Kybernetika 37 no. 3, 355-365, 2001

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

Chaouki T. Abdallah, Marco Ariola and Vladimir Koltchinskii

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.