01298nas a2200157   4500008004100000245005500041210005400096520078700150653002100937653001300958100001500971700001900986700001601005700001501021856010401036       2004                        eng d00aQuantised Control in Distributed Embedded Systems.0 aQuantised Control in Distributed Embedded Systems3 a<p>Traditional control design is based on ideal assumptions concerning the amount, type and accuracy of the information flow that can be circulated across the controller. Unfortunately, real implementation platforms exhibit non-idealities that may substantially invalidate such assumptions. As a result, the systems closed-loop performance can be severely affected and sometimes stability itself is jeopardised. These problems show up with particular strength when multiple feedback loops share a limited pool of computation and communication resources. In this case the designer is confronted with the challenging task of choosing at the same time the control law and the optimal allocation policy for the shared resources (control algortihm/system architecture co-design).</p>
10aEmbedded Control10aRobotics1 aBicchi, A.1 aJohansson, K H1 aPalopoli, L1 aPicasso, B  uhttps://www.centropiaggio.unipi.it/publications/quantised-control-distributed-embedded-systems.html01408nas a2200157   4500008004100000245006200041210006100103300001200164520088300176653002101059653001301080100001601093700001701109700001501126856010901141       2003                        eng d00aQuality of service control in soft real-time applications0 aQuality of service control in soft realtime applications  a664-6693 a<p>In this paper we present results obtained in the context of Quality of Service (QoS) control for soft real-time applications. The discussion addresses the issue of dynamically adjusting the bandwidth for a set of periodic tasks, when a reservation-based (RB) CPU scheduling policy is used. RB techniques are particularly suitable for this kind of applications since they allow an accurate mathematical modelling of the dynamic evolution of the QoS experienced by tasks. Based on this model, a control policy guaranteeing specified QoS levels for different tasks is illustrated, along with necessary and sufficient conditions for its existence. Moreover, the problem of steering a task QoS back into its nominal level is tackled, in response to deviations due to temporary overload conditions. Simulation results are reported, for the purpose of validating the approach.</p>
10aEmbedded Control10aRobotics1 aPalopoli, L1 aCucinotta, T1 aBicchi, A.  uhttps://www.centropiaggio.unipi.it/publications/quality-service-control-soft-real-time-applications.html