Persona: Dormido Canto, Sebastián
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0000-0001-7652-5338
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Dormido Canto
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Sebastián
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Publicación UN PROBLEMA BENCHMARK DE CONTROL NO LINEAL: ESTABILIZACIÓN Y SEGUIMIENTO DE TRAYECTORIA DE UN AERODESLIZADOR DE RADIO CONTROL(Comité Español de Automática, 2006-09-06) Aranda Almansa, Joaquín; Chaos García, Dictino; Dormido Canto, Sebastián; Muñoz Mansilla, María del Rocío; Díaz Martínez, José ManuelPublicación 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 Interactive software tools for robust control: application to marine systems(Robotics and Automation in the Maritime Industries, 2006-01-01) Dormido Bencomo, Sebastián; Díaz Martínez, José Manuel; Aranda Almansa, Joaquín; Dormido Canto, Sebastián; Muñoz Mansilla, María del Rocío; Chaos García, DictinoPublicación An Overview about Dynamic Positioning of Ships(Automation for the Maritime Industries, 2004-01-01) Hernández Cuesta, Carlos; Aranda Almansa, Joaquín; Díaz Martínez, José Manuel; Dormido Canto, Sebastián; Muñoz Mansilla, María del RocíoPublicación A new control laboratory using parallel programming(2007-11-28) Dormido Bencomo, Sebastián; Dormido Canto, Sebastián; Sánchez Moreno, JoséPublicación Decoupled feedforward-feedback periodic event-triggered control for disturbance rejection(Elsevier, 2021-04-14) Aranda Escolástico, Ernesto; Guinaldo Losada, María; Guzmán, José Luis; Dormido Canto, SebastiánIn this paper, feedforward and feedback controllers are studied considering decoupled periodic event-triggering mechanisms for output and disturbance sensors. Stability and robustness conditions for linear systems are obtained considering transportation delays and actuator saturation following the Lyapunov-Krasovskii procedure. A numerical example shows that the proposed control strategy reduces the communication between sensors and controller significantly, while the system performance is not deteriorated.Publicación About Identification of Mathematical Models for High Speed Crafts(Automation for the Maritime Industries, 2004-01-01) Dormido Bencomo, Sebastián; Muñoz Mansilla, María del Rocío; Aranda Almansa, Joaquín; Díaz Martínez, José Manuel; Dormido Canto, SebastiánPublicación A novel feature engineering approach for high-frequency financial data(Elsevier, 2023-10) Mantilla, Pablo; Dormido Canto, SebastiánFeature engineering for high-frequency financial data based on constructing dynamic data subsets, defined by time intervals in which high-frequency trends occur, is proposed. These intervals are obtained through time series segmentation. This methodology allows us to extract and analyze variables by intraday trends as well as to feed artificial intelligence models to forecast response variables in future trends. Furthermore, to show how to use this feature engineering, this methodology is applied to estimate high-frequency volatility, duration and direction linked to future intraday trends, developing multiclass classification models based on the machine learning method extreme gradient boosting. Experimentation was conducted using high-frequency financial data from the Brazil Stock Exchange, corresponding to 206 trading days related to 20 listed assets from this financial market.Publicación Benchmark Control Problems for a Non-Linear Underactuated Hovercraft: A Simulation Laboratory for Control Testing(INTERNATIONAL FEDERATION OF AUTOMATIC CONTROL, 2006-01-01) Aranda Almansa, Joaquín; Chaos García, Dictino; Dormido Canto, Sebastián; Muñoz Mansilla, María del Rocío; Díaz Martínez, José ManuelLos aerodeslizadores son un tipo de vehículos marinos que presentan una serie de cualidades atractivas como desafío de control .Su dinámica es compleja y presentan características fuertemente no lineales. Para este tipo de vehículos se analizan dos problemas de control de movimiento: estabilización en un punto y seguimiento de trayectoria. En este trabajo se presenta un problema bechmarck para un aerodeslizador de radio control, indicando las especificaciones para seguimiento de trayectorias y estabilización en un punto. Se ha desarrollado un entorno interactivo de simulación para desarrollo y verificación de diseños. Además se ha desarrollado un controlador para resolver los problemas planteados y se ha verificado su funcionalidad usando la plataforma de simulación.Publicación 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, Sebastián