Institute for Advanced Studies Lucca

Lucca, Italy

Institute for Advanced Studies Lucca

Lucca, Italy
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Ocampo-Martinez C.,Polytechnic University of Catalonia | Barcelli D.,University of Siena | Puig V.,Polytechnic University of Catalonia | Bemporad A.,Institute for Advanced Studies Lucca
IET Control Theory and Applications | Year: 2012

A hierarchical and decentralised model predictive control (DMPC) strategy for drinking water networks (DWN) is proposed. The DWN is partitioned into a set of subnetworks using a partitioning algorithm that makes use of the topology of the network, historic information about the actuator usage and heuristics. A suboptimal DMPC strategy was derived, which consists in a set of MPC controllers, whose prediction model is a plant partition, where each element solves its control problem in a hierarchical order. A comparative simulation study between centralised MPC (CMPC) and DMPC approaches is developed using a case study, which consists in an aggregate version of the Barcelona DWN. Results have shown the effectiveness of the proposed DMPC approach in terms of the scalability of computations with an acceptable admissible loss of performance in all the considered scenarios. © 2011 The Institution of Engineering and Technology.


Lluch Lafuente A.,Institute for Advanced Studies Lucca | Meseguer J.,University of Illinois at Urbana - Champaign | Vandin A.,Institute for Advanced Studies Lucca
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

We present c-reductions, a simple, flexible and very general state space reduction technique that exploits an equivalence relation on states that is a bisimulation. Reduction is achieved by a canonizer function, which maps each state into a not necessarily unique canonical representative of its equivalence class. The approach contains symmetry reduction and name reuse and name abstraction as special cases, and exploits the expressiveness of rewriting logic and its realization in Maude to automate c-reductions and to seamlessly integrate model checking and the discharging of correctness proof obligations. The performance of the approach has been validated over a set of representative case studies. © 2012 Springer-Verlag.


de Montis A.,University of Sassari | Caschili S.,University College London | Chessa A.,Complex Systems Computational Laboratory | Chessa A.,University of Rome La Sapienza | Chessa A.,Institute for Advanced Studies Lucca
European Physical Journal: Special Topics | Year: 2013

A major issue for policy makers and planners is the definition of "ideal" regional partitions, i. e. the delimitation of sub-regional domains showing a sufficient level of homogeneity with respect to some specific territorial features. In this paper, we compare some intermediate body partitions of Sardinia, Italy, with patterns that emerge from the workers and students' commuting. We apply grouping methodologies based on the characterization of Sardinian commuting system as a complex weighted network. We adopt an algorithm based on the maximization of the weighted modularity of this network and detect productive basins composed by municipalities with degree of cohesiveness in terms of commuters' flows. The results of this study lead us to conclude that the recently instituded provinces in Sardinia have been designed -even unconsciously- as labour basins of municipalities with similar commuting behaviour. © 2013 EDP Sciences and Springer.


De Nicola R.,Institute for Advanced Studies Lucca | Ferrari G.,University of Pisa | Loreti M.,University of Florence | Pugliese R.,University of Florence
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

SCEL is a new language specifically designed to model autonomic components and their interaction. It brings together various programming abstractions that permit to directly represent knowledge, behaviors and aggregations according to specific policies. It also supports naturally programming self-awareness, context-awareness, and adaptation. In this paper, we first present design principles, syntax and operational semantics of SCEL. Then, we show how a dialect can be defined by appropriately instantiating the features of the language we left open to deal with different application domains and use this dialect to model a simple, yet illustrative, example application. Finally, we demonstrate that adaptation can be naturally expressed in SCEL. © 2013 Springer-Verlag Berlin Heidelberg.


De Nicola R.,Institute for Advanced Studies Lucca | Loreti M.,University of Florence | Pugliese R.,University of Florence | Tiezzi F.,Institute for Advanced Studies Lucca
ACM Transactions on Autonomous and Adaptive Systems | Year: 2014

The autonomic computing paradigm has been proposed to cope with size, complexity, and dynamism of contemporary software-intensive systems. The challenge for language designers is to devise appropriate abstractions and linguistic primitives to deal with the large dimension of systems and with their need to adapt to the changes of the working environment and to the evolving requirements. We propose a set of programming abstractions that permit us to represent behaviors, knowledge, and aggregations according to specific policies and to support programming context-awareness, self-awareness, and adaptation. Based on these abstractions, we define SCEL (Software Component Ensemble Language), a kernel language whose solid semantic foundations lay also the basis for formal reasoning on autonomic systems behavior. To show expressiveness and effectiveness of SCEL's design, we present a Java implementation of the proposed abstractions and show how it can be exploited for programming a robotics scenario that is used as a running example for describing the features and potential of our approach. © 2014 ACM.


Bernardo M.,Urbino University | De Nicola R.,Institute for Advanced Studies Lucca | Loreti M.,University of Florence
Information and Computation | Year: 2013

Labeled transition systems are typically used as behavioral models of concurrent processes. Their labeled transitions define a one-step state-to-state reachability relation. This model can be generalized by modifying the transition relation to associate a state reachability distribution with any pair consisting of a source state and a transition label. The state reachability distribution is a function mapping each possible target state to a value that expresses the degree of one-step reachability of that state. Values are taken from a preordered set equipped with a minimum that denotes unreachability. By selecting suitable preordered sets, the resulting model, called ULTraS from Uniform Labeled Transition System, can be specialized to capture well-known models of fully nondeterministic processes (LTS), fully probabilistic processes (ADTMC), fully stochastic processes (ACTMC), and nondeterministic and probabilistic (MDP) or nondeterministic and stochastic (CTMDP) processes. This uniform treatment of different behavioral models extends to behavioral equivalences. They can be defined on ULTraS by relying on appropriate measure functions that express the degree of reachability of a set of states when performing multi-step computations. It is shown that the specializations of bisimulation, trace, and testing equivalences for the different classes of ULTraS coincide with the behavioral equivalences defined in the literature over traditional models except when nondeterminism and probability/stochasticity coexist; then new equivalences pop up. © 2013 Elsevier Inc.


Patrascu A.,Polytechnic University of Bucharest | Necoara I.,Institute for Advanced Studies Lucca | Patrinos P.,Polytechnic University of Bucharest
Proceedings of the IEEE Conference on Decision and Control | Year: 2014

In this paper we consider the minimization of ℓ0-regularized nonlinear optimization problems, where the objective function is the sum of a smooth convex term and the ℓ0 quasi-norm of the decision variable. We introduce the class of coordinatewise minimizers and prove that any point in this class is a local minimum for our ℓ0-regularized problem. Then, we devise a random proximal alternating minimization method, which has a simple iteration and is suitable for solving this class of optimization problems. Under convexity and coordinatewise Lipschitz gradient assumptions, we prove that any limit point of the sequence generated by our new algorithm belongs to the class of coordinatewise minimizers almost surely. We also show that the state estimation of dynamical systems with corrupted measurements can be modeled in our framework. Numerical experiments on state estimation of power systems, using IEEE bus test case, show that our algorithm performs favorably on solving such problems. © 2014 IEEE.


Patrascu A.,Polytechnic University of Bucharest | Necoara I.,Institute for Advanced Studies Lucca | Patrinos P.,Polytechnic University of Bucharest
Proceedings of the IEEE Conference on Decision and Control | Year: 2014

In this paper we consider the minimization of ℓ0-regularized nonlinear optimization problems, where the objective function is the sum of a smooth convex term and the ℓ0 quasi-norm of the decision variable. We introduce the class of coordinatewise minimizers and prove that any point in this class is a local minimum for our ℓ0-regularized problem. Then, we devise a random proximal alternating minimization method, which has a simple iteration and is suitable for solving this class of optimization problems. Under convexity and coordinatewise Lipschitz gradient assumptions, we prove that any limit point of the sequence generated by our new algorithm belongs to the class of coordinatewise minimizers almost surely. We also show that the state estimation of dynamical systems with corrupted measurements can be modeled in our framework. Numerical experiments on state estimation of power systems, using IEEE bus test case, show that our algorithm performs favorably on solving such problems. © 2014 IEEE.


Bernardini D.,University of Trento | Bemporad A.,Institute for Advanced Studies Lucca
Automatica | Year: 2012

Wireless sensor networks (WSNs) are becoming fundamental components of modern control systems due to their flexibility, ease of deployment and low cost. However, the energy-constrained nature of WSNs poses new issues in control design; in particular the discharge of batteries of sensor nodes, which is mainly due to radio communications, must be taken into account. In this paper we present a novel transmission strategy for communication between controller and sensors which is intended to minimize the data exchange over the wireless channel. Moreover, we propose an energy-aware control technique for constrained linear systems based on explicit model predictive control (MPC), providing closed-loop stability in the presence of disturbances. The presented control schemes are compared to traditional MPC techniques. The results show the effectiveness of the proposed energy-aware approach, which achieves a profitable trade-off between energy savings and closed-loop performance. © 2011 Elsevier Ltd. All rights reserved.


Bemporad A.,Institute for Advanced Studies Lucca
IEEE Transactions on Automatic Control | Year: 2016

This technical note proposes an active set method based on nonnegative least squares (NNLS) to solve strictly convex quadratic programming (QP) problems, such as those that arise in Model Predictive Control (MPC). The main idea is to rephrase the QP problem as a Least Distance Problem (LDP) that is solved via a NNLS reformulation.While the method is rather general for solving strictly convex QP's subject to linear inequality constraints, it is particularly useful for embedded MPC because (i) is very fast, compared to other existing state-of-the-art QP algorithms, (ii) is very simple to code, requiring only basic arithmetic operations for computing LDLT decompositions recursively to solve linear systems of equations, (iii) contrary to iterative methods, provides the solution or recognizes infeasibility in a finite number of steps. © 2015 IEEE.

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