learning theory have been shown to provide approximate solutions to challenging control problems. In this paper, using some recent results by the authors, an efficient statistical algorithm is used to design a robust, fixed-structure, controller for a high-speed communication network with multiple uncertain propagation delays.
LA - eng
KW - multiple uncertain delays; statistical learning theory; multiple uncertain delays; statistical learning theory
UR - http://eudml.org/doc/33540
ER -

References

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  1. Benmohamed L., Wang Y. T., A control-theoretic ABR explicit rate algorithm for ATM switches with Per-VC queuing, In: Proceedings Infocom98, San Francisco 1998, pp. 183–191 (1998) 
  2. Blanchini F., Cigno, R. Lo, Tempo R., Control of ATM Networks: Fragility and Robustness Issues, In: Proceedings American Control Conference, Philadelphia 1998, pp. 2847–2851 (1998) 
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  4. In, IEEE CSS., Proc, IEEE Conference on Decision and Control, Special Sessions TA-03, TM-03, TP-03. San Diego 1997 
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  8. Niculescu S.-I., Abdallah C. T., Delay effects on static output feedback stabilization, In: Proceedings IEEE CDC 2000, Sydney 2000 
  9. Niculescu S.-I., Verriest E., Dugard, L., Dion J.-M., Stability and robust stability of time-delay systems: A guided tour, In: Stability and Control of Time-Delay Systems, (L. Dugard and E. I. Verriest, eds., Lecture Notes in Control and Information Sciences 228), Springer–Verlag, London 1997, pp. 1–71 (1997) MR1482571
  10. Smith O. J. M., Closer control of loops with dead time, Chem. Engr. Progress 53 (1957), 5, 217–219 (1957) 
  11. Toker O., Ozbay H., 10.1007/BF01211858, Math. Control Signals Syst. 9 (1996), 386–400 (1996) MR1450360DOI10.1007/BF01211858
  12. Vidyasagar M., A Theory of Learning and Generalization with Applications to Neural Networks and Control Systems, Springer–Verlag, Berlin 1996 Zbl0928.68061MR1482231
  13. Vidyasagar M., 10.1109/37.736014, IEEE Control Systems Magazine 18 (1998), 6, 69–85 (1998) MR1632342DOI10.1109/37.736014

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