Commande en formation de véhicules autonomes.

Mohamed MAGHENEM
Soutenance de thèse de doctorat le 5 Juillet 2017, 09h30 à CentraleSupelec (Gif-sur-Yvette) Amphi Mesny

Dans cette thèse, des méthodes dites de Lyapunov sont proposées afin de résoudre des problèmes liés à la coordination distribuée des systèmes multiagent, plus précisément, un groupe de systèmes (agents) non-linéaires formés de robots mobiles non-holonomes est considéré. Pour ce groupe de systèmes, des lois de commande distribuée sont proposées dans le but de résoudre des problèmes de type leader-suiveur en formation et aussi des problèmes de type formation sans-leader par une approche de consensus, sous différentes hypothèses sur le graphe de communication et surtout sur les vitesses du leader. L'originalité de ce travail est dans l'approche proposée pour l'étude de stabilité de la boucle fermée, cette approche consiste à transformer les deux derniers problèmes en des problèmes de stabilisation globale asymptotique d'un ensemble invariant. L’analyse de stabilité est basée sur la construction de fonction de Lyapunov et de fonction de Lyapunov-Karasovskii strictes pour des classes de systèmes non-linéaires variant dans le temps présentant des retards bornés et variant dans le temps.

Mots-clés : Lyapunov functions, Mobile robots, Adaptive systems, Excitation permanente.

Composition du jury proposé :

M. Antonio   LORIA

CNRS

Directeur de thèse

Mme Elena   PANTELEY

CNRS

Codirecteur de thèse

M. Frédéric MAZENC

INRIA

Examinateur

M. Dragan NESIC

University of Melbourne

Examinateur

M. Lorenzo MARCONI

University of Bologna

Examinateur

M. Jamal   DAAFOUZ

Université   de Lorraine

Rapporteur

 

Contributions a l'analyse de données multivoie: algorithmes et applications

Olga Gisela LECHUGA LOPEZ
Soutenance de thèse de doctorat le 3 Juillet 2017, 14h00 à CentraleSupelec (Gif-sur-Yvette) Amphi Blondel

Des méthodes statistiques telles que l'analyse discriminante, la régression logistique, la régression de Cox, et l'analyse canonique généralisée regularisée sont étendues au contexte des données multivoie, pour lesquelles, chaque individu est décrit par plusieurs instances de la même variable. Les données ont ainsi naturellement une structure tensorielle. Contrairement à leur formulation standard, une contrainte structurelle est imposée. L'intérêt de cette contrainte est double: d'une part elle permet une étude séparée de l'influence des variables et de l'influence des modalités, conduisant ainsi à une interprétation facilité des modèles. D'autre part, elle permet de restreindre le nombre de coefficients à estimer, et ainsi de limiter à la fois la complexité calculatoire et le phénomene de sur-apprentissage. Des stratégies pour gérer les problèmes liés au grande dimension des données sont également discutés. Ces différentes méthodes sont illustrées sur deux jeux de données réelles: (i) des données de spectroscopie et (ii) des données d'imagerie par résonance magnétique multi-modales pour prédire le rétablissement à long terme des patients après traumatisme cranien. Dans ces deux cas les méthodes proposées offrent de bons résultats en comparaison des résultats obtenus avec les approches standards.

Mots-clés :  Analyse de données, multiway, classification


Composition du jury proposé
M. Arthur TENENHAUS     CentraleSupélec   Directeur de thèse
M. Hervé ABDI     University of Texas   Rapporteur
M. Mohamed HANAFI     Université de Nantes   Rapporteur
M. Christophe AMBROISE     Université d'Evry   Examinateur
M. Robert SABATIER     Université de Montpellier   Examinateur
M. Remy BOYER     CentraleSupelec   Invité
M. Laurent LE BRUSQUET     CentraleSupelec   Invité

 

Séminaire d’Automatique du plateau de Saclay : Non-Markovian Quantum Feedback Networks

Séminaire le 30 Juin 2017, 11h00 à INRIA Paris (Salle A115)
John Gough (Institute of Mathematics and Physics, Aberystwyth University)


We will recall the theory of Markovian Quantum feedback Networks, and explain some recent models with non-Markovian behaviour coming from physical requirements.

The concept of a controlled flow of a dynamical system, especially when the controlling process feeds information back about the system, is of central importance in control engineering, and we build on the ideas of by Bouten and van Handel to develop a general theory of quantum feedback. We elucidate the relationship between the controlling processes Z and the measured process Y, and to this end make a distinction between what we call the input picture and the output picture.

The theory is general enough to include a modulating filter which processes the measurement readout Y before returning to the system. This opens up the prospect of applying very general engineering feedback control techniques to open quantum systems in a systematic manner, and we consider a number of specific modulating filter problems.

 

Bio. John E. Gough was born in Drogheda, Ireland, in 1967. He received the B.Sc. and M.Sc. in Mathematical Sciences and the Ph.D. degree in Mathematical Physics from the National University of Ireland, Dublin, in 1987, 1988 and 1992 respectively. He was reader in Mathematical Physics at the Department of Mathematics and Computing, Nottingham-Trent University, up until 2007. He then joined the Institute of Mathematics and Physics at Aberystwyth University as established chair of Mathematics. He has held visiting positions at the University of Rome Tor Vergata, EPFL Lausanne, UC Santa Barbara and the Hong Kong Polytechnic University. His research interests include quantum probability, measurement and control of open quantum dynamical systems, and quantum feedback networks.

Algorithmes de conception de lois de commande prédictives pour les systèmes de production d’énergie

Van Quang Binh NGO
Soutenance de thèse de doctorat le 22 Juin 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Amphi F3-05

Cette thèse vise à élaborer de nouvelles stratégies de commande basées sur la commande prédictive pour le système de génération d'énergie éolienne. La topologie des systèmes de production éolienne basée sur le Générateur Asynchrone à Double Alimentation (GADA) qui convient à des plateformes de génération dans la gamme de puissance de 1.5 à 6 MW est abordée. Du point de vue technologique, le convertisseur à trois niveaux et clampé par le neutre (3L-NPC) est considéré comme une bonne solution pour une puissance élevée en raison de ses avantages: capacité à réduire la distorsion harmonique de la tension de sortie et du courant, et augmentation de la capacité du convertisseur grâce à une tension réduite appliquée à chaque semi-conducteur de puissance.

Une description détaillée de la commande prédictive à ensemble de commande fini (FCS-MPC) avec un horizon de prédiction de deux pas est présentée pour deux boucles de régulation: celle liée au convertisseur connecté au réseau et celle du convertisseur connecté au GADA. Le principe de la commande repose sur l'utilisation d'un modèle de prédiction permettant de prédire le comportement du système pour chaque état de commutation du convertisseur. La minimisation d'une fonction de coût appropriée prédéfinie permet d'obtenir la commutation optimale à appliquer au convertisseur.

La thèse étudie premièrement les problèmes liées à la compensation du temps de calcul de la commande et au choix et aux pondérations de la fonction de coût. Ensuite, le problème de stabilité de la commande FCS-MPC est abordé en considérant une fonction de Lyapunov dans la minimisation de la fonction de cout. Finalement, une étude sur la compensation des effets des temps morts du convertisseur est présentée.

Jury:

M. Gonzalo ABAD BIAIN, Professeur, Université de Mondragon, Rapporteur

M. Islam BOUSSAADA, Enseignant-Chercheur, IPSA, HDR L2S, Examinateur

M. Dimitri LEFEBVRE, Professeur, Université du Havre, Rapporteur

M. Pierre LEFRAN, Maître de conférence , Université Grenoble-Alpes, Examinateur

M. Silviu NICULESCU, Directeur du Laboratoire des Signaux et Systèmes, L2S, Co-encadrant

M. Sorin OLARU, Professeur, Centralesupélec/L2S,  Co-encadrant

M. Ahmed RACHID, Professeur, université de Picardie Jules Vernes, Examinateur

M. Pedro RODRIGUEZ-AYERBE, Professeur, Centralesupélec /L2S, Directeur de thèse

Séminaire d'Automatique du Plateau de Saclay : Quantum reservoir engineering to control light with atoms.

Séminaire le 20 Juin 2017, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Alain Sarlette (QUANTIC Lab, INRIA Paris & SYSTeMS research group, Ghent University)


This talk will give a simple introduction to a quantum stabilization technique called "reservoir engineering", which builds on the dissipation induced on a target system by its interaction with an open auxiliary system. We will introduce the technique, recall some older results obtained in our group and finally present our latest results in which we study the effect on the target system, of entanglement "in time" in the auxiliary system. This is joint work with my postdoc Zibo Miao.

Bio. Alain Sarlette has an engineering degree (applied physics) and a PhD (systems and control theory) from the University of Liège, Belgium. He has been a visiting researcher at Princeton University, Mines Paris-Tech, IIT Bombay among others. He is currently assistant professor at Ghent University (Belgium) and Senior Researcher (CR1) at INRIA Paris in the QUANTIC lab. His research interests include nonlinear and geometric control, coordination algorithms, and mainly algorithms and control for quantum technologies.

Séminaire d'Automatique du plateau de Saclay : Some Mathematical and Numerical questions on the Lindblad equation. Application to Quantum Control.

Séminaire le 20 Juin 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Claude Le Bris (Ecole des Ponts & Inria)


We overview a series of joint works with P. Rouchon (Mines de Paris) and other collaborators devoted to the mathematical analysis and the numerical simulation of high-dimensional Lindblad equations. These equations rule the time evolution of density matrices of open quantum systems. The numerical techniques we present aim
at adaptively constructing a low-rank approximation of the density matrices, deriving an evolution equation for this reduced model, and using it as a surrogate model for the original evolution. Alternately, using that reduced model, we also consider and improve advanced Monte-Carlo type techniques that simulate the stochastic system of equations equivalent to the Lindblad equation. The practically relevant setting where we test our approaches arises in stabilization/control problems for quantum optics and circuits. We believe that, interestingly, our approaches may be readily adapted to problems involving the simulation and control of the evolution of density matrices in other contexts.

Bio. Claude Le Bris is a civil engineer in chief, HdR from University Paris Dauphine. His applied mathematics works have primarily been devoted to the design and analysis of numerical approaches for Physics and Mechanics. He holds a research position at Ecole des Ponts et Chaussées. He is the scientific leader of the project-team  MATHERIALS at INRIA, the activity of which is focused on multiscale numerical simulation.

S³ seminar : Recursive State Estimation for Nonlinear Stochastic Systems and Application to a Continuous Glucose Monitoring System

Séminaire le 9 Juin 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Alexandros Charalampidis (CentraleSupélec, Rennes)


The talk will start with an introduction to recursive state estimation. It will be presented how the problem can be solved exactly in two important cases (systems with finite state space and linear Gaussian systems). The difficulties associated with nonlinear systems will be explained and the main techniques will be presented (Extended Kalman Filter, Unscented Kalman Filter, Gauss-Hermite Kalman Filter, Particle Filtering, Gaussian Sums). Then the talk will focus on systems that consist of linear dynamical systems interconnected through static nonlinear characteristics. It will be explained that for them, it is possible to avoid integration on the space space, which may be of high order, reducing it to the solution of some linear systems and low-order integration. This way, more accurate calculations can be made. Additionally, a novel quadrature technique, alternative to the Gauss-Hermite quadrature, specially designed for nonlinear filters using norm minimization concepts will be presented. The proposed techniques are applied to an example and it is shown that they can lead to a significant improvement. The final part of the talk will deal with the application of filters to data from a Continuous Glucose Monitoring System (CGMS). The importance of the CGMS to the construction of an artificial pancreas will be explained. It will be shown that, using simple models of the system dynamics, the application of Kalman and Particle Filtering to experimental data from ICU patients leads to an important reduction of the glucose estimation error.

S³ seminar : Inversion de données en traitement du signal et des images : régularisation parcimonieuse et algorithmes de minimisation L0.

Séminaire le 23 Mai 2017, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Charles SOUSSEN, (Centre de Recherche en Automatique de Nancy (CRAN, UMR CNRS 7039), Université de Lorraine)


Dans la première partie de l'exposé, je présenterai différents problèmes inverses auxquels je me suis intéressé ces dernières années et les contextes applicatifs associés : reconstruction d'images en tomographie, analyse d'images biologiques et d'images hyperspectrales en microscopie, problèmes d'inversion de données en spectroscopie optique avec applications biomédicales. Lorsque les données disponibles sont en nombre limité et partiellement informatives sur la quantité à estimer (problèmes inverses mal posés), la prise en compte d’informations a priori sur les inconnues est indispensable, et s’effectue par le biais des techniques de régularisation. Dans la seconde partie de l'exposé, je présenterai plus particulièrement la régularisation parcimonieuse de problèmes inverses, basée sur la minimisation de la "norme" l0. Les algorithmes heuristiques proposés sont conçus pour minimiser des critères mixtes L2-L0 du type

min_x J(x;lambda) = || y - Ax ||_2^2 + lambda || x ||_0.

Ce problème d'optimisation est connu pour être fortement non-convexe et NP-difficile. Les heuristiques proposées (appelées algorithmes "gloutons") sont définies en tant qu'extensions d'Orthogonal Least Squares (OLS). Leur développement est motivé par le très bon comportement empirique d'OLS et de ses versions dérivées lorsque la matrice A est mal conditionnée. Je présenterai deux types d'algorithmes pour minimiser J(x;lambda) à lambda fixé et pour un continuum de valeurs de lambda. Finalement, je présenterai quelques résultats théoriques visant à garantir que les algorithmes gloutons permettent de reconstruire exactement le support d'une représentation parcimonieuse y = Ax*, c'est-à-dire le support du vecteur x*.

Biographie : Charles Soussen est né en France en 1972. Il est diplômé de l'Ecole Nationale Supérieure en Informatique et Mathématiques Appliquées, Grenoble (ENSIMAG) en 1996. Il a obtenu sa thèse en traitement du signal et des images au Laboratoire des Signaux et Systèmes (L2S), Université de Paris-Sud, Orsay, en 2000, et son Habilitation à Diriger des Recherches à l'Université de Lorraine en 2013. Il est actuellement Maître de Conférences à l'Université de Lorraine, et au Centre de Recherche en Automatique de Nancy depuis 2005. Ses thématiques de recherche concernent les problèmes inverses et l'approximation parcimonieuse.

Traffic-Aware Scheduling and Feedback Reporting in Wireless Networks

Matha DEGHEL
Soutenance de thèse de doctorat le 22 Mai 2017, 09h00 à CentraleSupelec (Gif-sur-Yvette) Amphi Mesny

Demand of wireless communication systems for high throughputs continues to increase, and there are no signs this trend is slowing down. Three of the most prominent techniques that have emerged to meet such demands are OFDMA, cooperative relaying and MIMO. To fully utilize the capabilities of systems applying such techniques, it is essential to develop efficient scheduling algorithms and, more generally, efficient resource allocation algorithms. Classical studies on this subject investigate in much detail settings where the data requests of the users are not taken into consideration or where the perfect and full CSI is assumed to be available for the scheduling mechanism. In practice, however, different limitations may result in not having perfect or full CSI knowledge, such as limited feedback resources, probing cost and delay in the feedback process. Accordingly, in this thesis we examine the problems of scheduling and feedback allocations under realistic considerations concerning the CSI knowledge. Analysis is performed at the packet level and considers the queueing dynamics in the systems with arbitrary arrival processes, where the main performance metric we adopt is the stability of the queues. The first part of the thesis considers a multipoint to multipoint MIMO system with TDD mode under limited backhaul capacity and taking into account the feedback probing cost. Regarding the interference management technique, we apply interference alignment (IA) if more than one pair are active and SVD if only one pair is active. The second part of the thesis considers a multiuser multichannel OFDMA-like system where delayed and limited feedback is accounted for. Two scenarios are investigated, namely the system without relaying and the system with relaying. For the latter one, an additional imperfection we account for is that the users have incomplete knowledge of the fading coefficients between the base-station and the relay.

Jury:

M. Vincent K. N. LAU  Hong Kong       University of Science and Technology  Rapporteur

M. Jean-Marie GORCE                        NSA Lyon                                             Rapporteur

M. Anthony EPHREMIDES                  University of Maryland, College Park   Examinateur

M. Jianwei  HUANG Chinese               University of Hong Kong                      Examinateur

M. Michel  KIEFFER                             Université Paris-Sud                           Examinateur

Mme Laura  COTTATELLUCCI            Eurecom                                              Examinateur

M. Mérouane DEBBAH                        CentraleSupélec                                 Directeur de thèse

M. Mohamad ASSAAD                        CentraleSupélec                                 CoDirecteur de thèse

S³ seminar : Deux trous noirs dans une meule de foin : analyse de données pour l'astronomie gravitationnelle

Séminaire le 19 Mai 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Eric Chassande-Mottin, (CNRS, AstroParticule et Cosmologie, Université Paris Diderot)


Le 14 septembre 2015, les deux détecteurs du Laser Interferometer Gravitational-wave Observatory (LIGO) inauguraient une nouvelle ère pour l'astrophysique en observant pour la première fois une onde gravitationnelle issue de la fusion de deux trous noirs faisant chacun trente fois la masse du soleil environ et situés à une distance supérieure à un milliard d'années-lumière. On donnera une vue d'ensemble de cette découverte majeure en insistant sur les méthodes d'analyse de données utilisées pour sortir le signal du bruit complexe rencontré dans ces expériences.

Coded Caching in Wireless Networks

Séminaire le 19 Mai 2017, 09h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Meixia Tao


The global mobile data traffic has been shifting from voice and messages to rich content distributions, such as video streaming and application downloads. These contents are typically produced ahead of transmission and can be requested by multiple users though at possibly different times. By prefetching popular contents during off-peak times at the edge of wireless networks, such as small base stations, helper nodes, and user devices, wireless caching can alleviate peak-time network congestion and reduce user access latency. A fundamental question is what and how much gain can be leveraged by caching. In this talk, we shall investigate the gain of caching in two types of wireless networks. One is a general wireless interference network with arbitrary number of transmitters and arbitrary number of receives and with caches equipped at all the nodes. An information-theoretic study in terms of the storage-latency tradeoff will be presented. The other is a large-scale small-cell network where each small base station is equipped with a cache. We apply stochastic geometry to model, analyze, and optimize coded caching with performances characterized by average fractional offloaded traffic and average ergodic rate. Our study reveals several design insights of caching in practical wireless networks.

Bio: Meixia Tao received the B.S. degree from Fudan University, Shanghai, China, in 1999, and the Ph.D. degree from Hong Kong University of Science and Technology in 2003. She is currently a Professor with the Department of Electronic Engineering, Shanghai Jiao Tong University, China. Prior to that, she was a Member of Professional Staff at Hong Kong Applied Science and Technology Research Institute during 2003-2004, and a Teaching Fellow then an Assistant Professor at the Department of Electrical and Computer Engineering, National University of Singapore from 2004 to 2007. Her current research interests include content-centric wireless networks, wireless caching and multicasting, resource allocation, and interference coordination.

Dr. Tao is currently serving as a member of the Executive Editorial Committee of the IEEE Transactions on Wireless Communications and an Editor for the IEEE Transactions on Communications. Dr. Tao is the recipient of the IEEE Heinrich Hertz Award for Best Communications Letters in 2013 and the IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award in 2009. She also receives the best paper awards from IEEE/CIC ICCC 2015 and IEEE WCSP 2012.

Semantically-Secured Message-Key Trade-off over Wiretap Channels with Random Parameters

Séminaire le 4 Mai 2017, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Alexander Bunin, Faculty of Electrical Engineering at the Technion-Israel Institute of Technology, Israel.


Modern communication systems usually present an architectural separation between error correction and data encryption. The former is typically realized at the physical layer by transforming the noisy communication channel into a reliable "bit pipe". The data encryption is implemented on top of that by applying cryptographic principles.

Physical layer security (PLS) rooted in information-theoretic principles, is an alternative approach to provably secure communication. This approach dates back to Wyner's celebrated 1975 paper on the wiretap channel (WTC). By harnessing randomness from the noisy communication channel and combining it with proper physical layer coding, PLS guarantees protection against computationally-unlimited eavesdroppers with no requirement that the legitimate parties share a secret key (SK) in advance. The eavesdroppers computational abilities are of no consequence here since the signal he/she observes from the channel carries only negligible information about the secret data.

Two fundamental questions in PLS are those of the best achievable transmission rate of a secret message (SM) over a noisy channel, and the highest attainable SK rate that distributed parties can agree upon. Our work studies the trade-off between SM and SK rates simultaneously achievable over a state-dependent wiretap channel WTC with non-causal channel state information (CSI) at the encoder. This model subsumes all other instances of CSI availability as special cases, and calls for an efficient utilization of the state sequence both for reliability and security purposes. We derive an inner bound on the SM-SK capacity region based on a novel superposition coding scheme. Our inner bound improves upon the previously best known SM-SK trade-off result by Prabhakaran et al., and to the best of our knowledge, upon all other existing lower bounds for either SM or SK for this setup. The results are derived under the strict semantic-security metric that requires negligible information leakage for all message-key distributions. The achievability proof uses the strong soft-covering lemma for superposition codes.
The talk is based on joint work with: Z. Goldfeld and H. H. Permuter (Ben-Gurion University of the Negev, Israel), S. Shamai (Technion - Israel Institute of Technology), P. W. Cuff (Princeton University) and P. Piantanida (CentralSupelec).
The work of A. Bunin and S. Shamai has been supported by the European Union's Horizon 2020 Research And Innovation Programme, grant agreement no. 694630.

Séminaire d’Automatique du plateau de Saclay : Chance-constrained optimization with tight confidence bounds.

Séminaire le 25 Avril 2017, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Mark Cannon (Department of Engineering Science, University of Oxford)


Optimization problems involving chance constraints, i.e. constraints on decision variables that are required to hold with given probability, occur in numerous engineering contexts, but have in particular contributed to developments in robust control design over the past decade. This talk will provide a new perspective on randomized methods for solving chance-constrained programming problems based on samples of uncertain parameters, and presents a theoretical framework for sampled convex programming that encompasses analyses of constraint discarding approaches and sequential sampling approaches. We show that tight bounds on the confidence of the solution of a sampled problem meeting chance constraints apply if a randomized sample discarding strategy is employed. This suggests a solution methodology which is both computationally convenient, being based on the solutions of convex sampled optimization problems, and efficient, requiring the solution of smaller numbers of problems than existing constraint discarding and sequential methods. We illustrate the method with examples from stochastic model predictive control design.

Bio. Mark Cannon obtained the degrees of MEng in Engineering Science in 1993 and D.Phil. in Control Engineering in 1998, both from Oxford University, and SM in Mechanical Engineering in 1995 from Massachusetts Institute of Technology. He is currently Associate Professor of Engineering Science, Oxford University, and an Official Fellow of St John's College. His research interests are in robust constrained control and stochastic model predictive control, specifically: issues relating to optimization and controller design, closed loop stability and constraint satisfaction, and applications to power management in electric vehicles.

Séminaire d’Automatique du plateau de Saclay : On generalized homogeneity and time-constrained stabilization of evolution systems.

Séminaire le 25 Avril 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Andrey polyakov (NON-A team, Inria-Lille-Nord Europe)


Homogeneity is a symmetry of an object (e.g. function or operator) with respect to some transformations (dilations). Nonlinear homogeneous ODEs (ordinary differential equations) form an important class of models of control systems. They appear as local approximations of nonlinear plant and include models of process control, nonholonomic mechanical systems, models with frictions, etc. Being non-linear the homogeneous systems demonstrate properties typical for linear systems, for example, local stability implies the global one, stable homogeneous control system is ISS (input-to-state stable) with respect to measurement noises and additive exogenous disturbance, etc.

This talk is devoted to extension of ideas of homogeneity to evolution systems in Banach/Hilbert spaces. A lot of well-known partial differential equations are homogeneous in a generalized sense, (e.g. heat, wave, Navier-Stocks, Saint-Venant, Korteweg-de Vries, fast diffusion equations). They inherit many important properties of homogeneous ODEs such as  scalability of trajectories or finite-time stability in the case of negative homogeneity degree. Homogeneity allows us to design a universal control for finite-time stabilization of evolution system.

Bio. Andrey Polyakov received PhD degree from Voronezh State University (Russia) in 2005.
He was lecturer (2004-2007) and associate professor (2008-2010) of this university.
In 2007 and 2008 he was a post-doctoral research associate with Automatic Control Department of CINVESTAV (Mexico). From 2010 till 2013 he was researcher with Institute of Control Sciences of Russian Academy of Sciences. Now Andrey Polyakovis Inria researcher with NON-A team of Inria Lille Nord Europe (France). His research interests include
different problems of robust nonlinear control and estimation. He is co-author of the book "Attractive Ellipsoids in Robust Control". He is editor of International Journal of Robust and Nonlinear Control, Journal of Optimization Theory and Applications (JOTA), Automation and Remote Control.

S³ seminar : Extending Stationarity to Graph Signal Processing: a Model for Stochastic Graph Signals

Séminaire le 31 Mars 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Benjamin Girault, (University of Southern California)


During the past few years, graph signal processing has been extending the field of signal processing on Euclidean spaces to irregular spaces represented by graphs. We have seen successes ranging from the Fourier transform, to wavelets, vertex-frequency (time-frequency) decomposition, sampling theory, uncertainty principle, or convolutive filtering. One missing ingredient though are the tools to study stochastic graph signals for which the randomness introduces its own difficulties. Classical signal processing has introduced a very simple yet very rich class of stochastic signals that is at the core of the study of stochastic signals: the stationary signals. These are the signals statistically invariant through a shift of the origin of time. In this talk, we study two extensions of stationarity to graph signals, one that stems from a new translation operator for graph signals, and another one with a more sensible interpretation on the graph. In the course, we show that attempts of alternate definitions of stationarity on graphs in the recent literature are actually equivalent to our first definition. Finally, we look at a real weather dataset and show empirical evidence of stationarity.

Bio: Benjamin Girault received his License (B.Sc.) and his Master (M.Sc.) in France from École Normale Supérieure de Cachan, France, in 2009 and 2012 respectively in the field of theoretical computer science. He then received his PhD in computer science from École Normale Supérieure de Lyon, France, in December 2015. His dissertation entitled "Signal Processing on Graphs - Contributions to an Emerging Field" focused on extending the classical definition of stationary temporal signals to stationary graph signal. Currently, he is a postdoctoral scholar with Antonio Ortega and Shri Narayanan at the University of Southern California continuing his work on graph signal processing with a focus on applying these tools to understanding human behavior.

S³ seminar : Novel Algorithms for Automated Diagnosis of Neurological and Psychiatric Disorders

Séminaire le 28 Mars 2017, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Hojjat ADELI, (The Ohio State University, Columbus, USA)


Novel algorithms are presented for data mining of time-series data and automated electroencephalogram (EEG)-based diagnosis of neurological and psychiatric disorders based on adroit integration of three different computing technologies and problem solving paradigms: neural networks, wavelets, and the chaos theory. Examples of the research performed by the author and his associates for automated diagnosis of epilepsy, the Alzheimer’s Disease, Attention Deficit Hyperactivity Disorder (ADHD), autism spectrum disorder (ASD), and Parkinson’s disease (PD) are reviewed.

Biography: Hojjat Adeli received his Ph.D. from Stanford University in 1976 at the age of 26. He is Professor of Civil, Environmental, and Geodetic Engineering, and by courtesy Professor of Biomedical Informatics, Biomedical Engineering, Neuroscience, and Neurology at The Ohio State University. He has authored over 550 publications including 15 books. He is the Founder and Editor-in-Chief of international research journals Computer-Aided Civil and Infrastructure, now in 32nd year of publication, and Integrated Computer-Aided Engineering, now in 25th year of publication, and the Editor-in-Chief of International Journal of Neural Systems. In 1998 he received the Distinguished Scholar Award from OSU, “in recognition of extraordinary accomplishment in research and scholarship”. In 2005, he was elected Distinguished Member, ASCE: "for wide-ranging, exceptional, and pioneering contributions to computing in civil engineering and extraordinary leadership in advancing the use of computing and information technologies in many engineering disciplines throughout the world.” In 2010 he was profiled as an Engineering Legend in the ASCE journal of Leadership and Management in Engineering, and Wiley established the Hojjat Adeli Award for Innovation in Computing. In 2011 World Scientific established the Hojjat Adeli Award for Outstanding Contributions in Neural Systems. He is a Fellow of IEEE, the American Association for the Advancement of Science, American Neurological Society, and American Institute for Medical and Biomedical Engineering. Among his numerous awards and honors are a special medal from Polish Neural Network Society, the Eduardo Renato Caianiello Award for Excellence in Scientific Research from the Italian Society of Neural Networks, the Omar Khayyam Research Excellence Award from Scientia Iranica, an Honorary Doctorate from Vilnius Gediminas Technical University, and corresponding member of the Spanish Royal Engineering Society.

S³ seminar : Stochastic proximal algorithms with applications to online image recovery

Séminaire le 24 Mars 2017, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Jean-Christophe PESQUET, CVN, CentraleSupélec


Stochastic approximation techniques have been used in various contexts in machine learning and adaptive filtering. We investigate the asymptotic behavior of a stochastic version of the forward-backward splitting algorithm for finding a zero of the sum of a maximally monotone set-valued operator and a cocoercive operator in a Hilbert space. In our general setting, stochastic approximations of the cocoercive operator and perturbations in the evaluation of the resolvents of the set-valued operator are possible. In addition, relaxations and not necessarily vanishing proximal parameters are allowed. Weak almost sure convergence properties of the iterates are established under mild conditions on the underlying stochastic processes. Leveraging on these results, we propose a stochastic version of a popular primal-dual proximal optimization algorithm, and establish its convergence. We finally show the interest of these results in an online image restoration problem.

Séminaire d'Automatique du plateau de Saclay : Controllability of a bent 3-link magnetic microswimmer

Séminaire le 23 Mars 2017, 11h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Pierre Lissy (CEREMADE, Universite Paris-Dauphine)


A recent promising technique for moving a robotic micro-swimmer (in view notably of medical applications) is to apply an external magnetic field. In this talk, I will focus on a 3-link magnetic microswimmer, which consists of three rigid magnetized segments connected by two torsional springs, one of the springs being twisted, so that the swimmer is not aligned at rest. By acting on it with
an external magnetic field, the swimmer twists and moves through the surrounding fluid. After explaining some specific difficulties coming from the Low Reynolds number regime, I will explain how to model the problem thanks to a system of non-linear ODEs. By considering the external magnetic field as a control function, I will state a local partial controllability result around the equilibrium states. Then, I will propose a constructive method to find a magnetic field that allows the swimmer to move along a prescribed trajectory (tracking) in view of obtaining global partial controllability results. Finally, I will show some numerical simulations that illustrate the practical difficulties of the tracking method due to the straight positions of the swimmer. This is a joint work with Laetitia Giraldi (INRIA Sophia), Jean-Baptiste Pomet (INRIA Sophia) and Clément Moreau (ENS Cachan).

Bio: Pierre Lissy received his Ph.D degree in Applied Mathematics in 2013 under the direction of Professor Jean-Michel Coron at Université Pierre et Marie Curie. He is now Assistant Professor in Applied Mathematics at University Paris-Dauphine since 2014. His research interests include the controllability properties of partial differential equations (PDEs), with a focus on the controllability of (linear and non-linear) coupled systems of PDEs and the estimations of the cost of the control near the minimal time of control and in singular limits. He began recently to work on the controllability properties of magnetized micro-swimmers governed by non-linear ODEs.

Séminaire d'Automatique du plateau de Saclay : Time-extremal trajectories of generic control-affine systems have at most finite-order Fuller singularities

Séminaire le 23 Mars 2017, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Francesco Boarotto (CMAP, Ecole Polytechnique)


Let $M$ be a smooth connected $n$-dimensional manifold, and consider on it the control-affine system $\dot{q}=f_0(q)+uf_1(q),\quad u\in[-1,1].$ Time-extremal trajectories for the time-optimal control problem associated to this system are driven by controls $u$, whose set $\Sigma$ of discontinuities is possibly stratified as follows: $\Sigma_0$ is the set of isolated points in $\Sigma$ (switching times) and, recursively, the $k$-th order Fuller times $\Sigma_k$ are found as the isolated points of $\Sigma\setminus\left(\bigcup_{j=0}^{k-1}\Sigma_j\right)$.

In this talk we show that, in fact, for the generic choice of the pair $(f_0,f_1),$ there exists an integer $N>0$ such that the control $u$ associated to any time-extremal trajectory admits at most Fuller times of order $N$. In particular, $u$ is smooth out of a set of measure zero. This is a joint work with M. Sigalotti (CMAP, Ecole Polytechnique).

Bio: Francesco Boarotto was born in Verona, Italie, in 1988. He received the Master's degree in mathematics from the University of Padou, Italie, in 2012 and the Ph.D degree from SISSA, Trieste, Italie, in 2016. Since then he has been post-doc in CMAP - Ecole Polytechnique. His research interests include geometric control theory and sub-Riemannian geometry.

 

S³ seminar : On Electromagnetic Modeling and Imaging of Defects in Periodic Fibered Laminates

Séminaire le 10 Mars 2017, 12h30 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Zicheng LIU, (Inverse problems Group, Signals and Statistics Division, L2S Laboratory)


Composite laminates are commonly utilized in industry due to advantages as high stiffness, light weight, versatility, etc. Multiple layers, each one involving periodically-positioned circular-cylindrical fibers in a given homogeneous matrix, are usually involved. However, defects can affect the structure and thereupon impact security and efficiency, and they call for nondestructive testing. By electromagnetic (EM) means, it requires fast and reliable computational modeling of both sound and damaged laminates if one wishes to better understand pluses and minuses of the testing, and derive efficient imaging algorithms for the end user. Both direct modeling and inverse imaging will be introduced in this presentation.  For the former, since the periodicity of the structure is destroyed due to defects, methods based on the Floquet theorem are inapplicable. Two modeling approaches are then utilized: one is with supercell methodology where a fictitious periodic structure is fabricated, so as the EM field solution everywhere in space can be well approximately modeled, provided the supercell be large enough; the other is based on fictitious source superposition (FSS) where defects are treated as equivalent sources and the field solution is a summation of responses to the exterior source and equivalent ones. For imaging, with MUSIC and sparsity-based algorithm, missing fibers could be accurately located.

Biography: Zicheng LIU was born in Puyang, China, in October 1988. He received the M.S. degree in circuit and system from Xidian University, Xi’an, China in March 2014 and is currently pursuing the Ph.D. degree with the benefit of a Chinese Scholarship Council (CSC) grant at the Laboratoire des Signaux et Systèmes, jointly Centre National de la Recherche Scientifique (CNRS), CentraleSupélec, and Université Paris-Sud, Université Paris-Saclay, Paris, France. He will defend his Université Paris-Saclay Ph.D. early Fall 2017. His present work is on the electromagnetic modeling of damaged periodic fiber-based laminates and corresponding imaging algorithms and inversion. His research interests include computational electromagnetics, scattering theory on periodic structures, non-destructive testing, sparsity theory, and array signal processing.

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