01440nas a2200193 4500008004100000245006200041210006200103300001400165490000600179520084200185653002101027653001301048100001401061700001801075700001301093700001601106700001501122856010901137 2010 eng d00aDesign of Embedded Controllers Based on Anytime Computing0 aDesign of Embedded Controllers Based on Anytime Computing a492 - 5020 v63 a

In this paper, we present a methodology for designing embedded controllers based on the so-called anytime control paradigm. A control law is split into a sequence of subroutine calls, each one fulfilling a control goal and refining the result produced by the previous one. We propose a design methodology to define a feedback controller structured in accordance with this paradigm and show how a switching policy of selecting the controller subroutines can be designed that provides stability guarantees for the closed-loop system. The cornerstone of this construction is a stochastic model describing the probability of executing, in each activation of the controller, the different subroutines. We show how this model can be constructed for realistic real-time task sets and provide an experimental validation of the approach.

10aEmbedded Control10aRobotics1 aQuagli, A1 aFontanelli, D1 aGreco, L1 aPalopoli, L1 aBicchi, A. uhttps://www.centropiaggio.unipi.it/publications/design-embedded-controllers-based-anytime-computing.html01321nas a2200193 4500008004100000245008200041210006900123260004700192300001000239520063700249653002100886653001300907100001400920700001800934700001300952700001600965700001500981856013100996 2009 eng d00aDesigning Real-Time Embedded Controllers using the Anytime Computing Paradigm0 aDesigning RealTime Embedded Controllers using the Anytime Comput aPalma de Mallorca, SpaincSeptember, 12 -  a1 - 83 a

In this paper we present a methodology for designing embedded controllers with a variable accuracy. The adopted paradigm is the so called any-time control, which derives from the computing paradigm known as "imprecise computation". The most relevant contributions of the paper are a procedure for designing an incremental control law, whose different pieces cater for increasingly aggressive control requirements, and a modelling technique for the execution platform that allows us to design provably correct switching policies for the controllers. The methodology is validated by both simulations and experimental results.

10aEmbedded Control10aRobotics1 aQuagli, A1 aFontanelli, D1 aGreco, L1 aPalopoli, L1 aBicchi, A. uhttps://www.centropiaggio.unipi.it/publications/designing-real-time-embedded-controllers-using-anytime-computing-paradigm.html01738nas a2200193 4500008004100000245009500041210006900136260001800205300001600223490000700239520104900246653002101295653001301316100001601329700001501345700001501360700003301375856013601408 2005 eng d00aMaximizing the stability radius of a set of systems under real-time scheduling constraints0 aMaximizing the stability radius of a set of systems under realti cNovember 2005 a1790–17950 v503 a

We address the problem of synthesising real-time embedded controllers taking into account constraints deriving from the implementation platform. Assuming a time-triggered model of computation for tasks controlling a set of independent systems and a real-time preemptive scheduling policy managing a single CPU processor board, we deal with two problems: 1- deciding whether a performance specification can be met on a given platform, 2- optimising performance on a platform. Decision variables of the design problems are the activation periods of the tasks , while the considered performance metric is the minimum stability radius attained over the different feedback loops, which is related to the technological feasibility of the controller and to the robustness of the controlled systems. The analytical formulation of the design problems enables efficient numerical solutions. The resulting control policies are directly implementable without performance degradation that may otherwise arise due to scheduling and execution delays.

10aEmbedded Control10aRobotics1 aPalopoli, L1 aPinello, C1 aBicchi, A.1 aSangiovanni-Vincentelli, A L uhttps://www.centropiaggio.unipi.it/publications/maximizing-stability-radius-set-systems-under-real-time-scheduling-constraints.html01668nas a2200169 4500008004100000245009300041210006900134300001400203520104000217653002101257653001301278100001501291700001601306700001501322700001901337856014201356 2004 eng d00aControl of Distributed Embedded Systems in the Presence of Unknown–but–Bounded Noise0 aControl of Distributed Embedded Systems in the Presence of Unkno a1448-14533 a

In this paper we consider the problem of controlling multiple scalar systems through a limited capacity shared channel. Each system is affected by process noise and can be controlled byactuators with values in a {\em fixed}inite set. The control objective is to bound the evolution of the systems in specified sets (controlled invariance). Our goal is to find an optimal allocation of the shared communication resource to the different control activities and to identify correct choices for the design parameters. The paper provides fundamental conceptual tools to attack the design problem in the formal framework of an optimization problem. Namely, we give a feasibility criterion to decide whether a set of design parameters conforms with a control specification (i.e., with the controlled invariance of a specified set for each system). Moreover, we offer the explicit computation of the minimum bit rate necessary for the controlled invariance of a set, which is of utmost importance for solving the optimization problem.

10aEmbedded Control10aRobotics1 aPicasso, B1 aPalopoli, L1 aBicchi, A.1 aJohansson, K H uhttps://www.centropiaggio.unipi.it/publications/control-distributed-embedded-systems-presence-unknown%E2%80%93%E2%80%93bounded-noise.html01298nas a2200157 4500008004100000245005500041210005400096520078700150653002100937653001300958100001500971700001900986700001601005700001501021856010401036 2004 eng d00aQuantised Control in Distributed Embedded Systems.0 aQuantised Control in Distributed Embedded Systems3 a

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 system’s 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).

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

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.

10aEmbedded Control10aRobotics1 aPalopoli, L1 aCucinotta, T1 aBicchi, A. uhttps://www.centropiaggio.unipi.it/publications/quality-service-control-soft-real-time-applications.html01381nas a2200169 4500008004100000245007600041210006900117260001300186300001400199520077900213653002100992653001301013100001601026700001501042700003301057856012101090 2002 eng d00aNumerically efficient control of systems with communication constraints0 aNumerically efficient control of systems with communication cons cDecember a1626-16313 a

The problem of stabilization to the trivial equilibrium of a system with communication constraints is addressed. The communication constraints are related to the fact that commands are issued to different groups of actuators through a shared resource. We tackle the problem by using a Model Predictive Control scheme, which,at every step, decides the allocation of the bus {\em and} he control command values. After discussing two different alternatives for dealing with the scheduling constraints, we develop a formulation based on the generalized linear complementarity problem, which enables the application of efficient numerical solutions. Finally, we give some preliminary result on the parametric dependence of the problem's solution from the system's state.

10aEmbedded Control10aRobotics1 aPalopoli, L1 aBicchi, A.1 aSangiovanni-Vincentelli, A L uhttps://www.centropiaggio.unipi.it/publications/numerically-efficient-control-systems-communication-constraints.html00740nas a2200217 4500008004100000245006700041210006700108260004100175300001200216490001400228653002100242653001300263100001600276700001500292700003300307700001700340700001500357700001900372700001400391856011700405 2002 eng d00aSynthesis of robust control systems under resource constraints0 aSynthesis of robust control systems under resource constraints aHeidelberg, GermanybSpringer-Verlag a337-3500 vLNCS 228910aEmbedded Control10aRobotics1 aPalopoli, L1 aPinello, C1 aSangiovanni-Vincentelli, A L1 aEl-Ghaoui, L1 aBicchi, A.1 aGreenstreet, M1 aTomlin, C uhttps://www.centropiaggio.unipi.it/publications/synthesis-robust-control-systems-under-resource-constraints.html