Novel Microstereolithography (MSL) and Bulk Lithography (BL) technologies for polymer/ceramic 3D MEMS

Séminaire le 3 Juin 2015, 16h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Prof. Prasanna S. Gandhi


Polymers are increasingly being used for fabrication of MEMS for their advantages of low cost, easy disposability, high flexibility, and so on. With the area of printable organic electronics developing fast there are enormous possibilities with polymer MEMS, especially 3D. This talk will present two indigenously developed technologies for fabrication of polymer 3D MEMS.
The proposed MSL technology has demonstrated resolution of 6micron and a large overall size of fabricated component at the same time: a feature seldom found in other such systems in the literature. The core opto-mechanical scanner (patent pending) and mechatronic system built around it would be presented. This system is demonstrated to have positioning accuracy within 100 nm. Several cases of micro-component fabrication will be demonstrated. Main drawback of MSL is stair-stepping effects on slanted walls. To overcome this limitation, recently "Bulk Lithography" technology has been proposed by our group. The main principle used here is to impose spatial variation of laser energy dose while scanning. The method gives remarkable accuracy in getting free-form surface features desired for microlenses, tapered micro cantilevers, tapered diaphragm micromirrors and so on, which are otherwise not feasible to fabricate. Finally, ceramic microstereolithography and preliminary fabrication of ceramic microcomponents would be demonstrated. The proposed technologies hold potential for direct prototyping and also mass production of MEMS devices along with packaging.

Biography: P.S. Gandhi received the B.Eng. degree in from the University of Bombay, Mumbai in 1994 and the M.Tech degree from the Indian Institute of Technology, Bombay, Mumbai in 1996, both in mechanical engineering. He received the Ph.D. degree in mechanical engineering from the Rice University, Houston in 2001. Since 2001, he has been faculty member, currently Professor, in the Department of Mechanical Engineering at Indian Institute of Technology, Bombay, Mumbai. His research interests are in the areas of MEMS and Microsystems, Mechatronics, and Nonlinear Dynamical Systems and Control. He has been a recipient of 2006 BOYSCAST fellowship of Govt of India, 2007 Best faculty award (ME department) and Prof J.R.Issac fellowship. He has authored several patents and over 85 peer reviewed conference and journal papers. He has coordinated setup of a new laboratory Suman Mashruwala Microengineering Laboratory for research in Microdomain and has successfully developed technologies of Bulk Lithography and Microstereolithography for 3D MEMS fabrication in this laboratory. He has been a qualified teacher of stress relieving, life enhancing techniques of Art of Living foundation by Sri Sri Ravishankar

Hors série Revue Parlementaire: Enseignement Supérieur, Recherche et Innovation

Date: 
Tue, 04/21/2015 -
11:30 to 12:30

Dans le cadre de la publication d'un hors série spécial Ile de France, sur un thème unique : Enseignement Supérieur, Recherche et Innovation, par la Revue Parlementaire, mensuel existant depuis 1905 ( site web : larevueparlementaire.fr), le L2S a été sélectionné parmi 20 laboratoires et instituts de recherche pour  communiquer sous forme de publi-rédactionnel.
Ce hors série dresse un panorama des potentiels existants sur l'Ile de France et évoque les contours des multiples projets structurants déjà validés ou ceux en devenir.

Recrutement: Poste d'expert en calcul scientifique

Date: 
Mon, 04/20/2015 - 17:30

Le poste "Expert en calcul scientifique - IR - BAP E" est proposé, dans le cadre de la campagne de mobilité interne NOEMI qui se déroulera du 24 avril 2015 au 27 mai 2015.
N° Y61002 - Chef de projet ou expert en calcul scientifique - IR - BAP E"

 

MIMO Radar Processing Methods for Anticipating and Compensating Real World Imperfections.

Mathieu CATTENOZ
Soutenance de thèse de doctorat le 27 Mai 2015, 10h00 à CentraleSupelec (Gif-sur-Yvette) Amphi Ampère

Le concept du radar MIMO est prometteur en raison des nombreux avantages qu'il apporte par rapport aux architectures radars actuelles : flexibilité pour la formation de faisceau à l'émission --- large illumination de la scène et résolution fine après traitement --- et allègement de la complexité des systèmes, via la réduction du nombre d'antennes et la possibilité de transférer des fonctions de contrôle et d'étalonnage du système dans le domaine numérique. Cependant, le radar MIMO reste au stade du concept théorique, avec une prise en compte insuffisante des impacts du manque d'orthogonalité des formes d'onde et des défauts matériels.

Ce travail de thèse, dans son ambition de contribuer à ouvrir la voie vers le radar MIMO opérationnel, consiste à anticiper et compenser les défauts du monde réel par des traitements numériques. La première partie traite de l'élaboration des formes d'onde MIMO. Nous montrons que les codes de phase sont optimaux en termes de résolution spatiale. Nous présentons également leurs limites en termes d'apparition de lobes secondaires en sortie de filtre adapté. La seconde partie consiste à accepter les défauts intrinsèques des formes d'onde et proposer des traitements adaptés au modèle de signal permettant d'éliminer les lobes secondaires résiduels induits. Nous développons une extension de l'Orthogonal Matching Pursuit (OMP) qui satisfait les conditions opérationnelles, notamment par sa robustesse aux erreurs de localisation, sa faible complexité calculatoire et la non nécessité de données d'apprentissage. La troisième partie traite de la robustesse des traitements vis-à-vis des écarts au modèle de signal, et particulièrement la prévention et l'anticipation de ces phénomènes afin d'éviter des dégradations de performance. En particulier, nous proposons une méthode numérique d'étalonnage des phases des émetteurs. La dernière partie consiste à mener des expérimentations en conditions réelles avec la plateforme radar MIMO Hycam. Nous montrons que certaines distorsions subies non anticipées, même limitées en sortie de filtre adapté, peuvent impacter fortement les performances en détection des traitements dépendant du modèle de signal.

Mots-clefs : radar MIMO, forme d'onde MIMO, réduction des lobes secondaires, traitement dépendant du modèle de signal, OMP, IAA, écart au modèle, expérimentation MIMO.

Plus d’infos : www.cattenoz.wordpress.com

Composition du jury

Philippe FORSTER     Professeur (Univ. Paris-Ouest et SATIE, ENS Cachan)  (Rapporteur)
Xavier NEYT  Professeur (Ecole royale militaire, Bruxelles)  (Rapporteur)
François LE CHEVALIER  Professeur (Université de Delf et Thales)  (Examinateur)
Josef WORMS  Mathématicien (FHR, Fraunhofer-Gesellschaft) (Examinateur)
Pascal CHEVALIER  Professeur et expert (CNAM et THALES-Communications-Security)  (Examinateur)
Sylvie MARCOS  Directrice de thèse, directrice de recherche (L2S-CNRS-CentraleSupélec-UPSUD)  (Examinateur)
Laurent SAVY  Encadrant de thèse, ingénieur (ONERA) (Examinateur)
Chin Yuan CHONG Chercheuse (DSO, Singapour)  (Invité)
Erwan COMTE  Responsable ingénierie radar (Direction générale de l'armement)  (Invité)
Philippe BROUARD  Encadrant de thèse, ingénieur (ONERA)  (Invité)
Laurent CONSTANCIAS  Encadrant de thèse, ingénieur (ONERA) (Invité)

S³: The appliction of medium grazing angle sea-clutter models -- The NRL multi-aperture SAR: system description and recent results

Séminaire le 26 Mai 2015, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Dr. Luke Rosenberg - DSTO, Australia


Details are given in the attached file. Access information are available on the website http://www.lss.supelec.fr/scube/

Seminaire_s3-sondra-icode May 26th

Commande prédictive hiérarchisée. Application à la commande de fours de réchauffage sidérurgiques

Xuan Manh NGUYEN
Soutenance de thèse de doctorat le 18 Mai 2015, 14h00 à CentraleSupelec (Gif-sur-Yvette) Amphi F3-05

Dans l'industrie sidérurgique, les fours de réchauffage sont les plus grands consommateurs d'énergie après les hauts fourneaux. En conséquence, la réduction de leur consommation énergétique s’avère être la préoccupation majeure dans le contexte de la commande des fours. Dans un four de réchauffage de brames, des brames d'acier sont chauffées en traversant successivement plusieurs zones de la température ambiante à un profil de température homogène de 1250 °C en sortie du four, avant d’être laminées par la suite dans les laminoirs à chaud. La température des brames est contrôlée principalement par une structure de commande hiérarchisée à deux niveaux (niveau 1 et 2).

L'objectif de ces travaux est d'améliorer la performance du chauffage et en conséquence de réduire la consommation énergétique du four à l'aide d’une stratégie de commande prédictive distribuée et hiérarchisée implantées sur les deux niveaux de commande. Dans un premier temps, une approche de commande prédictive distribuée est développée pour le niveau 1 afin de suivre les consignes de température de chaque zone. L’aspect distribué de la commande permet de prendre en compte les couplages entre les zones tout en induisant une moindre complexité d’implantation par rapport à une approche totalement centralisée. L’implantation industrielle de cette stratégie a permis une amélioration significative de la précision du suivi de température et une réduction de la consommation d'énergie de 3%.

Une deuxième étape propose l’élaboration de la commande prédictive hiérarchisée du niveau 2 afin, à partir de la consigne de température de la brame, de déterminer les consignes de température optimales des zones en se fondant sur un modèle de transfert thermique du four. Les résultats de la simulation obtenus avec cette stratégie comparés aux données industrielles montrent une réduction de la consommation énergétique de 5% et une meilleure qualité de chauffage des brames. L’approche précédente est enfin étendue pour prendre en compte et optimiser le cadencement des brames au sein de la commande prédictive du niveau 2, afin d’augmenter la productivité du four. La simulation montre alors une augmentation potentielle de productivité du four de 15 tonnes par heure tout en améliorant la qualité de chauffage des brames.

 

Composition du Jury :

 

Directeur de thèse :                 Didier DUMUR                                    Professeur, CentraleSupélec

Co-encadrant :                        Fayçal LAWAYEB                               Ingénieur, ArcelorMittal

Co-encadrant :                        Pedro RODRIGUEZ-AYERBE            Professeur Adjoint, CentralSupélec

Rapporteurs :                         Edouard LAROCHE                             Professeur des Universités, Université de Strasbourg

                                               Pierre RIEDINGER                               Professeur des Universités, CRAN Nancy

Examinateurs :                       Estelle COURTIAL                               Maître de Conférences, Université d’Orléans

                                               Mohammed M’SAAD                          Professeur des Universités, GREYC Caen

                                               Dorothée NORMAND-CYROT           Directeur de Recherche CNRS, L2S Gif-sur-Yvette

Commande prédictive hiérarchisée. Application à la commande de fours de réchauffage sidérurgiques

Xuan Manh NGUYEN
Soutenance de thèse de doctorat le 18 Mai 2015, 14h00 à CentraleSupelec (Gif-sur-Yvette) Amphi F3-05

Dans l'industrie sidérurgique, les fours de réchauffage sont les plus grands consommateurs d'énergie après les hauts fourneaux. En conséquence, la réduction de leur consommation énergétique s’avère être la préoccupation majeure dans le contexte de la commande des fours. Dans un four de réchauffage de brames, des brames d'acier sont chauffées en traversant successivement plusieurs zones de la température ambiante à un profil de température homogène de 1250 °C en sortie du four, avant d’être laminées par la suite dans les laminoirs à chaud. La température des brames est contrôlée principalement par une structure de commande hiérarchisée à deux niveaux (niveau 1 et 2).

L'objectif de ces travaux est d'améliorer la performance du chauffage et en conséquence de réduire la consommation énergétique du four à l'aide d’une stratégie de commande prédictive distribuée et hiérarchisée implantées sur les deux niveaux de commande. Dans un premier temps, une approche de commande prédictive distribuée est développée pour le niveau 1 afin de suivre les consignes de température de chaque zone. L’aspect distribué de la commande permet de prendre en compte les couplages entre les zones tout en induisant une moindre complexité d’implantation par rapport à une approche totalement centralisée. L’implantation industrielle de cette stratégie a permis une amélioration significative de la précision du suivi de température et une réduction de la consommation d'énergie de 3%.

Une deuxième étape propose l’élaboration de la commande prédictive hiérarchisée du niveau 2 afin, à partir de la consigne de température de la brame, de déterminer les consignes de température optimales des zones en se fondant sur un modèle de transfert thermique du four. Les résultats de la simulation obtenus avec cette stratégie comparés aux données industrielles montrent une réduction de la consommation énergétique de 5% et une meilleure qualité de chauffage des brames. L’approche précédente est enfin étendue pour prendre en compte et optimiser le cadencement des brames au sein de la commande prédictive du niveau 2, afin d’augmenter la productivité du four. La simulation montre alors une augmentation potentielle de productivité du four de 15 tonnes par heure tout en améliorant la qualité de chauffage des brames.

 

Composition du Jury :

Directeur de thèse :                 Didier DUMUR                                    Professeur, CentraleSupélec

Co-encadrant :                        Fayçal LAWAYEB                               Ingénieur, ArcelorMittal

Co-encadrant :                        Pedro RODRIGUEZ-AYERBE            Professeur Adjoint, CentralSupélec

 

Rapporteurs :                         Edouard LAROCHE                             Professeur des Universités, Université de Strasbourg

                                               Pierre RIEDINGER                               Professeur des Universités, CRAN Nancy

Examinateurs :                       Estelle COURTIAL                               Maître de Conférences, Université d’Orléans

                                               Mohammed M’SAAD                          Professeur des Universités, GREYC Caen

                                               Dorothée NORMAND-CYROT           Directeur de Recherche CNRS, L2S Gif-sur-Yvette

An introduction to neural fields

Séminaire le 12 Mai 2015, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Georgios Detorakis, post-doc L2S


The main objective of the field of Computational Neuroscience is to understand how the brain works through mathematical models (numerical and analytical works). Some of these models are described by neural fields equations. Neural fields are integro-differential equations that describe the spatiotemporal dynamics of the activity of a piece of neocortical tissue. Neural fields equations emerge when one assimilates the high number of neurons of the selected piece of brain tissue in its continuum limit. Neural fields have been studied both analytically and numerically by many researchers. They can model many different and interesting biological phenomena such as attention, working memory, self-organization, or synaptic depression. The seminar consists of two parts. The first part is a brief introduction to neuroscience and the second part is dedicated to neural fields. We will review how neural fields equations can be derived, how the steady-state solution can be computed, and its stability can be insured. Finally, some cognitive models that are based on neural fields will be presented.

Bio:
Georgios Detorakis has studied Applied Mathematics and Neuroscience. He did his PhD on cortical plasticity, self-organization and neural fields. During his PhD, he studied the formation of topographic maps in area 3b of the primary somatosensory cortex and the multimodal problem of “Touch and the body”. He is now a postdoc fellow at L2S working with Antoine Chaillet on Parkinson’s disease in the ANR project "SynchNeuro". He uses delayed neural fields in order to model some brain areas that play a crucial role in Parkinson’s disease motor symptoms.

Stability theory, as told by its developers

Séminaire le 5 Mai 2015, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Antonio Loria, Elena Panteley (L2S)


We present a brief but detailed historical review on the development of stability theory, from its early starts out of the minds of Lagrangia and Dirichlet. The survey carries on to focus on Lyapunov stability. Through exact citations from the works of the developers of stability, including many Soviet texts from the 20th century, we revise the fundamental definitions and theorems; making emphasis on several misfortunate translations which have led to wrong interpretations and ambiguous statements. We favour depth and sacrifice generality: on technical grounds, we focus on the most elementary (yet not so) well-known forms of Lyapunov stability and common but crucial qualifiers that go with it: uniform, asymptotic, global. We revise the origin of the wrongly known invariance principle ...

Approches bayésiennes en tomographie micro-ondes. Application à l'imagerie du cancer du sein

Leila GHARSALLI
Soutenance de thèse de doctorat le 10 Avril 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Amphi F3-05

Ce travail concerne l'imagerie micro-onde en vue d'application à l'imagerie biomédicale.  Cette technique d'imagerie a pour objectif de retrouver la distribution des propriétés diélectriques internes (permittivité diélectrique et conductivité) d'un objet inconnu illuminé par une onde interrogatrice connue à partir des mesures du champ électrique dit diffracté résultant de leur interaction.

Un tel problème constitue un problème dit inverse par opposition au problème direct associé qui consiste à calculer le champ diffracté, l'onde interrogatrice et l'objet étant alors connus.

La résolution du problème inverse nécessite la construction préalable du modèle direct associé. Celui-ci est ici basé sur une représentation intégrale de domaine des champs électriques donnant naissance à deux équations intégrales couplées dont les contreparties discrètes sont obtenues à l'aide de la méthode des moments.

En ce qui concerne le problème inverse, hormis le fait que les équations physiques qui interviennent dans sa modélisation directe le rendent non-linéaire, il est également mathématiquement mal posé au sens de Hadamard, ce qui signifie que les conditions d'existence, d'unicité et de stabilité de la solution ne sont pas simultanément garanties. La résolution d'un tel problème nécessite sa régularisation préalable qui consiste généralement en l'introduction d'information a priori sur la solution recherchée. Cette résolution est effectuée, ici, dans un cadre probabiliste bayésien où l'on introduit une connaissance a priori adaptée à l'objet sous test et qui consiste à considérer ce dernier comme étant composé d'un nombre fini de matériaux homogènes distribués dans des régions compactes. Cet information est introduite par le biais d'un modèle de « Gauss-Markov-Potts ». Le calcul bayésien nous donne la loi a posteriori de toutes les inconnues à partir de laquelle on peut définir les estimateurs ponctuels. On s'attache ensuite à déterminer les estimateurs a posteriori via des méthodes d'approximation variationnelles et à reconstruire ainsi l'image de l'objet recherché.

Les principales contributions de ce travail sont d'ordre méthodologique et algorithmique. Elles sont illustrées par une application de l'imagerie micro-onde à l'imagerie du cancer du sein. Cette dernière constitue en soi un point très important et original de la thèse. En effet, l'imagerie du cancer du sein par la technique micro-onde est une alternative très intéressante à la mammographie par rayons X, mais n'en est encore qu'à un stade exploratoire.

Membres du jury:

Directeur de thèse   Mr Duchêne Bernard  Chargé de recherche, CNRS
Co-directeur de thèse   Mr Mohammad-Djafari Ali   Directeur de recherche, CNRS
Encadrant   Mr Ayasso Hacheme  Maître de conférences à l'Université de Grenoble
Rapporteurs  Mme Litman Amélie  Maître de conférences à l'Université d'Aix-Marseille
                    Mr Massa Andréa  Professeur à l'Université de Trento, Italie
Examinateurs  Mme Blanc-Feraud Laure  Directrice de recherche, CNRS
                      Mr Pichot du Mezeray Christian  Directeur de recherche, CNRS

Nonlinear control and stability analysis of multi-terminal high voltage direct current (HVDC) networks

Yijing Chen
Soutenance de thèse de doctorat le 8 Avril 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S

The research work in this dissertation was started with the intention of filling some gaps between the theory and the practice, in particular: 1) to investigate various control approaches for the purpose of improving the performance of MTDC systems; 2) to establish connections between existing empirical control design and theoretical analysis; 3) to improve the understanding of the multi-time-scale behavior of MTDC systems characterized by the presence of slow and fast transients in response to external disturbances.

The main contributions of this thesis work are put into three areas, namely nonlinear control design of MTDC systems, analysis of MTDC system's dynamic behaviors and application of MTDC systems for frequency control of AC systems.

In the area of nonlinear control design of MTDC systems, based on different nonlinear control design techniques, new control schemes have been proposed with corresponding theoretical analysis. Besides, the developed control algorithms have been tested by numerical simulations, whose performances are evaluated in comparison to the performance of the conventional vector control method.

The contribution in the area of analyzing MTDC system's dynamic behaviors consists of three parts:1) control induced time-scale separation for a class of nonlinear systems;2) analysis of time-scale separation for an MTDC system with master-slave control configuration;3) analysis of time-scale separation for an MTDC system with droop control configuration.Theoretical analysis mainly based on singular perturbation and Lyapunov theories, have been carried out for each of the aforementioned aspects and confirmed by various simulation studies.

The final contribution relates to the application of MTDC systems where frequency support strategy using MTDC systems has been introduced and analyzed.The principle of the frequency control is to regulate the AC frequency by modulating each AC grid's scheduled (or prescribed) active power.A DC-voltage-based control scheme for the AC frequency regulation is proposed, which achieves the objective of sharing primary reserves between different AC areas interconnected via an MTDC system without using remote information communication.

Membres du jury:

Directeur de thèse :  Dr. LAMNABHI-LAGARRIGUE  Françoise  Directeur de recherche, CNRS
Encadrant:   Dr. DAMM Gilney  Maitre de Conférences, HDR, Université d'Evry-Val-d’Essonne
Co-encadrant :  Dr. BENCHAIB  Abdelkrim  Ingénieur de recherche, HDR, Alstom
Rapporteurs:  Dr. ANNASWAMY Anuradha  Senior Research Scientist, MIT, USA
                     Prof. GIRI Fouad  Professeur à l'Université de Caen Basse-Normandie, France
Examinateurs :  Prof. GLUMINEAU  Alain  Professeur à l'Ecole Centrale de Nantes, France
                        Prof. MARINO Riccardo  Università di Roma Tor Vergata, Italie

Hierarchical control scheme for multi-terminal high voltage direct current power networks.

Miguel JIMÉNEZ CARRIZOSA
Soutenance de thèse de doctorat le 7 Avril 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Amphi F3-06

This thesis focuses on the hierarchical control for a multi-terminal high voltage direct current (MT-HVDC) grid suitable for the integration of large scale renewable energy sources. The proposed control scheme is composed of 4 layers, from the low local control at the power converters in the time scale of units of ms; through distributed droop control (primary control) applied in several terminals in the scale of unit of seconds; and then to communication based Model Predictive Control (MPC) that assures the load flow and the steady state voltage/power plan for the whole system, manage large scale storage and include weather forecast (secondary control); finally reaching the higher level controller that is mostly based on optimization techniques, where economic aspects are considered in the same time as longer timespan weather forecast (tertiary control).

Concerning the converters' level, special emphasis is placed on DC/DC bidirectional converters. The main task of these devices is to link several DC grids with different voltages, in analogous form as the use of transformers for AC grids. In this thesis, three different topologies are studied in depth: two phases dual active bridge (DAB), the three phases DAB, and the use of the Modular Multilevel Converter (MMC) technology as DC/DC converter. For each topology a specific non-linear control is presented and discussed. In addition, the DC/DC converter can provide other important services as its use as a direct current circuit breaker (DC-CB), which is a capital device for the future development of MT-HVDC networks. This is possible thanks to the fact that the DC-DC converters studied here include an AC stage, and therefore there exist instants in which the current passes through zero, and consequently we can open the switches when a fault occurs in the network in a safer way. Several operation strategies are studied for these topologies used as DC-CB.

With respect to primary control, which is the responsible to maintain the DC voltage control of the grid, we have studied several control philosophies: master/slave, voltage margin control and droop control. Finally we have chosen to use droop control, among other reasons, because the communication between nodes is not required. Two different approaches have been studied for the droop control. Firstly, we have considered that dynamics of converters (AC/DC) are negligible (too fast compared to the network), and in a second step, based on these _rst results, we have studied the dynamics of droop control coupled to the AC/DC converters. Voltage source converters (VSC) are used as AC/DC converters in this approach.

Relative to the secondary control, its main goal is to schedule power transfer between the network nodes providing voltage and power references to local and primary controllers, providing steady state response to disturbances and managing power reserves. In this part we have proposed a new approach to solve the power flow problem (non-linear equations) based on the contraction mapping theorem, which gives the possibility to use more than one bus for the power balance (slack bus) instead of the classic approach based on the Newton-Raphson (NR) method. In addition with the method prosed in this thesis the unique existence of solution is guarantee when some feasible constraints are fulfilled. Secondary control plays a very important role in practical applications, in particular when including time varying power sources, as renewable ones. In such cases, it is interesting to consider storage devices in order to improve the stability and the efficiency of the whole system. Due to the sample time of secondary control is on the order of minutes, it is also possible to consider different kinds of forecast (weather, load,..) and to achieve additional control objectives, based on managing storage reserves. All these characteristics encourage the use of a model predictive control (MPC) approach to design this task. In this context, several possibilities of optimization objective were considered, like to minimize transmission losses or to avoid power network congestions.

The main task of tertiary control is to manage the load flow of the whole HVDC grid in order to achieve economical optimization, especially relevant with the presence of storage devices. This control level provides power references to the secondary controller. In this thesis we were able to maximize the economic profit of the system by acting on the spot market, and by optimizing the use of storage devices. In this level it is again used the MPC approach, but acting in a higher time scale, and in a complementary way of the secondary objectives. With the aim of implementing the hierarchical control philosophy ex-plained in this thesis, we have built an experimental test bench. This platform has 4 terminals interconnected via a DC grid, and connected to the main AC grid through VSC power converters. This DC grid can work at a maximum of 400 V, and with a maximum allowed current of 15 A. The local VSC converters are controlled by the dSPACE software package. Also, in this network a supervisor PC (secondary controller) is included, which communicates with each dSPACE software of each VSC through a National Instruments CompactRIO programmable automation controller, which combines embedded real-time and FPGA technology, thought a local area network (internet).

Composition du jury:

Dr. Françoise Lamnabhi-Lagarrigue    L2S-CNRS, CentraleSupélec (Directrice)
Dr. Gilney Damm  L2S (Co-encadrant)
Dr. Abdelkrim Benchaib  ALSTOM GRID  (Co-encadrant)
Prof. Séddik Bacha  Université de Grenoble Alpes  (Rapporteur)
Prof. Aleksandar Stankovic  TUFTS University  (Rapporteur)
Dr. Jean-Luc Thomas  CNAM  (Examinateur)
Dr. Adrià Junyent Ferré  Imperial College London  (Examinateur)
Dr. Fernando Dorado Navas  Universidad de Sevilla  (Examinateur)
M. Stéphan Lelaidier  ALSTOM GRID  (Invité)

S³ Working memory in random neural networks

Séminaire le 3 Avril 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Gilles Wainrib, ENS, Computer Science Department


Numerous experimental studies investigate how neural representations of a signal depend on its past context. Although synaptic plasticity and adaptation may play a crucial role to shape this dependence, we study here the hypothesis that this dependence upon past context may be also explained by dynamical network effects, in particular due to the recurrent nature of neural networks connectivity.

Short Bio: Gilles Wainrib is assistant professor in the Computer Science Department at Ecole Normale Supérieure and his research interests range from theoretical biology to applied mathematics and artificial intelligence.

Talk 1: Level set methods for seismic full waveform inversion. Talk 2: Some inverse problems for cargo container screening.

Séminaire le 30 Mars 2015, 13h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Oliver Dorn, Foreign Guest DIGITEO


Bio: Oliver Dorn is currently Lecturer at the School of Mathematics at The University of Manchester. He has obtained his PhD in Applied Mathematics from The University in Muenster, Germany, in 1997, followed by various postdoctoral research stays in the US and Canada. From 2002 until 2007 he was awarded a Ramon y Cajal fellowship at Universidad Carlos III de Madrid, where he became full professor (Profesor Titular) in 2008. He has visited Supélec and Université Paris Sud frequently for longer periods, and has published more than 50 papers in internationally competitive journals and conference proceedings. He is a professional member of SIAM (Society for Industrial and Applied Mathematics), IEEE (Institute of Electrical and Electronics Engineers) and EAGE (European Association of Geoscientists and Engineers) and is on the advisory board of the Journal 'Inverse Problems'. Right now he is at L2S as Foreign Guest DIGITEO.

S³ - Inverse problems in signal and image processing and S³ - Bayesian inference framework: from basic to advanced Bayesian computation

Séminaire le 27 Mars 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Ali Mohammad Djafari, CNRS, L2S


In signal and image processing community, we can distinguish two categories:
- Those who start from the observed signals and images and do classical processing: filtering for denoising, change detection, contour detection, segmentation, compression, …
- The second category called “model based”, before doing any processing try first to understand from where those signals and images come from and why they are here . So, first defining what quantity has been at the origin of those observations, then modeling their link by “forward modeling” and finally doing inversion. This approach is often called “Inverse problem approach”. Then, noting the “ill-posedness” of the inverse problems, many “Regularization methods” have been proposed and applied successfully. However, deterministic regularization has a few limitations and recently the Bayesian inference approach has become the main approach for proposing unsupervised methods and effective solutions in many real applications. Interestingly, even many classical methods have found better understanding when re-stated as inverse problem. The Bayesian approach with simple prior models such as Gaussian, Generalized Gaussian, Sparsity
enforcing priors or more sophisticated Hierarchical models such as Mixture models, Gaussian Scale Mixture or Gauss-Markov-Potts models have been proposed in different applications of imaging systems with great success. However, Bayesian computation still is too costly and need more practical algorithms than MCMC. Variational Bayesian Approximation (VBA) methods have recently became a standard for computing the posterior means in unsupervized methods.
Interestingly, we show that VBA includes Joint Maximum A Posteriori (JMAP) and Expectation-Maximization (EM) as special cases. VBA is much faster than MCMC methods, but, it gives only access to the posterior means.
This talk gives an overview of these methods with examples in Deconvolution (simple or blind, signal or image) and  in Computed Tomography (CT).

Bio: http://djafari.free.fr/index.htm

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PDE-­‐based inversion method with no forward solver for inverse medium scattering problems

Séminaire le 20 Mars 2015, 14h00 à CentraleSupelec (Gif-sur-Yvette) Salle du conseil du L2S - B4.40
Dr. Yu Zhong


Bio: Dr. Yu Zhong received his B.S. and M.S. degrees in electronic engineering from Zhejiang University, Hangzhou, China, in 2003 and 2006, respectively, and the Ph.D. degree from the National University of Singapore, Singapore, in 2010.
He is currently a Scientist in Institution of High Performance Computing (IHPC), A*STAR, Singapore.
His research interests mainly are inverse-­‐scattering problems and electromagnetic modeling on composite materials. He is a regular visitor at the Laboratoire des Signaux et Systèmes (L2S) in Gif-­sur-­‐Yvette, France as an invited senior scientific expert since 2012.
 
Talk 1: PDE-­‐based inversion method with no forward solver for inverse medium scattering problems
A new partial differential equation (PDE) based inversion method for inverse medium scattering problems is proposed in this talk, which does not need to solve any forward problem. The proposed method is the subspace-­‐based optimization method (SOM) in the differential-­‐equation frame. The finite difference scheme is used to discretized the Helmholtz equation, and the twofold subspace-­‐based regularization scheme, as in the integral equation based SOM, is applied in this PDE-­‐based inversion method to stabilize the solver. By using such a PDE-­‐based inversion method, the Green’s funciton for the domain of interests is no longer needed. Representative numerical tests are presented to verify the efficacy of the proposed method.

Talk 2: New integral equation and new partial differential equation for inverse medium scattering problems with strong scatterers 

In this talk, we propose two new equations, an integral equation (IE) and a partial differential equation (PDE), for solving inverse medium scattering problems (IMSP) with strong scatterers. First, we present a new integral equation, which could effectively reduce the globle wave contribution in estimating the contrast (the difference between permittivities of the scatterers and the known background) compared to the original Lippmann-­‐Schwinger equation. Using such a new IE in the IE-­‐based inversion method one is able to solve the highly nonlinear IMSP with strong scatterers.
Subsequently, the connection between the PDE-­‐based inversion method (in Talk 1), using the Helmholtz equation, and the conventional IE based inversion method, using the Lippmann-­‐Schwinger equation, is discussed. With such a connection and the new IE, we propose a new PDE,
using which the PDE-­‐based inversion method can also solve the highly nonlinear IMSP. At last, we discuss the pros and cons of both PDE-­‐ and IE-­‐based inversion methods.

S³ - Analysis of remote sensing multi-sensor heterogeneous images

Séminaire le 20 Mars 2015, 10h30 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Jorge Prendes, IRIT Toulouse and SONDRA CentraleSupelec


Remote sensing images are images of the Earth acquired from planes or satellites. In recent years the technology enabling this kind of images has been evolving really fast. Many different sensors have been developed to measure different properties of the earth surface, including optical images, SAR images and hyperspectral images. One of the interest of this images is the detection of changes on datasets of multitemporal images. Change detection has been thoroughly studied on the case where the dataset consist of images acquired by the same sensor. However, having to deal with datasets containing images acquired from different sensors (heterogeneous images) is becoming very common nowadays.
In order to deal with heterogeneous images, we proposed a statistical model which describe the joint distribution of the pixel intensity of the images, more precisely a mixture model. On unchanged areas, we expect the parameter vector of the model to belong to a manifold related to the physical properties of the objects present on the image, while on areas presenting changes this constraint is relaxed. The distance of the model parameter to the manifold can be thus be used as a similarity measure, and the manifold can be learned using ground truth images where no changes are present. The model parameters are estimated through a collapsed Gibbs sampler using a Bayesian non parametric approach combined with a Markov random field.
In this talk I will present the proposed statistical model, its parameter estimation, and the manifold learning approach. The results obtained with this method will be compared with those of other classical similarity measures.

Bio: Jorge Prendes was born in Santa Fe, Argentina in 1987. He received the 5 years Eng. degree in Electronics Engineering with honours from the Buenos Aires Institute of Technology (ITBA), Buenos Aires, Argentina in July 2010. He worked on Signal Processing at ITBA within the Applied Digital Electronics Group (GEDA) from July 2010 to September 2012. Currently he is a Ph.D. student in Signal Processing in SONDRA laboratory at Supélec, within the cooperative laboratory TéSA and the Signal and Communication Group of the Institut de Recherche en Informatique de Toulouse (IRIT). His main research interest include image processing, applied mathematics and pattern recognition.

 

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S³: Rare event simulation: a Point Process interpretation with application in probability and quantile estimati

Séminaire le 13 Mars 2015, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Clément Walter, CEA and University Paris Diderot


Clément Walter, 25, graduated from Mines ParisTech in 2013. Beforehand he attended preparatory classes in Lycée Sainte-Geneviève (branch Maths and Physics). For his master degree he specialised in Geostatistics and started working with CEA as an intern on emulation of complex computer codes (especially kriging) for rare event simulation and estimation. He has then pursued his work in a PhD under the direction of Pr. Josselin Garnier, focusing on multilevel splitting methods.

S³ Bayesian Tomography

Séminaire le 6 Mars 2015, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
John Skilling, Maximum Entropy Data Consultants Ltd, UK


Bio: John Skilling was awarded his PhD in radio astronomy in 1969.  Through the 1970s and 1980s he was a lecturer in applied mathematics at Cambridge University, specialising in data analysis.  He left to concentrate on consultancy work, originally using maximum entropy methods but moving to Bayesian methodology when algorithms became sufficiently powerful.  John has been a prominent contributor to the “MaxEnt” conferences since their beginning in 1981.  He is the discoverer of the nested sampling algorithm which performs integration over spaces of arbitrary dimension, which is the basic operation dictated by the sum rule of Bayesian calculus.

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S³ L0 optimization for DOA and sparse channel estimation

Séminaire le 6 Mars 2015, 10h00 à CentraleSupelec (Gif-sur-Yvette) Salle des séminaires du L2S
Adilson Chinatto, Univeristy of Campinas, BR and Ecole Normale Supérieure de Cachan, FR


Bio: Adilson Chinatto received a degree in Electrical Engineering in 1997 and Masters in 2011, both from the University of Campinas (Unicamp), Brazil. He worked as hardware, software and firmware development engineer for optical transmission equipment in the companies AsGa and CPqD in Brazil. He is a co-founder of Espectro Ltd., a Brazilian design house for hardware and software, focused in signal processing. Nowadays he is coordinator of a High Performance GPS Receiver Project at Espectro Ltd. funded by the Brazilian National Counsel of Technological and Scientific Development (CNPq). He has experience in electrical engineering with emphasis on telecommunication systems, digital signal processing and smart antennas, working mainly with development and implementation of programmable logic devices (FPGA). He is currently finishing his Ph.D. at Unicamp, working with sparse and compressive sensing signal processing.

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