Starspots and spin-orbit alignment for Kepler cool host stars

The angle between the spin axis of the host star and the orbit of its planets (i.e., the stellar obliquity) is precious information about the formation and evolution of exoplanetary systems. Measurements of the Rossiter-McLaughlin effect revealed that many stars that host a hot-Jupiter have high obliquities, suggesting that hot-Jupiter formation involves excitation of orbital inclinations. In this contribution we show how the passage of the planet over starspots can be used to measure the obliquity of exoplanetary systems. This technique is used to obtain - for the first time - the obliquity of a system with several planets that lie in a disk, Kepler-30, with the result that the star has an obliquity smaller than 10 degrees. The implications for the formation of exoplanetary systems, in particular the hot-Jupiter population, are also discussed.Comment: To appear in special edition of AN, proceedings of the Cool Stars 17 conference, Barcelona June 201

Pointwise convergence topology and function spaces in fuzzy analysis

We study the space of all continuous fuzzy-valued functions from a space $X$ into the space of fuzzy numbers (\mathbb{E}\sp{1},d\sb{\infty}) endowed with the pointwise convergence topology. Our results generalize the classical ones for continuous real-valued functions. The field of applications of this approach seems to be large, since the classical case allows many known devices to be fitted to general topology, functional analysis, coding theory, Boolean rings, etc

Transitivity in Fuzzy Hyperspaces

Given a metric space (X, d), we deal with a classical problem in the theory of hyperspaces: how some important dynamical properties (namely, weakly mixing, transitivity and point-transitivity) between a discrete dynamical system f : (X, d) → (X, d) and its natural extension to the hyperspace are related. In this context, we consider the Zadeh’s extension fbof f to F(X), the family of all normal fuzzy sets on X, i.e., the hyperspace F(X) of all upper semicontinuous fuzzy sets on X with compact supports and non-empty levels and we endow F(X) with different metrics: the supremum metric d∞, the Skorokhod metric d0, the sendograph metric dS and the endograph metric dE. Among other things, the following results are presented: (1) If (X, d) is a metric space, then the following conditions are equivalent: (a) (X, f) is weakly mixing, (b) ((F(X), d∞), fb) is transitive, (c) ((F(X), d0), fb) is transitive and (d) ((F(X), dS)), fb) is transitive, (2) if f : (X, d) → (X, d) is a continuous function, then the following hold: (a) if ((F(X), dS), fb) is transitive, then ((F(X), dE), fb) is transitive, (b) if ((F(X), dS), fb) is transitive, then (X, f) is transitive; and (3) if (X, d) be a complete metric space, then the following conditions are equivalent: (a) (X × X, f × f) is point-transitive and (b) ((F(X), d0) is point-transitive

Networked gain-scheduled fault diagnosis under control input dropouts without data delivery acknowledgement

This paper investigates the fault diagnosis problem for discrete‐time networked control systems under dropouts in both control and measurement channel with no delivery acknowledgment. We propose to use a proportional integral observer‐based fault diagnoser collocated with the controller. The observer estimates the faults and computes a residual signal whose comparison with a threshold alarms the fault appearance. We employ the expected value of the arriving control input for the open‐loop estimation and the measurement reception scenario for the correction with a jump observer. The jumping gains are scheduled in real time with rational functions depending on a statistic of the difference between the control command being applied in the plant and the one being used in the observer. We design the observer, the residual, and the threshold to maximize the sensitivity under faults while guaranteeing some minimum detectable faults under a predefined false alarm rate. Exploiting sum‐of‐squares decomposition techniques, the design procedure becomes an optimization problem over polynomials

Jump state estimation with multiple sensors with packet dropping and delaying channels

This work addresses the design of a state observer for systems whose outputs are measured through a communication network. The measurements from each sensor node are assumed to arrive randomly, scarcely and with a time-varying delay. The proposed model of the plant and the network measurement scenarios cover the cases of multiple sensors, out-of-sequence measurements, buffered measurements on a single packet and multirate sensor measurements. A jump observer is proposed that selects a different gain depending on the number of periods elapsed between successfully received measurements and on the available data. A finite set of gains is pre-calculated offline with a tractable optimisation problem, where the complexity of the observer implementation is a design parameter. The computational cost of the observer implementation is much lower than in the Kalman filter, whilst the performance is similar. Several examples illustrate the observer design for different measurement scenarios and observer complexity and show the achievable performance

Inferential networked control with accessibility constraints in both the sensor and actuator channels

The predictor and controller design for an inferential control scheme over a network is addressed. A linear plant with disturbances and measurement noise is assumed to be controlled by a controller that communicates with the sensors and the actuators through a constrained network. An algorithm is proposed such that the scarce available outputs are used to make a prediction of the system evolution with an observer that takes into account the amount of lost data between successful measurements transmissions. The state prediction is then used to calculate the control actions sent to the actuator. The possibility of control action drop due to network constraints is taken into account. This networked control scheme is analyzed and both the predictor and controller designs are addressed taking into account the disturbances, the measurement noise, the scarce availability of output samples and the scarce capability of control actions update. The time-varying sampling periods that result for the process inputs and outputs due to network constraints have been determined as a function of the probability of successful transmission on a specified time with a Bernoulli distribution. For both designs H∞ performance has been established and LMI design techniques have been used to achieve a numerical solution

Performance Tradeoffs for Networked Jump Observer-Based Fault Diagnosis

Print Request Permissions In this paper, we address the fault diagnosis problem for discrete-time multi-sensor systems over communication networks with measurement dropouts. We use the measurement outcomes to model the measurement reception scenarios. Based on this, we propose the use of a jump observer to diagnose multiple faults. We model the faults as slow time-varying signals and introduce this dynamic in the observer to estimate the faults and to generate a residual. The fault detection is assured by comparing the residual signal with a prescribed threshold. We design the jump observer, the residual and the threshold to attain disturbance attenuation, fault tracking and detection conditions and a given false alarm rate. The false alarm rate is upper bounded by means of Markov's inequality. We explore the tradeoffs between the minimum detectable faults, the false alarm rate and the response time to faults of the fault diagnoser. By imposing the disturbances and measurement noises to be Gaussian, we tighten the false alarm rate bound which improves the time needed to detect a fault. A numerical example is provided to illustrate the effectiveness of the theory developed in the paper

Une Approche Multi Spectrale Endogène pour la Séparation de Chromophores en Profondeur

L¿échographie transfontanellaire est lamodalité de référence utilisée aujourd¿hui lors de l¿examen cérébral du prématuré pour le dépistage des hémorragies et le diagnostic des souffrances anoxo-ischémiques. Le diagnostic des lésions de la substance blanche reste difficile du fait du signal hyper-échogène naturel des tissus. L¿imagerie par résonance magnétique (IRM), outre qu¿elle présente l¿inconvénientmajeur d¿obliger le déplacement de l¿enfant, ne permet pas toujours une identification fiable de ces lésions. Dans le cadre demon stage, on propose d¿utiliser la lumière infrarouge pour extraire la variation locale de concentration de chromophores (paramètre d¿absorption lié à la concentration d¿hémoglobine, d¿eau, de lipides, etc.) et la modification des structures de tissus (paramètres de diffusion), susceptibles de caractériser les lésions de substance blanche. Pour cela, une approche en TOD-RT (tomographie optique diffuse résolue en temps) a été mise en place au laboratoire. J¿ai proposé un nouveau protocole d¿acquisition multi-spectrale permettant la décomposition du paramètre optique ¹a en concentration des différentes substances. Pour aboutir à cette décomposition, j¿ai été amené à développer des outils d¿analyse et de quantification des reconstructions. Le nouveau protocole et les outils d¿analyse ont été testés et validés grâce à un fantôme multi-spectral également défini au cours du stage. Ces résultats seront présentés en détail dans ce rapport.Sendra Sanchis, D. (2013). Une Approche Multi Spectrale Endogène pour la Séparation de Chromophores en Profondeur. http://hdl.handle.net/10251/33355.Archivo delegad

Co-design of jump estimators and transmission policies for wireless multi-hop networks with fading channels

We study transmission power budget minimization of battery-powered nodes in a remote state estimation problem over multi-hop wireless networks. Communication links between nodes are subject to fading, thereby generating random dropouts. Relay nodes help to transmit measurements from distributed sensors to an estimator node. Hopping through each relay node introduces a unit delay. Motivated by the need for estimators with low computational and implementation cost, we propose a jump estimator whose modes depend on a Markovian parameter that describes measurement transmission outcomes over a finite interval. It is well known that transmission power helps to increase the reliability of measurement transmissions, at the expense of reducing the life-time of the nodes’ battery. Motivated by this, we derive a tractable iterative procedure, based on semi-definite programming, to design a finite set of filter gains, and associated power control laws to minimize the energy budget while guaranteeing an estimation performance level. This procedure allows us to tradeoff the complexity of the filter implementation with performance and energy use.This work has been funded by projects TEC2015-69155-R from MICINN, PI15734, E-2015-15 and P1⋅1B2015-42 from Universitat Jaume I. The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Hideaki Ishii under the direction of Editor Christos G. Cassandras