Approaches for Future Internet architecture design and Quality of Experience (QoE) Control

Researching a Future Internet capable of overcoming the current Internet limitations is a strategic investment. In this respect, this paper presents some concepts that can contribute to provide some guidelines to overcome the above-mentioned limitations. In the authors' vision, a key Future Internet target is to allow applications to transparently, efficiently and flexibly exploit the available network resources with the aim to match the users' expectations. Such expectations could be expressed in terms of a properly defined Quality of Experience (QoE). In this respect, this paper provides some approaches for coping with the QoE provision problem

ROBUST REGULATION FOR SYSTEMS WITH POLYNOMIAL NONLINEARITY APPLIED TO RAPID THERMAL PROCESSES

Abstract. A problem of output robust control for a system with power nonlinearity is considered. The considered problem can be rewritten as a stabilization problem for a system with polynomial nonlinearity by introducing the error term. The problem of temperature regulation is considered as application; the rapid thermal processes in vapor deposition processing are studied. Modern industrial equipment uses complex sensors and control systems; these devices are not available for laboratory setups. The limited amount of available sensors and other technical restrictions for laboratory setups make it an actual problem to design simple low-order output control laws. The problem is solved by the consecutive compensator approach. The paper deals with a new type of restriction which is a combination of linear and power restrictions. It is shown that the polynomial nonlinearity satisfies this restriction. Asymptotical stability of the closed-loop system is proved by the Lyapunov functions approach for the considered nonlinear function; this contribution extends previously known results. Numerical simulation of the vapor deposition processing illustrates that the proposed approach results in zero-mean tracking error with standard deviation less than 1K