Persona: Dormido Canto, Sebastián
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sebas@dia.uned.es
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0000-0001-7652-5338
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Dormido Canto
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Sebastián
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Publicación Control education for societal-scale challenges: A community roadmap(ELSEVIER, 2023-03-17) Rossiter, John Anthony; Cassandras, Christos G.; Hespanha, João; Dormido Canto, Sebastián; Torre Cubillo, Luis de la; Ranade, Gireeja; Visioli, Antonio; Hedengren, John; Murray, Richard M.; Antsaklis, Panos; Lamnabhi Lagarrigue, Francoise; Parisini, ThomasThis article focuses on extending, disseminating and interpreting the findings of an IEEE Control Systems Society working group looking at the role of control theory and engineering in solving some of the many current and future societal challenges. The findings are interpreted in a manner designed to give focus and direction to both future education and research work in the general control theory and engineering arena, interpreted in the broadest sense. The paper is intended to promote discussion in the community and also provide a useful starting point for colleagues wishing to re-imagine the design and delivery of control-related topics in our education systems, especially at the tertiary level and beyond.Publicación Asynchronous periodic event-triggered control with dynamical controllers(Elsevier, 2018-04-20) Aranda Escolástico, Ernesto; Rodríguez, Carlos; Guinaldo Losada, María; Guzmán, José Luis; Dormido Canto, SebastiánIn this work, we study a networked control system under a periodic eventtriggered control strategy. In addition, the input and the output of the system are sampled with different rates, which enables to obtain a compromise between performance and waste of communication resources. Stability analysis and L2-gain analysis are carried out through Lyapunov-Krasovskii techniques. Simulation results of a quadruple-tank process show the benefits of the approach.Publicación Design of periodic event-triggered control for polynomial systems: A delay system approach(Elsevier, 2017-10-17) Aranda Escolástico, Ernesto; Abdelrahim, M.; Guinaldo Losada, María; Dormido Canto, Sebastián; Heemels, W.P.M.H.Event-triggered control is a control strategy which allows the savings of communication resources in networked control systems. In this paper, we are interested in periodic eventtriggering mechanisms in the sense that the triggering condition is only verified at predefined periodic sampling instants, which automatically ensures that Zeno behavior does not occur. We consider the case where both the output measurement and the control input are transmitted asynchronously using two independent triggering conditions. The developed result is dedicated to a class of nonlinear systems, where both the plant model and the feedback law can be described by polynomial functions. The overall problem is modeled and analyzed in the framework of time-delay systems, which allows to derive sum-of-squares (SOS) conditions to guarantee the global asymptotic stability in terms of the sampling period and the parameters of the triggering conditions. The approach is illustrated on a nonlinear numerical example.Publicación Adaptive predictors based on probabilistic SVM for real time disruption mitigation on JET(IOP Publishing, 2018-03-02) Murari, A.; Lungaroni, M.; Peluso, E.; Gaudio, P.; Vega, J.; Baruzzo, M.; Gelfusa, Michela; Contributors, JET.; Dormido Canto, SebastiánDetecting disruptions with sufficient anticipation time is essential to undertake any form of remedial strategy, mitigation or avoidance. Traditional predictors based on machine learning techniques can be very performing, if properly optimised, but do not provide a natural estimate of the quality of their outputs and they typically age very quickly. In this paper a new set of tools, based on probabilistic extensions of support vector machines (SVM), are introduced and applied for the first time to JET data. The probabilistic output constitutes a natural qualification of the prediction quality and provides additional flexibility. An adaptive training strategy 'from scratch' has also been devised, which allows preserving the performance even when the experimental conditions change significantly. Large JET databases of disruptions, covering entire campaigns and thousands of discharges, have been analysed, both for the case of the graphite and the ITER Like Wall. Performance significantly better than any previous predictor using adaptive training has been achieved, satisfying even the requirements of the next generation of devices. The adaptive approach to the training has also provided unique information about the evolution of the operational space. The fact that the developed tools give the probability of disruption improves the interpretability of the results, provides an estimate of the predictor quality and gives new insights into the physics. Moreover, the probabilistic treatment permits to insert more easily these classifiers into general decision support and control systems.Publicación Assessment of linear disruption predictors using JT-60U data(Elsevier, 2019-09) Vega, J.; Hernández del Olmo, Félix; Isayama, A.; Joffrin, E.; Matsunaga, G.; Suzuki, T.; Dormido Canto, SebastiánDisruptions are dangerous events in tokamaks that require mitigation methods to alleviate its detrimental effects. A prerequisite to trigger any mitigation action is the existence of a reliable disruption predictor. This article assesses a predictor that relates in a linear way consecutive samples of a single quantity (in particular, the magnetic perturbation time derivative signal has been used). With this kind of predictor, the recognition of disruptions does not depend on how large the signal amplitude is but on how large the signal increments are: small increments mean smooth plasma evolution whereas abrupt increments reflect a non-smooth evolution and potential risk of disruption. Results are presented with data from the JT-60U tokamak and high-beta discharges. Two training methods have been tested: a classical approach in which the more data for training the better and an adaptive method that starts from scratch. In both cases the success rate is about 95%. It should be noted that predictors based on signal increments and their adaptive versions can be of big interest for next devices such as JT-60SA or ITER.Publicación A linear equation based on signal increments to predict disruptive behaviours and the time to disruption on JET(IOP Publishing, 2019-12-13) Vega, J.; Murari, A.; Hernández del Olmo, Félix; Cruz, T.; Gadariya, Dhaval; Rattá, Giuseppe A.; Contributors, JET.; Dormido Canto, SebastiánThis article describes the development of a generic disruption predictor that is also used as basic system to provide an estimation of the time to disruption at the alarm times. The mode lock signal normalised to the plasma current is used as input feature. The recognition of disruptive/non-disruptive behaviours is not based on a simple threshold of this quantity but on the evolution of the amplitudes between consecutive samples taken periodically. The separation frontier between plasma behaviours (disruptive/non-disruptive) is linear in such parameter space. The percentages of recognised and false alarms are 98% and 4%, respectively. The recognised alarms can be split into valid alarms (90%) and late detections (8%). The experimental distribution of warning times follows an exponential model with average warning time of 443 ms. On the other hand, the prediction of the time to the disruption has been fitted to a Weibull model that relates this predicted time to the distance of the points to the diagonal in the parameter space of consecutive samples. The model shows a very good agreement between predicted times and warning times in narrow time intervals (between 0.01 s and 0.06 s) before the disruption.Publicación Evidence-Based Control Engineering Education: Evaluating the LCSD Simulation Tool(IEEE, 2020-09-25) Marin, Loreto; Vargas, Héctor; Heradio Gil, Rubén; Torre Cubillo, Luis de la; Díaz Martínez, José Manuel; Dormido Canto, SebastiánThe advance in control engineering education needs well-designed studies that validate what methods and tools work best. This paper addresses the lack of empirical evidence supporting innovations in control engineering education by proposing a methodology that works at different abstraction levels. Hence, innovations' impact on students' performance can be statistically analyzed either globally or locally by examining competencies or fine-grained indicators, respectively. The article reports the application of the methodology for evaluating an interactive simulation tool, named LCSD, on 101 students at the Pontifical Catholic University of Valparaiso in Chile. According to the experimental results, LCSD is an effective free alternative to enhance the student's skills on control system analysis for our automatic control course. Also, some improvements have been identified for future LCSD versions.Publicación Development of a Web-Based Control Laboratory for Automation Technicians: The Three-Tank System(IEEE TRANSACTIONS ON EDUCATION, 2007-01-01) Vargas Oyarzún, Héctor; Dormido Bencomo, Sebastián; Dormido Canto, Raquel; Duro Carralero, Natividad; Sánchez Moreno, José; Dormido Canto, Sebastián; Farias, GonzaloPublicación Control problems in marine vehicles: Some experiences in stabilization and tracking control(2006-01-01) Cruz García, Jesús Manuel de la; Riola Rodríguez, José María; Aranda Almansa, Joaquín; Muñoz Mansilla, María del Rocío; Chaos García, Dictino; Díaz Martínez, José Manuel; Dormido Canto, SebastiánPublicación What remote labs can do for you(AIP Publishing, 2016-04-01) Torre Cubillo, Luis de la; Sánchez Fernández, Juan Pedro; Dormido Canto, SebastiánThe Internet of Things (IoT) is the network of physical devices connected to the internet. Online connections enable users to remotely monitor the devices and their surroundings or to actively control them through sensors and actuators. As the technology has progressed, the importance of the IoT has grown tremendously. According to the McKinsey Global Institute, the IoT’s annual economic impact could reach $11 trillion by 2025. That figure represents about 10% of today’s world economy.1 Bullish sounding at first, the prediction is not so ridiculous if one stops to think about how deeply internet technologies have already penetrated today’s society. Consider, for example, mobile devices—those smartphones and tablets everybody carries nowadays. A typical modern smartphone has numerous sensors that allow it to capture the device’s orientation, location, ambient light conditions, and much more. And it is frequently connected to the internet. A world filled with such internet-connected devices opens...