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Feedback control has been applied to computing systems, usually taking a designed system and closing a loop to adjust some of its parameters. However, the design of computing systems components as controllers have shown advantages with respect to state-of-the-art techniques, especially in the scheduling domain, where uniprocessor schedulers have been designed as discrete-time control structures. H

An extended Kalman-Yakubovich-Popov (KYP) Lemma for positive systems is derived. The main difference compared to earlier versions is that non-strict inequalities are treated. Matrix assumptions are also less restrictive. Moreover, a new equivalence is introduced in terms of linear programming rather than semi-definite programming. As a complement to the KYP lemma, it is also proved that a symmetri

As farms are getting bigger with more animals, less manual supervision and attention can be given the animals on both group and individual level. In order not to jeopardize animal welfare, automated supervision is in some way already in use. Function and control of ventilation is already in use in modern pig stables, e.g. by the use of sensors for temperature, relative humidity and malfunction con

This paper describes a knowledge integration framework for robotics, whose goal is to represent, store, adapt, and distribute knowledge across engineering platforms. The architecture abstracts the components as data sources, where data are available in the AutomationML data exchange format. AutomationML is an on-going standard initiative that aims at unifying data representation and APIs used by e

In this paper a distributed version of the Kalman filter is proposed. In particular, the estimation problem is reduced to the optimization of a cost function that depends on the system dynamics and the latest output measurements and state estimates which is distributed among the agents by means of dual decomposition. The techniques presented in the paper are applied to estimate the position of mob

Program parallelization becomes increasingly important when new multi-core architectures provide ways to improve performance. One of the greatest challenges of this development lies in programming parallel applications. Declarative languages, such as constraint programming, can make the transition to parallelism easier by hiding the parallelization details in a framework. Automatic parallelizatio

We consider a class of distributed algorithms for computing arithmetic averages (average consensus) over net- works of agents connected through digital noisy broadcast channels. Our algorithms combine error-correcting codes with the classical linear consensus iterative algorithm, and do not require the agents to have knowledge of the global network structure. We improve the performance by introduc

An adaptive resource management system combined with a thermal controller is presented. The aim of the system is to dynamically allocate computing resources to applications competing for the same computing resources in such a way that the system is not overheated. The approach has been implemented on a mobile robot. Experimental results are presented showing the feasibility of the approach.

Cloud computing is an application hosting model providing the illusion of infinite computing power. However, even the largest datacenters have finite computing capacity, thus cloud infrastructures have experienced overload due to overbooking or transient failures. The topic of this paper is the comparison of different control strategies to mitigate overload for datacenters, that assume that the r

The Modelica language, targeted at modeling of complex physical systems, has gained increased attention during the last decade. Modelica is about to establish itself as a de facto standard in the modeling community with strong support both within academia and industry. While there are several tools, both commercial and free, supporting simulation of Modelica models few efforts have been made in th

Turbines operating in wind farms are coupled by the wind flow. This coupling results in limited power production and increased fatigue loads on turbines operating in the wake of other turbines. To operate wind farms cost effectively, it is important to understand and address these effects. In this paper, we derive a stationary model for turbine interaction. The model has a simple intuitive structu

We consider a class of large scale linear-quadratic coordination problems where the information exchange is subject to a time-delay. We show that several previously known properties of the optimal solution to the delay-free problem extend to this case. In particular, the optimal control law comprises a diagonal (decentralized) term complemented by a rank-one coordination term, which can be impleme

Temporal logics have proven effective for correct-by-construction synthesis of controllers for a wide range of robotic applications. Receding horizon frameworks mitigate the computational intractability of reactive synthesis for temporal logic, but have thus far been limited by pursuing a single sequence of short horizon problems to the goal. We propose a receding horizon algorithm for reactive sy

Correct-by-construction synthesis of high-level reactive control relies on the use of formal methods to generate controllers with provable guarantees on their behavior. While this approach has been successfully applied to a wide range of systems and environments, it scales poorly. A receding horizon framework mitigates this computational blowup, by decomposing the global control problem into sever

We study the use of the System Optimum (SO) Dynamic Traffic Assignment (DTA) problem to design optimal traffic flow controls for freeway networks as modeled by the Cell Transmission Model, using variable speed limit, ramp metering, and routing. We consider two optimal control problems: the DTA problem, where turning ratios are part of the control inputs, and the Freeway Network Control (FNC), wher

Distributed averaging is one of the simplest and most widely studied network dynamics. Its applications range from cooperative inference in sensor networks, to robot formation, to opinion dynamics. A number of fundamental results and examples scattered through the literature are gathered here and some original approaches and generalizations are presented, emphasizing the deep interplay between the