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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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2011 - 201927
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Tiene archivos: true × Fecha de inicio: 2010 × Fecha de finalización: 2019 ×

Resultados de la búsqueda

Mostrando 1 - 10 de 27
  • Miniatura
    Publicación
    Fuzzy logic vs analytic controllers on a non-linear system
    (World Scientific, 2014) Aranda Escolástico, Ernesto; Guinaldo Losada, María; Dormido Canto, Sebastián; Santos, Matilde
    In this paper, an intelligent control of the rotary inverted pendulum by fuzzy logic is presented. Specifically, the design consists of a Takagi-Sugeno fuzzy model to approximate the non-linear system to a succession of points where a linear system is described. A feedback gain is obtained that allows the stabilization of the inverted pendulum in a higher attractor than in the case of analytic Full State Feedback controller or Linear Quadratic Regulator.
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    Control of a chain pendulum: A fuzzy logic approach
    (Taylor and Francis Group, 2016-02-12) Aranda Escolástico, Ernesto; Guinaldo Losada, María; Santos, Matilde; Dormido Canto, Sebastián
    In this paper, we present a real application of computational intelligence. Fuzzy control of a non-linear rotary chain pendulum is proposed and implemented on real prototypes. The final aim is to obtain a larger region of attraction for the stabilization of this complex system, that is, a more robust controller. As it is well-known, fuzzy logic exploits the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost when dealing with complex systems. In this case, the control strategy is based on a Takagi-Sugeno fuzzy model of the strongly non-linear multivariable system. Simulation and experimental results on the real plant have been obtained and tested in a rotary inverted pendulum and in a double rotary inverted pendulum. They have been compared to other feedback control strategies such as Full State Feedback or Linear Quadratic Regulator with encouraging results. Fuzzy control allows to enlarge the stability region of control. Indeed, the region of attraction and therefore the stabilization has been enlarged up to over 17% for the real system.
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    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, Sebastián
    In 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.
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    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.
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    An anytime optimal control strategy for multi-rate systems
    (IEEE , 2017-02-20) Aranda Escolástico, Ernesto; Guinaldo Losada, María; Ángel Cuenca; Julián Salt; Dormido Canto, Sebastián; https://orcid.org/0000-0003-4466-2666; https://orcid.org/0000-0002-9640-2658
    In this work, we study a dual-rate system with fast-sampling at the input and propose a design to optimize the consecutive control signals. The objective of the optimization is to maximize the decay rate depending on the available resources to stabilize faster the control system. Stability conditions are enunciated in terms of Linear Matrix Inequalities (LMIs). The control solution is extended to time delays. A numerical example illustrates the benefits of the control proposal.
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    A novel approach for periodic event-triggering based on general quadratic functions
    (IEEE, 2015) Aranda Escolástico, Ernesto; Guinaldo Losada, María; Dormido Canto, Sebastián
    This paper is concerned with periodic event-triggered control, which avoids the continuous monitoring of the state of the system while reducing the number of control updates. A new form of quadratic event-triggering condition is proposed to enlarge the inter-event times. The asymptotic stability criteria is analyzed by means of Lyapunov-Krasovskii functionals and the stability condition is expressed in terms of linear matrix inequalities. Simulation and experimental results are given to show the effectiveness of the proposed method.
  • Miniatura
    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, Sebastián
    This 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.
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    Stability of output event-based control systems through quadratic trigger functions
    (IEEE, 2015-10) Aranda Escolástico, Ernesto; Guinaldo Losada, María; Dormido Canto, Sebastián
    The design of event-based controllers for systems with unknown states is investigated in this paper. The case of general quadratic triggering conditions that depend on the estimated state given by a Luenberger observer is studied. Novel frameworks are proposed for continuous and periodic event-based control providing criteria for asymptotic stability with the form of Linear Matrix Inequalities (LMIs). The frameworks are tested in simulation through a challenging system, such as the double rotary inverted pendulum.
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    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, Sebastián
    Detecting 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.
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    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, Sebastián
    Disruptions 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.