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Dynamical flow networks with heterogeneous routing are analyzed in terms of stability and resilience to perturbations. Particles flow through the network and, at each junction, decide which downstream link to take on the basis of the local state of the network. Differently from single-commodity scenarios, particles belong to different classes, or commodities, with different origins and destination

This paper addresses the need of continued education of process industry practitioners such as operators and instrumentation engineers. The process industry regulatory control tuning situation of today is reviewed. Areas of potential improvement are identified. A course, aimed at fulfilling these needs is presented. Especially, useful laboratory experiments are outlined. The suggested course was g

We consider a networked control system where a linear time-invariant (LTI) plant, subject to a stochastic disturbance, is controlled over a communication channel with colored noise and a signal-to-noise ratio (SNR) constraint. The controller is based on output feedback and consists of an encoder that measures the plant output and transmits over the channel, and a decoder that receives the channel

Reichenbach’s constraint is the methodological imperative formulated by Reichenbach in the following passage: “If we want to construct a philosophy of science, we have to distinguish carefully between two kinds of context in which scientific theories may be considered. The context of discovery is to be separated from the context of justification; the former belongs to the psychology of scient

The adaptive resource management framework implemented in the European ACTORS project is presented. A resource manager has been developed that collaborates with a new Linux scheduler providing support for hard constant bandwidth server reservations, in order to adapt applications to changes in resource availability and to adapt the resource allocation to changes in application requirements. The fo

Self-adaptation enables software to execute successfully in dynamic, unpredictable, and uncertain environments. Control theory provides a broad set of mathematically grounded techniques for adapting the behavior of dynamic systems. While it has been applied to specific software control problems, it has proved difficult to define methodologies allowing non-experts to systematically apply control te

The design of a controller for glycemia regulation, either in open or in closed-­‐loop, relies on models able to describe the effects of a meal intake and an insulin injection on blood glucose dynamics. The purpose of this study was therefore to propose a physiological relevant yet parsimonious model for carbohydrate action on fasting blood glucose in T1DM patients when no insulin is taken.

This study investigates temporal relationships between vegetation growth, rainfall, and soil moisture for six sites located in sub-Saharan and southern Africa for the period 2005-2009. Specifically, seasonal components of time series of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) composites from the Moderate Resolution Imaging Spectroradiometer (MODIS) and hal

A number of techniques have been proposed to provide run- time performance guarantees while minimizing power consumption. One drawback of existing approaches is that they work only on a fixed set of components (or actuators) that must be specified at design time. If new components become available, these management systems must be redesigned and reimplemented. In this paper, we propose PTRADE, a n

It has been shown that optimal controller synthesis for positive systems can be formulated as a linear program. Leveraging these results, we propose a scalable iterative algorithm for the systematic design of sparse, small gain feedback strategies that stabilize the evolutionary dynamics of a generic disease model. We achieve the desired feedback structure by augmenting the optimization problems w

The problem of resource management in a sys- tem of a-priori unknown software components executing on nondeterministic hardware is considered. The approach uses on-line parameter estimation to address uncertainties and combines this with a convex optimization-based control scheme able to handle overload situations. An algorithm to solve the optimization in real-time is presented together with perf

For interconnected systems and systems of large size, aggregating information of subsystems studied individually is useful for addressing the overall stability. In the Lyapunov- based analysis, summation and maximization of separately constructed functions are two typical approaches in such a philosophy. This paper focuses on monotone systems which are common in control applications and elucidates

This paper presents a reinforcement learning algorithm and provides conditions for global convergence to Nash equilibria. For several reinforcement learning schemes, including the ones proposed here, excluding convergence to action profiles which are not Nash equilibria may not be trivial, unless the step-size sequence is appropriately tailored to the specifics of the game. In this paper, we sides