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Keywords:
multiple uncertain delays; statistical learning theory
multiple uncertain delays; statistical learning theory
Summary:
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.
References:
[3] 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
[4] 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
[5] Dugard L., (eds.) E. I. Verriest: Stability and Control of Time-Delay Systems. (Lecture Notes in Control and Information Sciences 228.) Springer–Verlag, London 1997 MR 1482570 | Zbl 0901.00019
[6] In, IEEE CSS.: Proc. IEEE Conference on Decision and Control, Special Sessions TA-03, TM-03, TP-03. San Diego 1997
[7] Koltchinskii V., Abdallah C. T., Ariola M., Dorato, P., Panchenko D.: Improved sample complexity estimates for statistical learning control of uncertain systems. IEEE Trans. Automat. Control 45 (2000), 12, 2383–2388 DOI 10.1109/9.895579 | MR 1808524 | Zbl 0991.93130
[8] Prycker M. De: Asynchronous Transfer Mode: Solution for Broadband ISDN. Prentice–Hall, Englewood Cliffs, NJ 1995
[9] Mascolo S.: Smith’s principle for congestion control in high-speed data network. IEEE Trans. Automat. Control 45 (2000), 2, 358–364 DOI 10.1109/9.839966 | MR 1756771
[10] Niculescu S.-I., Abdallah C. T.: Delay effects on static output feedback stabilization. In: Proceedings IEEE CDC 2000, Sydney 2000
[11] 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 MR 1482571
[12] Smith O. J. M.: Closer control of loops with dead time. Chem. Engr. Progress 53 (1957), 5, 217–219
[13] Toker O., Ozbay H.: Complexity issues in robust stability of linear delay-differential systems. Math. Control Signals Syst. 9 (1996), 386–400 DOI 10.1007/BF01211858 | MR 1450360
[14] Vidyasagar M.: A Theory of Learning and Generalization with Applications to Neural Networks and Control Systems. Springer–Verlag, Berlin 1996 MR 1482231 | Zbl 0928.68061
[15] Vidyasagar M.: Statistical learning theory and randomized algorithms for control. IEEE Control Systems Magazine 18 (1998), 6, 69–85 DOI 10.1109/37.736014 | MR 1632342
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