Persona: Dormido Canto, Sebastián
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Dormido Canto
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Sebastián
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Publicación An event-based adaptation of the relay feedback experiment for frequency response identification of stable processes(Elsevier, 2023-04-13) Sánchez Moreno, José; Torre Cubillo, Luis de la; Chacón Sombría, Jesús; Dormido Canto, Sebastián; Elsevier; https://orcid.org/0000-0003-0898-3462An event-based modification of the classical relay feedback experiment without the inclusion of additional elements (integrator, time delay, . . . ) for identification of the spectrum of stable processes between zero and the phase cross-over frequency is presented. By inserting an event-based sampler in the control loop, the natural behaviour of a classical relay is simulated and the system is forced to work in two modes. The event-based sampler activates the first mode by sending control actions to the process every time the error signal crosses zero; this mode is to discover the approximated value of the cross-over frequency ω180◦ . During the second mode, the event-based sampler sends samples to the process simulating that the error signal crosses zero at ω180◦ /N where N is the number of points to identify in the range 0 ≤ ω ≤ ω180◦ . One advantage of this procedure is that the logic used in an already existing relay feedback experiment to fit a transfer function model or tune a controller could be maintained just replacing the relay block by the event-based sampler block presented in the paper. Simulations and experiments with different processes and in presence of noise demonstrate the effectivity of the procedure.Publicación Simulation and Experimental Results of a New Control Strategy For Point Stabilization of Nonholonomic Mobile Robots(IEEE, 2019-08-22) Farias, Gonzalo; Garcia, Gonzalo; Dormido Bencomo, Sebastián; Fábregas Acosta, Ernesto; Aranda Escolástico, Ernesto; Chaos García, Dictino; Dormido Canto, SebastiánThis article presents a closed-loop position control of a mobile robot, which is capable of moving from its current position to a target point by manipulating its linear and angular velocities. The main objective of this article is to modify an existing control law based on the kinematic model to improve the response when the robot is backwards oriented and to reach the destination point in less time and with a shorter trajectory. Stability of the proposed control law is validated by Lyapunov Criterion. Some procedures are implemented to test this approach both in simulation with MATLAB, and experimentally with the Khepera IV robot.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 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 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 Obtaining high preventive and resilience capacities in critical infrastructure by industrial automation cells(Elsevier, 2020-06) González, Santiago G.; Dormido Canto, Sebastián; Sánchez Moreno, JoséThe advances in Information Technologies (ITs) are providing Industrial Control Systems (ICS) with a great capacity for interconnection and adaptability. However, the use of communication networks makes ICS highly vulnerable. Consequently, it is essential to develop methodologies for the identification and subsequent classification of the ICS that intervene in critical infrastructure assets with any level of complexity, scalability and heterogeneity. The System and Infrastructure of Knowledge for Real Experimentation by means of Cells of Industrial Automation (SIKRECIA), described in this work, provides new capabilities for research, development, simulation and testing of the functioning of these systems, and the ability to foresee the behavior of a specific system in industrial production. The scenarios recreated through SIKRECIA have the ability to anticipate new threats that affect the ICS of critical infrastructures. Using SIKRECIA, a specific vulnerability of a PLC has been verified through the engineering programmed for the management of a traffic light control system. The results obtained demonstrate the high dependence between IT and OT (Operation Technologies) systems and therefore the importance of being able to recreate those environments before entering into operation. As SIKRECIA is an open system, it can use components from different industrial manufacturers to cover the existing architectures in the process industry.Publicación Disruption prediction with artificial intelligence techniques in tokamak plasmas(Springer Nature, 2022-06-06) Vega, J.; Murari, A.; Rattá, Giuseppe A.; Gelfusa, Michela; Contributors, JET.; Dormido Canto, SebastiánIn nuclear fusion reactors, plasmas are heated to very high temperatures of more than 100 million kelvin and, in so-called tokamaks, they are confined by magnetic fields in the shape of a torus. Light nuclei, such as deuterium and tritium, undergo a fusion reaction that releases energy, making fusion a promising option for a sustainable and clean energy source. Tokamak plasmas, however, are prone to disruptions as a result of a sudden collapse of the system terminating the fusion reactions. As disruptions lead to an abrupt loss of confinement, they can cause irreversible damage to present-day fusion devices and are expected to have a more devastating effect in future devices. Disruptions expected in the next-generation tokamak, ITER, for example, could cause electromagnetic forces larger than the weight of an Airbus A380. Furthermore, the thermal loads in such an event could exceed the melting threshold of the most resistant state-of-the-art materials by more than an order of magnitude. To prevent disruptions or at least mitigate their detrimental effects, empirical models obtained with artificial intelligence methods, of which an overview is given here, are commonly employed to predict their occurrence—and ideally give enough time to introduce counteracting measures.Publicación A Study of Strategies for Developing Online Laboratories(IEEE, 2021-12-01) Sáenz Valiente, Jacobo; Torre Cubillo, Luis de la; Chacón Sombría, Jesús; Dormido Canto, SebastiánResearchers and teachers around the world have created newsoftware and hardware to develop, reuse, and deploy online laboratories (labs). However, due to the nature of labs, most of the available solutions depend greatly on where and how online labs can be used in the first place. Thus, there have been multiple design solutions and great technology combinations. In this study, we analyzed and studied the main obstacles in the online lab development and the alternatives of the technologies, means, methodologies, and approaches on creating online labs. The resulting analysis showed the advantages, disadvantages, and problems of each key component and attempted to explore the working combinations that ensure the usability, modularity, universality, accessibility, and reliability of online labs. In addition, we explored a general solution to take advantage of the benefits of the technologies involved in online labs and to fix or reduce the impacts of the arising problems when developing and deploying online labs.Publicación The Ball and Beam System: A Case Study of Virtual and Remote Lab Enhancement With Moodle(IEEE (Institute of Electrical and Electronics Engineers), 2015-06-10) Torre Cubillo, Luis de la; Guinaldo Losada, María; Heradio Gil, Rubén; Dormido Canto, SebastiánWeb-based labs are key tools for distance education that help to illustrate scientific phenomena, which require costly or difficult-to-assemble equipment. Easy Java Simulations (EJS) is an authoring tool that speeds up the creation of these kind of labs. An excellent proof of the EJS potential is the open source physics (OSP) repository, which hosts hundreds of free EJS labs. Learning management systems, such as Moodle, provide social contexts where students interact with each other. The work described in this paper looks for the synergy of both tools, EJS and Moodle, by supporting the deployment of EJS labs into Moodle and thus enriching them with social features (e.g., chat, forums, and videoconference). To test this approach, the authors have created the ball and beam lab, which helps students of automatic control engineering to train different advanced techniques (robust, fuzzy, and reset control), and compare their performance in relation to a conventional proportional-integral-derivative control.
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