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  • 1.
    Alhashimi, Anas
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Del Favero, Simone
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Gustafsson, Thomas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Pillonetto, Gianluigi
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Bayesian strategies for calibrating heteroskedastic static sensors with unknown model structures2018In: 2018 European Control Conference (ECC), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 2447-2453Conference paper (Refereed)
    Abstract [en]

    This paper investigates the problem of calibrating sensors affected by (i) heteroskedastic measurement noise and (ii) a polynomial bias, describing a systematic distortion of the measured quantity. First, a set of increasingly complex statistical models for the measurement process was proposed. Then, for each model the authors design a Bayesian parameters estimation method handling heteroskedasticity and capable to exploit prior information about the model parameters. The Bayesian problem is solved using MCMC methods and reconstructing the unknown parameters posterior in sampled form. The authors then test the proposed techniques on a practically relevant case study, the calibration of Light Detection and Ranging (Lidar) sensor, and evaluate the different proposed procedures using both artificial and field data.

  • 2.
    Alhashimi, Anas
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems. Department of Computer EngineeringUniversity of Baghdad.
    Pierobon, Giovanni
    Department of Information EngineeringUniversity of Padova.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Gustafsson, Thomas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Modeling and Calibrating Triangulation Lidars for Indoor Applications2018In: Informatics in Control, Automation and Robotics: 13th International Conference, ICINCO 2016 Lisbon, Portugal, 29-31 July, 2016 / [ed] Kurosh Madani, Dimitri Peaucelle, Oleg Gusikhin, Cham: Springer Publishing Company, 2018, p. 342-366Conference paper (Refereed)
    Abstract [en]

    We present an improved statistical model of the measurement process of triangulation Light Detection and Rangings (Lidars) that takes into account bias and variance effects coming from two different sources of uncertainty:                                                                           {\$}{\$}(i) {\$}{\$}                 mechanical imperfections on the geometry and properties of their pinhole lens - CCD camera systems, and                                                                           {\$}{\$}(ii) {\$}{\$}                 inaccuracies in the measurement of the angular displacement of the sensor due to non ideal measurements from the internal encoder of the sensor. This model extends thus the one presented in [2] by adding this second source of errors. Besides proposing the statistical model, this chapter considers:                                                                           {\$}{\$}(i) {\$}{\$}                 specialized and dedicated model calibration algorithms that exploit Maximum Likelihood (ML)/Akaike Information Criterion (AIC) concepts and that use training datasets collected in a controlled setup, and                                                                           {\$}{\$}(ii) {\$}{\$}                 tailored statistical strategies that use the calibration results to statistically process the raw sensor measurements in non controlled but structured environments where there is a high chance for the sensor to be detecting objects with flat surfaces (e.g., walls). These newly proposed algorithms are thus specially designed and optimized for inferring precisely the angular orientation of the Lidar sensor with respect to the detected object, a feature that is beneficial especially for indoor navigation purposes.

  • 3.
    Alhashimi, Anas
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Gustafsson, Thomas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Calibrating distance sensors for terrestrial applications without groundtruth information2017In: IEEE Sensors Journal, ISSN 1530-437X, E-ISSN 1558-1748, Vol. 17, no 12, p. 3698-3709, article id 7911206Article in journal (Refereed)
    Abstract [en]

    This paper describes a new calibration procedure for distance sensors that does not require independent sources of groundtruth information, i.e., that is not based on comparing the measurements from the uncalibrated sensor against measurements from a precise device assumed as the groundtruth. Alternatively, the procedure assumes that the uncalibrated distance sensor moves in space on a straight line in an environment with fixed targets, so that the intrinsic parameters of the statistical model of the sensor readings are calibrated without requiring tests in controlled environments, but rather in environments where the sensor follows linear movement and objects do not move. The proposed calibration procedure exploits an approximated expectation maximization scheme on top of two ingredients: an heteroscedastic statistical model describing the measurement process, and a simplified dynamical model describing the linear sensor movement. The procedure is designed to be capable of not just estimating the parameters of one generic distance sensor, but rather integrating the most common sensors in robotic applications, such as Lidars, odometers, and sonar rangers and learn the intrinsic parameters of all these sensors simultaneously. Tests in a controlled environment led to a reduction of the mean squared error of the measurements returned by a commercial triangulation Lidar by a factor between 3 and 6, comparable to the efficiency of other state-of-the art groundtruth-based calibration procedures. Adding odometric and ultrasonic information further improved the performance index of the overall distance estimation strategy by a factor of up to 1.2. Tests also show high robustness against violating the linear movements assumption.

  • 4.
    Alhashimi, Anas
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Gustafsson, Thomas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Joint Temperature-Lasing Mode Compensation for Time-of-Flight LiDAR Sensors2015In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 15, no 12, p. 31205-31223Article in journal (Refereed)
    Abstract [en]

    We propose an expectation maximization (EM) strategy for improving the precision of time of flight (ToF) light detection and ranging (LiDAR) scanners. The novel algorithm statistically accounts not only for the bias induced by temperature changes in the laser diode, but also for the multi-modality of the measurement noises that is induced by mode-hopping effects. Instrumental to the proposed EM algorithm, we also describe a general thermal dynamics model that can be learned either from just input-output data or from a combination of simple temperature experiments and information from the laser’s datasheet. We test the strategy on a SICK LMS 200 device and improve its average absolute error by a factor of three.

  • 5.
    Alhashimi, Anas W.
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Gustafsson, Thomas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Statistical modeling and calibration of triangulation Lidars2016In: ICINCO 2016: Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics / [ed] Peaucelle D.,Gusikhin O.,Madani K, SciTePress, 2016, p. 308-317Conference paper (Refereed)
    Abstract [en]

    We aim at developing statistical tools that improve the accuracy and precision of the measurements returned by triangulation Light Detection and Rangings (Lidars). To this aim we: i) propose and validate a novel model that describes the statistics of the measurements of these Lidars, and that is built starting from mechanical considerations on the geometry and properties of their pinhole lens - CCD camera systems; ii) build, starting from this novel statistical model, a Maximum Likelihood (ML) / Akaike Information Criterion (AIC) -based sensor calibration algorithm that exploits training information collected in a controlled environment; iii) develop ML and Least Squares (LS) strategies that use the calibration results to statistically process the raw sensor measurements in non controlled environments. The overall technique allowed us to obtain empirical improvements of the normalized Mean Squared Error (MSE) from 0.0789 to 0.0046

  • 6.
    Bof, Nicoletta
    et al.
    Department of Information Engineering, University of Padova, Padova, Italy.
    Carli, Ruggero
    Department of Information Engineering, University of Padova, Padova, Italy.
    Notarstefano, Giuseppe
    Department of Electrical, Electronic and Information Engineering, University of Bologna, Bologna, Italy.
    Schenato, Luca
    Department of Information Engineering, University of Padova, Padova, Italy.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Multiagent Newton–Raphson Optimization Over Lossy Networks2019In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 64, no 7, p. 2983-2990Article in journal (Refereed)
    Abstract [en]

    In this work, we study the problem of unconstrained convex optimization in a fully distributed multiagent setting, which includes asynchronous computation and lossy communication. In particular, we extend a recently proposed algorithm named Newton-Raphson consensus by integrating it with a broadcast-based average consensus algorithm, which is robust to packet losses. We show via the separation of time-scale principle that under mild conditions (i.e., persistency of the agents activation and bounded consecutive communication failures), the proposed algorithm is provably locally exponentially stable with respect to the optimal global solution. Finally, we complement the theoretical analysis with numerical simulations and comparisons based on real datasets.

  • 7.
    Carli, Ruggero
    et al.
    Department of Information Engineering, University of Padova.
    Notarstefano, Giuseppe
    Department of Engineering for Innovation, University of Salento.
    Schenato, Luca
    Department of Information Engineering, University of Padova.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Analysis of Newton-Raphson consensus for multi-agent convex optimization under asynchronous and lossy communications2015In: IEEE 54th Annual Conference on Decision and Control (CDC): Osaka, Japan, 15-18 Dec. 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 418-424, article id 7402236Conference paper (Refereed)
    Abstract [en]

    We extend a multi-agent convex-optimization algorithm named Newton-Raphson consensus to a network scenario that involves directed, asynchronous and lossy communications. We theoretically analyze the stability and performance of the algorithm and, in particular, provide sufficient conditions that guarantee local exponential convergence of the node-states to the global centralized minimizer even in presence of packet losses. Finally, we complement the theoretical analysis with numerical simulations that compare the performance of the Newton-Raphson consensus against asynchronous implementations of distributed subgradient methods on real datasets extracted from open-source databases

  • 8.
    Carli, Ruggero
    et al.
    Department of Information Engineering, University of Padova.
    Notarstefano, Giuseppe
    Department of Engineering for Innovation, University of Salento.
    Schenato, Luca
    Department of Information Engineering, University of Padova.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Distributed quadratic programming under Asynchronous and Lossy Communications via Newton-Raphson Consensus2015In: 2015 European Control Conference (ECC): Linz, 15-17 July 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 2514-2520Conference paper (Refereed)
    Abstract [en]

    Quadratic optimization problems appear in several interesting estimation, learning and control tasks. To solve these problems in peer-to-peer networks it is necessary to design distributed optimization algorithms supporting directed, asynchronous and unreliable communication. This paper addresses this requirement by extending a promising distributed convex optimization algorithm, known as Newton-Raphson consensus, and originally designed for static and undirected communication. Specifically, we modify this algorithm so that it can cope with asynchronous, broadcast and unreliable lossy links, and prove that the optimization strategy correctly converge to the global optimum when the local cost functions are quadratic. We then support the intuition that this robustified algorithm converges to the true optimum also for general convex problems with dedicated numerical simulations.

  • 9.
    Ebadat, Afrooz
    et al.
    School of Electrical Engineering, KTH Royal Institute of Technology, ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology.
    Bottegal, Giulio
    School of Electrical Engineering, KTH Royal Institute of Technology, ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology.
    Molinari, Marco
    Kungliga tekniska högskolan, KTH, ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology.
    Wahlberg, Bo
    School of Electrical Engineering, KTH Royal Institute of Technology, ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Hjalmarsson, Håkan
    School of Electrical Engineering, KTH Royal Institute of Technology, ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology.
    Johansson, Karl Henrik
    School of Electrical Engineering, KTH Royal Institute of Technology, ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology.
    Multi-room occupancy estimation through adaptive gray-box models2015In: IEEE 54th Annual Conference on Decision and Control (CDC): Osaka, Japan, 15-18 Dec. 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 3705-3711, article id 7402794Conference paper (Refereed)
    Abstract [en]

    We consider the problem of estimating the occupancy level in buildings using indirect information such as CO2 concentrations and ventilation levels. We assume that one of the rooms is temporarily equipped with a device measuring the occupancy. Using the collected data, we identify a gray-box model whose parameters carry information about the structural characteristics of the room. Exploiting the knowledge of the same type of structural characteristics of the other rooms in the building, we adjust the gray-box model to capture the CO2 dynamics of the other rooms. Then the occupancy estimators are designed using a regularized deconvolution approach which aims at estimating the occupancy pattern that best explains the observed CO2 dynamics. We evaluate the proposed scheme through extensive simulation using a commercial software tool, IDA-ICE, for dynamic building simulation

  • 10.
    Ebadat, Afrooz
    et al.
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Bottegal, Giulio
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Wahlberg, Bo
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Hjalmarsson, Håkan
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Johansson, Karl Henrik
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Blind identification strategies for room occupancy estimation2015In: 2015 European Control Conference (ECC): Linz, 15-17 July 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 1315-1320, article id 7330720Conference paper (Refereed)
    Abstract [en]

    We propose and test on real data a two-tier estimation strategy for inferring occupancy levels from measurements of CO2 concentration and temperature levels. The first tier is a blind identification step, based either on a frequentist Maximum Likelihood method, implemented using non-linear optimization, or on a Bayesian marginal likelihood method, implemented using a dedicated Expectation-Maximization algorithm. The second tier resolves the ambiguity of the unknown multiplicative factor, and returns the final estimate of the occupancy levels. The overall procedure addresses some practical issues of existing occupancy estimation strategies. More specifically, first it does not require the installation of special hardware, since it uses measurements that are typically available in many buildings. Second, it does not require apriori knowledge on the physical parameters of the building, since it performs system identification steps. Third, it does not require pilot data containing measured real occupancy patterns (i.e., physically counting people for some periods, a typically expensive and time consuming step), since the identification steps are blind.

  • 11.
    Ebadat, Afrooz
    et al.
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Bottegal, Giulio
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Wahlberg, Bo
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Johansson, Karl H.
    Kungliga tekniska högskolan, KTH.
    Regularized Deconvolution-Based Approaches for Estimating Room Occupancies2015In: IEEE Transactions on Automation Science and Engineering, ISSN 1545-5955, E-ISSN 1558-3783, Vol. 12, no 4, p. 1157-1168Article in journal (Refereed)
    Abstract [en]

    We address the problem of estimating the number of people in a room using information available in standard HVAC systems. We propose an estimation scheme based on two phases. In the first phase, we assume the availability of pilot data and identify a model for the dynamic relations occurring between occupancy levels, CO2 concentration and room temperature. In the second phase, we make use of the identified model to formulate the occupancy estimation task as a deconvolution problem. In particular, we aim at obtaining an estimated occupancy pattern by trading off between adherence to the current measurements and regularity of the pattern. To achieve this goal, we employ a special instance of the so-called fused lasso estimator, which promotes piecewise constant estimates by including an l(1) norm-dependent term in the associated cost function. We extend the proposed estimator to include different sources of information, such as actuation of the ventilation system and door opening/closing events. We also provide conditions under which the occupancy estimator provides correct estimates within a guaranteed probability. We test the estimator running experiments on a real testbed, in order to compare it with other occupancy estimation techniques and assess the value of having additional information sources

  • 12.
    Ebadat, Afrooz
    et al.
    ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology, Sweden.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Bottegal, G
    TU Eindhoven, Department of Electrical Engineering, Eindhoven, The Netherlands.
    Wahlberg, Bo
    ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology, Sweden.
    Johansson, K. H.
    ACCESS and the Department of Automatic Control, School of Electrical Engineering, KTH Royal Institute of Technology, Sweden.
    Application-oriented input design for room occupancy estimation algorithms2018In: 2017 IEEE 56th Conference on Decision and Control, CDC, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 3417-3424Conference paper (Refereed)
    Abstract [en]

    We consider the problem of occupancy estimation in buildings using available environmental information. In particular, we study the problem of how to collect data that is informative enough for occupancy estimation purposes. We thus propose an application-oriented input design approach for designing the ventilation signal to be used while collecting the system identification datasets. The main goal of the method is to guarantee a certain accuracy in the estimated occupancy levels while minimizing the experimental time and effort. To take into account potential limitations on the actuation signals we moreover formulate the problem as a recursive nonlinear and nonconvex optimization problem, solved then using exhaustive search methods. We finally corroborate the theoretical findings with some numerical examples, which results show that computing ventilation signals using experiment design concepts leads to occupancy estimator performing 4 times better in terms of Mean Square Error (MSE).

  • 13. Eriksson, Martin
    et al.
    Lucchese, Riccardo
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Gustafsson, Jonas
    RISE - Swedish Institute of Computer Science.
    Ljung, Anna-Lena
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Monitoring and Modelling Open Compute Servers2017In: Proceedings IECON 2017: 43rd Annual Conference of the IEEE Industrial Electronics Society, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 7177-7184Conference paper (Refereed)
    Abstract [en]

    Energy efficient control of server rooms in modern data centers can help reducing the energy usage of this fast growing industry. Efficient control, however, cannot be achieved without: i) continuously monitoring in real-time the behavior of the basic thermal nodes within these infrastructures, i.e., the servers; ii) analyzing the acquired data to model the thermal dynamics within the data center. Accurate data and accurate models are indeed instrumental for implementing efficient data centers cooling strategies. In this paper we focus on a class of Open Compute Servers, designed in an open-source fashion and currently deployed by Facebook. We thus propose a set of methods for collecting real-time data from these platforms and a control-oriented model describing the thermal dynamics of the CPUs and RAMs of these servers as a function of both manipulable and exogenous inputs (e.g., the CPU utilization levels and the air mass flow produced by the server's fans). We identify the parameters of this model from real data and make the results available to other researchers.

  • 14.
    Fjällström, Eva
    et al.
    Luleå University of Technology, Department of Arts, Communication and Education, Education, Language, and Teaching.
    Knorn, Steffi
    Uppsala University.
    Staffas, Kjell
    Uppsala University.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Developing Concept Inventory Tests for Electrical Engineering: Extractable Information, Early Results, and Learned Lessons2018In: 2018 UKACC 12th International Conference on Control (CONTROL), 2018, p. 436-441, article id 8516766Conference paper (Refereed)
    Abstract [en]

    This paper suggests a method for developing, implementing and assessing a concept inventory test for electrical engineering students (CITE). The aim of this test is to help students better understand and learn core concepts, plus increase their awareness about links between the different courses and other themes of the program. Our and other experiences show that students often struggle to understand and use fundamental concepts, and how these relate to the various courses. This issue is probably due to the fact that traditional exams mainly focus on assessing procedural tasks (e.g., directly solving specific problems following step-by-step approaches). The investigated programs at Uppsala University (UU) and Luleå Uni-versity of Technology (LTU), nonetheless, have no tool for collecting quantitative data on how students develop conceptual knowledge throughout the programs, and thus no means to obtain an holistic view about their learning process. The here proposed methodology thus describes how to develop tests that would not only provide students with valuable feedback on their progression, but also equip teachers and program boards with high-end data for pedagogical and course development purposes. Besides illustrating the developmental methodology, the paper includes reactions and remarks from students on what the tests would provide and what would motivate them to take it.

  • 15.
    Guay, Martin
    et al.
    Department of Chemical Engineering, Queen's University, Kingston, ON, K7L 3N6, Canada.
    Atta, Khalid
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    An extremum-seeking control observer design technique for nonlinear systems2018In: 2017 IEEE 56th Conference on Decision and Control, CDC, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2018Conference paper (Refereed)
    Abstract [en]

    In this study, we propose an extremum-seeking control approach for the design on nonlinear observers for a general class of detectable nonlinear systems. The extremum-seeking control approach provides a mechanism to compute an observer gain that minimizes the squared output error. The technique extends and generalizes an earlier extremum seeking control observer design approach that was limited to systems in observer normal form with a linear state to output map. The analysis provides conditions for the application of the technique and establishes a semi-global practical stability property of the error dynamics. Two simulation examples are presented to demonstrate the effectiveness of the technique

  • 16.
    Knorn, Steffi
    et al.
    Signals and Systems, Uppsala University.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Melles, Reinhile
    Department of Psychology and Neuroscience, Clinical Psychological Science, Behavioural Medicine, Maastricht Universitair Medisch Centrum, Maastricht.
    Dewitte, Marieke
    Department of Psychology and Neuroscience, Clinical Psychological Science, Behavioural Medicine, Maastricht Universitair Medisch Centrum, Maastricht.
    Mathematical Modelling of Pressure Versus Pain Relations in Women Suffering From Dyspareunia2017In: Journal of Sexual Medicine, ISSN 1743-6095, E-ISSN 1743-6109, Vol. 14, no 5:Suppl. 4, p. e205-e350Article in journal (Refereed)
  • 17.
    Knorn, Steffi
    et al.
    Department of Engineering Sciences, Uppsala University, Sweden.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Oliver-Chiva, Ernesto
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Melles, Reinhilde
    Department of Psychology and Neuroscience, Clinical Psychological Science, Behavioural Medicine, Maastricht Universitair Medisch Centrum, Maastricht, The Netherlands.
    Dewitte, Marieke
    Department of Psychology and Neuroscience, Clinical Psychological Science, Behavioural Medicine, Maastricht Universitair Medisch Centrum, Maastricht, The Netherlands.
    Data-driven modelling of pelvic floor muscles dynamics2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 27, p. 321-326Article in journal (Refereed)
    Abstract [en]

    This paper proposes individualized, dynamical and data-driven models that describe pelvic floor muscle responses in women that use vaginal dilation. Specifically, the models describe how the volume of an inflatable balloon inserted at the vaginal introitus dynamically affects the aggregated pressure exerted by the pelvic floor muscles of the person. The paper inspects the approximation capabilities of different model structures, such as Hammerstein-Wiener and NARX, for this specific application, and finds the specific model structures and orders that best describe the recorded measurement data. Hence, although the current dataset is drawn from a sample of healthy volunteers, this paper is an initial step towards better understanding women’s responses to vaginal dilation and facilitating individualised medical vaginal dilation treatment.

  • 18.
    Lucchese, Riccardo
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Olsson, Jesper
    Luleå University of Technology.
    Ljung, Anna-Lena
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Garcia-Gabin, Winston
    ABB Corporate Research, Västerås.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Energy savings in data centers: A framework for modelling and control of servers’ cooling2017In: IFAC-PapersOnLine, ISSN 1045-0823, E-ISSN 1797-318X, Vol. 50, no 1, p. 9050-9057Article in journal (Refereed)
    Abstract [en]

    Aiming at improving the energy efficiency of air cooled servers in data centers, we devise a novel control oriented, nonlinear, thermal model of the servers that accounts explicitly for both direct and recirculating convective air flows. Instrumental to the optimal co-design of both geometries and cooling policies, we propose an identification methodology based on Computational Fluid Dynamics (CFD) for a generic thermal network of m fans and n electronic components. The performance of the proposed modelling framework is validated against CFD measurements with promising results. We formalize the minimum cooling cost control problem as a polynomially constrained Receding Horizon Control (RHC) and show, in-silico, that the resulting policy is able to efficiently modulate the cooling resources in spite of the unknown future computational and electrical power loads.

  • 19.
    Lucchese, Riccardo
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    A tight bound on the Bernoulli trials network size estimator2016In: 2016 IEEE 55th Conference on Decision and Control, CDC 2016, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 3474-3480, article id 7798790Conference paper (Refereed)
    Abstract [en]

    We consider the problem of finding exact statistical characterizations of the Bernoulli trials network size estimator, a simple algorithm for distributedly counting the number of agents in an anonymous communication network for which the probability of committing estimation errors scales down exponentially with the amount of information exchanged by the agents. The estimator works by cascading a local, randomized, voting step (i.e., the i.i.d. generation of some Bernoulli trials) with an average consensus on these votes. We derive a tight upper bound on the probability that this strategy leads to an incorrect estimate, and refine the offline procedure for selecting the Bernoulli trials success rate.

  • 20.
    Lucchese, Riccardo
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Average consensus via max consensus2015Article in journal (Refereed)
    Abstract [en]

    Since intuition states that it is simple and fast to compute maxima over networks, we aim at understanding the limits of computing averages over networks through computing maxima. We thus build on top of max-consensus based networks’ cardinality estimation protocols a novel estimation strategy that infers averages through computing maxima of opportunely and locally generated random initial conditions. We motivate the max-consensus strategy explaining why it satisfies practical requirements, we characterize completely its statistical properties, and we analyze when and under which conditions it performs favorably against classical linear consensus strategies in static Cayley graphs

  • 21.
    Lucchese, Riccardo
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Networks cardinality estimation using order statistics2015In: American Control Conference (ACC), 2015: Chicago, IL, 1-3 July 2015,, Piscataway, NJ: IEEE Communications Society, 2015, p. 3810-3817Conference paper (Refereed)
    Abstract [en]

    We consider a network of collaborative peers that aim at distributedly estimating the size of the network they belong to. We assume nodes to be endowed with unique identification numbers (IDs), and we study the performance of size estimators that are based on exchanging these IDs. Motivated by practical scenarios where the time-to-estimate is critical, we specifically address the case where the convergence time of the algorithm, i.e., the number of communications required to achieve the final estimate, is minimal. We thus construct estimators of the network size by exploiting statistical inference concepts on top of the distributed computation of order statistics of the IDs, i.e., of the M biggest IDs available in the network. We then characterize the statistical performance of these estimators from theoretical perspectives and show their effectiveness in practical estimation situations by means of numerical examples.

  • 22.
    Lucchese, Riccardo
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Delvenne, Jean-Charles
    Université Catholique de Louvain.
    Hendrickx, Julien M.
    Université Catholique de Louvain.
    Network cardinality estimation using max consensus: the case of Bernoulli trials2015In: IEEE 54th Annual Conference on Decision and Control (CDC): Osaka, Japan, 15-18 Dec. 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 895-901, article id 7402342Conference paper (Refereed)
    Abstract [en]

    Interested in scalable topology reconstruction strategies with fast convergence times, we consider network cardinality estimation schemes that use, as their fundamental aggregation mechanism, the computation of bit-wise maxima over strings. We thus discuss how to choose optimally the parameters of the information generation process under frequentist assumptions on the estimand, derive the resulting Maximum Likelihood (ML) estimator, and characterize its statistical performance as a function of the communications and memory requirements. We then numerically compare the bitwise-max based estimator against lexicographic-max based estimators, and derive insights on their relative performances in function of the true cardinality.

  • 23.
    Lucchese, Riccardo
    et al.
    University of Padova.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Johansson, Karl H.
    Kungliga tekniska högskolan, KTH.
    Distributed detection of topological changes in communication networks2014In: 19th IFAC World Congress on International Federation of Automatic Control: IFAC 2014, Cape Town, South Africa 24 - 29 August 2014, 2014, p. 1928-1934Conference paper (Refereed)
    Abstract [en]

    Changes in the topology of communication networks, such as sudden appearance or disappearance of links or nodes, may signal malicious attacks or malfunctions. A topology change detector may thus be useful to trigger alarms or self-reconfiguration procedures. Here we present a novel approach that enjoys several desirable qualities such as fast convergence, intrinsically distributed computations, and scalability w.r.t. communication and computational requirements. We characterize the performance of this technique from analytical and practical points of view, providing theoretical results on its performance. We thus show how it is possible to tune and trade-off the accuracy of the change detection results with the communication requirements of the procedure.

  • 24.
    Lucchese, Riccardo
    et al.
    University of Padova, Department of Information Engineering, University of Padova.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Johansson, Karl Henrik
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Distributed detection of topological changes in communication networks2014In: 19th IFAC World Congress on International Federation of Automatic Control: IFAC 2014, Cape Town, South Africa 24 - 29 August 2014 / [ed] X. Xia; E. Boje, IFAC, International Federation of Automatic Control , 2014, p. 1928-1934Conference paper (Refereed)
    Abstract [en]

    Changes in the topology of communication networks, such as sudden appearance or disappearance of links or nodes, may signal malicious attacks or malfunctions. A topology change detector may thus be useful to trigger alarms or self-reconfiguration procedures. Here we present a novel approach that enjoys several desirable qualities such as fast convergence, intrinsically distributed computations, and scalability w.r.t. communication and computational requirements. We characterize the performance of this technique from analytical and practical points of view, providing theoretical results on its performance. We thus show how it is possible to tune and trade-off the accuracy of the change detection results with the communication requirements of the procedure

  • 25.
    Mamikoglu, Umut
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Nikolakopoulos, George
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Pauelsen, Mascha
    Luleå University of Technology, Department of Health Sciences, Health and Rehab.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Röijezon, Ulrik
    Luleå University of Technology, Department of Health Sciences, Health and Rehab.
    Gustafsson, Thomas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Elbow Joint Angle Estimation by Using Integrated Surface Electromyography2016In: 24th Mediterranean Conference on Control and Automation (MED): June 21-24, Athens, Greece, 2016, Piscataway, NJ: IEEE Communications Society, 2016, p. 785-790, article id 7535891Conference paper (Refereed)
    Abstract [en]

    Electromyography (EMG) signals represent the electrical activation of skeletal muscles and contain valuable information about muscular activity. Estimation of the joint movements by using surface EMG signals has great importance as a bio-inspired approach for the control of robotic limbs and prosthetics. However interpreting surface EMG measurements is challenging due to the nonlinearity and user dependency of the muscle dynamics. Hence it requires complex computational methods to map the EMG signals and corresponding limb motions. To solve this challenge we here propose to use an integrated EMG signal to identify the EMG-joint angle relation instead of using common EMG processing techniques. Then we estimate the joint angles for elbow flexion-extension movement by using an auto-regressive integrated moving average with exogenous input (ARIMAX) model, which takes integrated EMG measurements as input. The experiments showed that the suggested approach results in a 21.85% average increase in the estimation performance of the elbow joint angle compared to the standard EMG processing and identification.

  • 26.
    Modolo, V.
    et al.
    University of Padova, Padova, Italy.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Carli, L.
    University of Padova, Padova, Italy.
    Distributed formation control using robust asynchronous and broadcast-based optimization schemes2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 23, p. 385-390Article in journal (Refereed)
    Abstract [en]

    We consider the problem of letting a network of mobile agents distributedly track and maintain a formation while using communication schemes that are asynchronous, broadcasts based, and prone to packet losses. To this purpose we revisit and modify an existing distributed optimization algorithm that corresponds to a distributed version of the Newton Raphson (NR) algorithm. The proposed scheme uses then robust asynchronous ratio consensus algorithms as building blocks, and employs opportune definitions for the local cost functions to achieve the desired coordination objective. In our algorithm, indeed, we code the position of the to-be-followed target as the minimum of a shared global cost, and capture the desired inter-robots behaviors through dedicated distances-based potential barriers. We then check the effectiveness of the strategy using field tests, and verify that the scheme achieves the desired goal of introducing robustness to changes in the agents positions due to unexpected disturbances. More precisely, if an agent breaks the formation, then the update mechanism embedded in our scheme make that agent move back to a meaningful position as soon as some packets are successfully received by the misplaced agent. 

  • 27.
    Mustafa, Mohammed Obaid
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Nikolakopoulos, George
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Gustafsson, Thomas
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Detecting broken rotor bars in induction motors with model-based support vector classifiers2016In: Control Engineering Practice, ISSN 0967-0661, E-ISSN 1873-6939, Vol. 52, p. 15-23Article in journal (Refereed)
    Abstract [en]

    We propose a methodology for testing the sanity of motors when both healthy and faulty data are unavailable. More precisely, we consider a model-based Support Vector Classification (SVC) method for the detection of broken bars in three phase asynchronous motors at full load conditions, using features based on the spectral analysis of the stator's steady state current (more specifically, the amplitude of the lift sideband harmonic and the amplitude at fundamental frequency). We diverge from the mainstream focus on using SVCs trained from measured data, and instead derive a classifier that is constructed entirely using theoretical considerations. The advantage of this approach is that it does not need training steps (an expensive, time consuming and often practically infeasible task), i.e., operators are not required to have both healthy and faulty data from a system for checking it. We describe what are the theoretical properties and fundamental limitations of using model based SVC methodologies, provide conditions under which using SVC tests is statistically optimal, and present some experimental results to prove the effectiveness of the suggested scheme.

  • 28.
    Parisio, Alessandra
    et al.
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Fabietti, Luca
    Kungliga tekniska högskolan, KTH.
    Molinari, Marco
    Kungliga tekniska högskolan, KTH.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Johansson, Karl Henrik
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Control of HVAC Systems via Scenario-based Explicit MPC2015In: 2014 IEEE 53rd Annual Conference on Decision and Control : (CDC 2014): Los Angeles, CA., 15-17 Dec. 2014, Piscataway, NJ: IEEE Communications Society, 2015, p. 5201-5207Conference paper (Refereed)
    Abstract [en]

    Improving energy efficiency of Heating, Ventilation and Air Conditioning (HVAC) systems is a primary objective for the society. Model Predictive Control (MPC) techniques for HVAC systems have recently received particular attention, since they can naturally account for several factors, such as weather and occupancy forecasts, comfort ranges and actuation constraints. Developing effective MPC based control strategies for HVAC systems is nontrivial, since buildings dynamics are nonlinear and affected by various uncertainties. Further, the complexity of the MPC problem and the burden of on-line computations can lead to difficulties in integrating this scheme into a building management system.We propose to address this computational issue by designing a scenario-based explicit MPC strategy, i.e., a controller that is simultaneously based on explicit representations of the MPC feedback law and accounts for uncertainties in the occupancy patterns and weather conditions by using the scenarios paradigm. The main advantages of this approach are the absence of a-priori assumptions on the distributions of the uncertain variables, the applicability to any type of building, and the limited on-line computational burden, enabling practical implementations on low-cost hardware platforms.We illustrate the practical implementation of the proposed explicit MPC controller on a room of a university building, showing its effectiveness and computational tractability.

  • 29.
    Parisio, Alessandra
    et al.
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Molinari, Marco
    Kungliga tekniska högskolan, KTH.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Johansson, Karl H.
    Kungliga tekniska högskolan, KTH.
    Control of HVAC Systems in Sweden: Current Status and Future Directions2014Conference paper (Other academic)
  • 30.
    Parisio, Alessandra
    et al.
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Molinari, Marco
    Kungliga tekniska högskolan, KTH.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Johansson, Karl H.
    Kungliga tekniska högskolan, KTH.
    Control of HVAC Systems in Sweden: Current Status and Future Directions2014Conference paper (Refereed)
  • 31.
    Parisio, Alessandra
    et al.
    School of Electrical and Electronic Engineering, The University of Manchester.
    Molinari, Marco
    School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Johansson, Karl H.
    ACCESS Linnaeus Centre, School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm.
    Energy Management Systems for Intelligent Buildings in Smart Grids2018In: Intelligent Building Control Systems: A Survey of Modern Building Control and Sensing Strategies / [ed] John T. Wen, Sandipan Mishra, Cham: Springer, 2018, p. 253-291Chapter in book (Refereed)
    Abstract [en]

    The next-generation electric grid needs to be smart and sustainable to simultaneously deal with the ever-growing global energy demand and achieve environmental goals. In this context, the role of residential and commercial buildings is crucial, due to their large share of primary energy usage worldwide. In this chapter, we describe energy management frameworks for buildings in a smart grid scenario. An Energy Management System (EMS) is responsible for optimally scheduling end-user smart appliances, heating systems, ventilation units, and local generation devices. We discuss the performance and the practical implementation of novel stochastic MPC schemes for HVAC systems, and illustrate how these schemes take into account several sources of uncertainties, e.g., occupancy and weather conditions. Furthermore, we show how to integrate local generation capabilities and storage systems into a holistic building energy management framework.

  • 32.
    Parisio, Alessandra
    et al.
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Molinari, Marco
    Kungliga tekniska högskolan, KTH.
    Pattarello, Giorgio
    Kungliga tekniska högskolan, KTH.
    Fabietti, Luca
    Kungliga tekniska högskolan, KTH.
    Johansson, Karl H.
    Kungliga tekniska högskolan, KTH.
    Implementation of a Scenario-based MPC for HVAC Systems: an Experimental Case Study2014In: 19th IFAC World Congress on International Federation of Automatic Control: IFAC 2014, Cape Town, South Africa 24 - 29 August 2014, 2014, p. 599-605Conference paper (Refereed)
    Abstract [en]

    Heating, Ventilation and Air Conditioning (HVAC) systems play a fundamental role in maintaining acceptable thermal comfort and air quality levels. Model Predictive Control (MPC) techniques are known to bring significant energy savings potential. Developing effective MPC-based control strategies for HVAC systems is nontrivial since buildings dynamics are nonlinear and influenced by various uncertainties. This complicates the use of MPC techniques in practice. We propose to address this issue by designing a stochastic MPC strategy that dynamically learns the statistics of the building occupancy patterns and weather conditions. The main advantage of this method is the absence of a-priori assumptions on the distributions of the uncertain variables, and that it can be applied to any type of building. We investigate the practical implementation of the proposed MPC controller on a student laboratory, showing its effectiveness and computational tractability.

  • 33.
    Parisio, Alessandra
    et al.
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Molinari, Marco
    Kungliga tekniska högskolan, KTH, School of Electrical Engineering, Royal Institute of Technology, Stockholm.
    Pattarello, Giorgio
    Kungliga tekniska högskolan, KTH, School of Electrical Engineering, Royal Institute of Technology, Stockholm.
    Fabietti, Luca
    Kungliga tekniska högskolan, KTH, Department of Information Engineering, University of Padova.
    Johansson, Karl Henrik
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Implementation of a scenario-based MPC for HVAC systems: An experimental case study2014In: 19th IFAC World Congress on International Federation of Automatic Control: IFAC 2014, Cape Town, South Africa 24 - 29 August 2014 / [ed] X. Xia; E. Boje, IFAC, International Federation of Automatic Control , 2014, p. 599-605Conference paper (Refereed)
    Abstract [en]

    Heating, Ventilation and Air Conditioning (HVAC) systems play a fundamental role in maintaining acceptable thermal comfort and air quality levels. Model Predictive Control (MPC) techniques are known to bring significant energy savings potential. Developing effective MPC-based control strategies for HVAC systems is nontrivial since buildings dynamics are nonlinear and influenced by various uncertainties. This complicates the use of MPC techniques in practice. We propose to address this issue by designing a stochastic MPC strategy that dynamically learns the statistics of the building occupancy patterns and weather conditions. The main advantage of this method is the absence of a-priori assumptions on the distributions of the uncertain variables, and that it can be applied to any type of building. We investigate the practical implementation of the proposed MPC controller on a student laboratory, showing its effectiveness and computational tractability.

  • 34.
    Pillonetto, Gianluigi
    et al.
    Information Engineering, University of Padova.
    Schenato, Luca
    Department of Information Engineering, University of Padova.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Distributed multi-agent Gaussian regression via finite-dimensional approximations2019In: IEEE Transaction on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, E-ISSN 1939-3539, Vol. 41, no 9, p. 2098-2111Article in journal (Refereed)
    Abstract [en]

    We consider the problem of distributedly estimating Gaussian processes in multi-agent frameworks. Each agent collects few measurements and aims to collaboratively reconstruct a common estimate based on all data. Agents are assumed with limited computational and communication capabilities and to gather M noisy measurements in total on input locations independently drawn from a known common probability density. The optimal solution would require agents to exchange all the M input locations and measurements and then invert an M×M matrix, a non-scalable task. Differently, we propose two suboptimal approaches using the first E orthonormal eigenfunctions obtained from the Karhunen-Loève (KL) expansion of the chosen kernel, where typically E≪M. The benefits are that the computation and communication complexities scale with E and not with M, and computing the required statistics can be performed via standard average consensus algorithms. We obtain probabilistic non-asymptotic bounds that determine a priori the desired level of estimation accuracy, and new distributed strategies relying on Stein's unbiased risk estimate (SURE) paradigms for tuning the regularization parameters and applicable to generic basis functions (thus not necessarily kernel eigenfunctions) and that can again be implemented via average consensus. The proposed estimators and bounds are finally tested on both synthetic and real field data.

  • 35.
    Pillonetto, Gianluigi
    et al.
    Department of Information Engineering, University of Padova, Padova, Italy.
    Schenato, Luca
    Department of Information Engineering, University of Padova, Padova, Italy.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Statistical bounds for Gaussian regression algorithms based on Karhunen-Loève expansions2018In: 2017 IEEE 56th Conference on Decision and Control, CDC, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 363-368Conference paper (Refereed)
    Abstract [en]

    We consider the problem of estimating functions in a Gaussian regression distributed and nonparametric framework where the unknown map is modeled as a Gaussian random field whose kernel encodes expected properties like smoothness. We assume that some agents with limited computational and communication capabilities collect M noisy function measurements on input locations independently drawn from a known probability density. Collaboration is then needed to obtain a common and shared estimate. When the number of measurements M is large, computing the minimum variance estimate in a distributed fashion is difficult since it requires first to exchange all the measurements and then to invert an M χ M matrix. A common approach is then to circumvent this problem by searching a suboptimal solution within a subspace spanned by a finite number of kernel eigenfunctions. In this paper we analyze this classical distributed estimator, and derive a rigorous probabilistic bound on its statistical performance that returns crucial information on the number of measurements and eigenfunctions needed to obtain the desired level of estimation accuracy.

  • 36.
    Sandberg, Marcus
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Industrilized and sustainable construction.
    Risberg, Mikael
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.
    Ljung, Anna-Lena
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Fluid and Experimental Mechanics.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Xiong, Damiano
    Sveriges Lantbruksuniversitet.
    Nilsson, Michael
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Distance- Spanning Technology.
    A modelling methodology for assessing use of datacenter waste heat in greenhouses2017Conference paper (Refereed)
    Abstract [en]

    In Sweden, the number of datacenters establishments are steadily increasing thanks to green, stable and affordable electricity, free air cooling, advantageous energy taxes and well-developed Internet fiber infrastructures. Even though datacenters use a lot of energy, the waste heat that they create is seldom reused. A possible cause is that this waste heat is often low grade and airborne: it is therefore hard to directly inject it into a district heating system without upgrades, which require additional energy and equipment that generate extra costs. One option for reusing this heat without needs for upgrades is to employ it for heating up greenhouses. But assessing the feasibility of this approach by building physical prototypes can be costly, therefore using computer models to simulate real world conditions is an opportunity. However, there is a lack of computer modelling methodologies that can assess the possibility of using waste heat from datacenters in greenhouses in cold climates.

    The objective of this paper is therefore to propose such a methodology and discuss its benefits and drawbacks in comparison with other research studies. This methodology combines computational fluid dynamics, process modelling and control engineering principles into a computer model that constitutes a decision support system to study different waste heat and greenhouse or mushroom house scenarios.

    The paper validates the strategy through a case study in northern Sweden, where we assess the amount of produced waste heat by collecting temperature, relative humidity, and fan speed data for the air discharged from the datacenter.

    The resulting methodology, composed by conducting measurements and computer models, calculations can then be used for other datacenter operators or greenhouse developers to judge whether it is possible or not to build greenhouses using datacenter waste heat.

  • 37.
    Varagnolo, Damiano
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Detecting and modelling air flow overprovisioning / underprovisioning in air-cooled datacenters2018In: IECON 2018: 44th Annual Conference of the IEEE Industrial Electronics Society, 2018Conference paper (Refereed)
  • 38.
    Varagnolo, Damiano
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Knorn, Steffi
    Department of Engineering Sciences, Uppsala University.
    Melles, Reinhilde
    Department of Psychology and Neuroscience, Clinical Psychological Science, Behavioural Medicine, Maastricht Universitair Medisch Centrum, Maastricht.
    Dewitte, Marieke
    Department of Psychology and Neuroscience, Clinical Psychological Science, Behavioural Medicine, Maastricht Universitair Medisch Centrum, Maastricht.
    Qualitative modeling of pressure vs. pain relations in women suffering from dyspareunia2017In: IFAC-PapersOnLine, ISSN 1045-0823, E-ISSN 1797-318X, Vol. 50, no 1, p. 2043-2050Article in journal (Refereed)
    Abstract [en]

    Genital pain / penetration disorders affect a significant portion of the female population and diminish significantly the quality of life of the subjects. Treatments, that often consist in stretching opportunely the vaginal duct by means of opportune vaginal dilators, are known to be invasive, lengthy and uncomfortable. Designing better treatments (e.g., more efficient locations and levels of pressures) nonetheless requires understanding better how the pressure developed in the vaginal channel affects the patient and leads to subjective pain. Here we take a control-oriented approach to the problem, and aim at describing the dynamics of the pressure vs. pain mechanisms by means of opportune state space representations. In particular, we first collect and discuss the medical literature, that describes how the variables that are involved in the treatment of genital pain / penetration disorders with vaginal dilators, are logically related. After this we translate (and complete) this set of logical relations into a qualitative model that allows control oriented analyses of the dynamics. The obtained state space model is then proved to both mimic correctly what is expected from logical perspectives and reproduce behaviors measured in clinical settings.

  • 39.
    Varagnolo, Damiano
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Knorn, Steffi
    Uppsala University.
    Oliver Chiva, Ernesto
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Melles, R.J.
    Maastricht University Medical Center.
    Dewitte, Marieke
    Maastricht University.
    Towards the individualization of vaginal dilatation exercises: A Quantitative analysis of the variability of vaginal pressure responses2018In: Journal of Sexual Medicine, ISSN 1743-6095, E-ISSN 1743-6109, Vol. 15, no 7 : Suppl. 3, p. S303-Article in journal (Refereed)
  • 40.
    Varagnolo, Damiano
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Knorn, Steffi
    Department of Engineering Sciences, Uppsala University.
    Oliver-Chiva, Ernesto
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Melles, Reinhilde
    Department of Psychology and Neuroscience, Clinical Psychological Science, Behavioural Medicine, Maastricht Universitair Medisch Centrum, Maastricht.
    Dewitte, Marieke
    Department of Psychology and Neuroscience, Clinical Psychological Science, Behavioural Medicine, Maastricht Universitair Medisch Centrum, Maastricht.
    Data-driven modelling of subjective pain/pleasure assessments as responses to vaginal dilation stimuli2018In: IEEE Control Systems Letters, E-ISSN 2475-1456, Vol. 2, no 3, p. 423-428Article in journal (Refereed)
    Abstract [en]

    Women affected by pain during penetrative sexual intercourse are often treated using fixed-size vaginal dilators that are regularly perceived as uncomfortable and leading to premature treatment drop-outs. These dilators could be improved by making them adaptive, i.e., able to exert dynamically different pressures on the vaginal duct to simultaneously guarantee comfort levels and achieve the medical dilation objectives. Implementing feedback control would then benefit from models that connect the patients’ comfort levels with their experienced physiological stimuli. Here we address the problem of data-driven quantitative modelling of pain/pleasure self-assessments obtained through medical trials. More precisely, we consider time-series records of Pelvic Floor Muscles (PFM) pressure, vaginal dilation, and pain/pleasure evaluations, and model the relations among these quantities using statistical analysis tools. Besides this, we also address the important issue of the individualization of these models: different persons may respond differently, but these variations may sometimes be so small that it may be beneficial to learn from several individuals simultaneously. We here numerically validate the previous claim by verifying that clustering patients in groups may lead, from a data-driven point of view, to models with a significantly improved statistical performance.

  • 41.
    Varagnolo, Damiano
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Pillonetto, Gianluigi
    Department of Information Engineering, University of Padova.
    Schenato, Luca
    Department of Information Engineering, University of Padova.
    Auto-tuning procedures for distributed nonparametric regression algorithms2015In: 2015 European Control Conference (ECC): Linz, 15-17 July 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 640-647Conference paper (Refereed)
    Abstract [en]

    We propose a distributed regression algorithm with the capability of automatically calibrating its parameters during its on-line functioning. The estimation procedure corresponds to a Regularization Network, i.e., the structural form of the estimator is a linear combination of basis functions which coefficients are computed by solving a linear system. The automatic tuning strategy instead constructs and then exploits opportune bounds on the distance between the distributed estimation results and the unknown centralized optimal estimate that would be computed processing the whole dataset at once. By numerical simulations we show how the proposed procedure allows the sensor networks to effectively self-tune the parameters of the distributed regression scheme by simple consensus strategies.

  • 42.
    Varagnolo, Damiano
    et al.
    School of Electrical Engineering, KTH Royal Institute of Technology.
    Pillonetto, Gianluigi
    Department of Information Engineering, University of Padova.
    Schenato, Luca
    Department of Information Engineering, University of Padova.
    Distributed Cardinality Estimation in Anonymous Networks2014In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 59, no 3, p. 645-659Article in journal (Refereed)
  • 43.
    Varagnolo, Damiano
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
    Zanella, Filippo
    Department of Information Engineering, University of Padova.
    Cenedese, Angelo
    Department of Information Engineering, University of Padova.
    Pillonetto, Gianluigi
    Department of Information Engineering, University of Padova.
    Schenato, Luca
    Department of Information Engineering, University of Padova.
    Newton-Raphson Consensus for Distributed Convex Optimization2016In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 61, no 4, p. 994-1009Article in journal (Refereed)
    Abstract [en]

    We address the problem of distributed unconstrained convex optimization under separability assumptions, i.e., the framework where each agent of a network is endowed with a local private multidimensional convex cost, is subject to communication constraints, and wants to collaborate to compute the minimizer of the sum of the local costs. We propose a design methodology that combines average consensus algorithms and separation of time-scales ideas. This strategy is proved, under suitable hypotheses, to be globally convergent to the true minimizer. Intuitively, the procedure lets the agents distributedly compute and sequentially update an approximated Newton-Raphson direction by means of suitable average consensus ratios. We show with numerical simulations that the speed of convergence of this strategy is comparable with alternative optimization strategies such as the Alternating Direction Method of Multipliers. Finally, we propose some alternative strategies which trade-off communication and computational requirements with convergence speed

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