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Statistical-learning control of multiple-delay systems with application to ATM networks. (English) Zbl 1265.93210

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.

MSC:

93D21 Adaptive or robust stabilization
93C73 Perturbations in control/observation systems
68T05 Learning and adaptive systems in artificial intelligence
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References:

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