Pere Colet and Damia Gomila

Instituto de Física Interdisciplinar y Sistemas Complejos, IFISC (CSIC-UIB)

11 juillet 2024, 14h
Salle des commissions
Campus Saint-Jérôme
https://univ-amu-fr.zoom.us/j/88505334444?pwd=38rJZyBA8Df7TDvy1nCra7u0QstRaV.1

Pere Colet
Power grid frequency fluctuations in scenarios of large penetration of renewables


As the transition towards a sustainable energy system accelerates, conventional power plants are progressively replaced by variable renewable energy sources. This reduces the overall flexibility of the grid, requiring additional control strategies to ensure stable operation. We consider a model for the high-voltage grid including conventional and variable renewable generation, as well as demand variations. By assimilating load and generation data, the model reproduces frequency fluctuations with the current power mix with a high degree of accuracy. Moreover, it allows to simulate the frequency dynamics for different scenarios with a very high penetration of renewable energy. As a case study, we analyze the power grid of Gran Canaria, which is isolated, and the Balearic Islands, connected to mainland with a DC cable, considering an increasing share of, respectively wind and solar generation.

Damia Gomila
Power grid frequency fluctuations and smart devices with dynamic demand control

The increase of electric demand and the progressive integration of renewable sources threatens the stability of the power grid. To solve this issue, several methods have been proposed to control the demand side instead of increasing the spinning reserve in the supply side. Here we focus on dynamic demand control (DDC), a method in which smart devices can autonomously delay its scheduled operation if the electric frequency is outside a suitable range. DDC can effectively reduce small and medium size frequency fluctuations but, due to the need of recovering pending tasks, the probability of large demand peaks, and hence large frequency fluctuations, may actually increase. Although these events are very rare they can potentially trigger a failure of the system and therefore strategies to avoid them have to be addressed. We show also that an improved method including communication among DDC devices belonging to a given group, such that they can coordinate opposite actions to keep the group demand more stable can reduce the amount of pending tasks by a factor 10 while large frequency fluctuations are significantly reduced or even completely avoided.

Michel Fliess

LIX – Palaiseau

7 décembre 2023, 14.30
Salle X133
Campus Toulon

Atténuer les congestions internet grâce aux outils de l’automatique

Active Queue Management (AQM) for mitigating Internet congestion has been addressed via various feedback control syntheses, especially P, PI, and PID regulators, by using a linear approximation where the round trip time, i.e., the delay, is assumed to be constant. This constraint is lifted here by using a nonlinear modeling with a variable delay, introduced more than 20 years ago. This delay, intimately linked to the congestion phenomenon, may be viewed as a flat output. All other system variables, especially the control variable, i.e., the packet loss ratio, are expressed as a function of the delay and its derivatives: they are frozen if the delay is kept constant. This flatness-like property, which demonstrates the mathematical discrepancy of the linear approximation adopted until today, yields also our control strategy in two steps: Firstly, designing an open-loop control, thanks to straightforward Flatness-Based Control (FBC) techniques, and secondly, closing the loop via Model-Free Control (MFC) in order to take into account severe model mismatches, like, here, the number of TCP sessions. Several convincing computer simulations, which are easily implementable, are presented and discussed.

Alessandro Scagliotti

TUM Munich

30 novembre 2023, 14.00
Salle X133
Campus Toulon

Ensemble optimal control: ResNets, diffeomorphisms approximation and
Normalizing Flows

In the last years it was observed that Residual Neural
Networks (ResNets) can be interpreted as discretizations of control
systems, bridging ResNets (and, more generally, Deep Learning) with
Control Theory. In the first part of this seminar we formulate the task
of a data-driven reconstruction of a diffeomorphism as an ensemble
optimal control problem. In the second part we adapt this machinery to
address the problem of Normalizing Flows: after observing some samplings
of an unknown probability measure, we want to (approximately) construct
a transport map that brings a “simple” distribution (e.g., a Gaussian)
onto the unknown target distribution. In both the problems we use tools
from $\Gamma$-convergence to study the limiting case when the size of
the data-set tends to infinity.

This talk is based on the papers

Deep Learning approximation of diffeomorphisms via linear-control systems.

Normalizing flows as approximations of optimal transport maps via
linear-control neural ODEs

Hassan Haghighi

LIS (UMR CNRS 7020)

12 octobre 2023, 14.00
Salle des commissions
Campus St. Jérôme


Path Planning According to the Fault Tolerance and Modeling. Application in: Autonomous Emergency Landing for Aircraft

 In the field of controlling complex systems, a key focus is on developing strategies to handle technical, dynamic, structural defects, and faults. This study analyzes equation stability and state-space structure changes to identify stable system poles despite the presence of defects. Additionally, it employs Dubin’s equations to swiftly devise emergency landing routes. To implement in a case study project, we construct sample sets of stable poles for the system according to the defects and calculate corresponding path as admissible set. From these samples, we design a path planning system to select specific points. Our concept integrates Dubin’s path for emergency landings, enabling an optimization system to choose from admissible stable routes.

Swann Marx

L2SN (UMR CNRS 6004) Nantes

27 avril 2023, 14.00
Salle des commissions
Campus St. Jérôme

Singular perturbation analysis for a coupled KdV-ODE system

This talk will be about the singular perturbation analysis of
a Korteweg-de Vries equation, which is a nonlinear PDE modeling waves on
shallow water surfaces, coupled with an ODE. The coupled system may
admit different time-scales, and this particular feature will be taken
into account when analysing the asymptotic stability of the coupled
system. To introduce our methodology, we will first explain how it can
be applied on scalar ODEs. We will then give some insights on the
difficulties when applying it on already known coupled PDE-ODE systems.
Finally, we will show how one can apply this methodology for the KdV-ODE
system under consideration. This talk is based on a joint work with
Eduardo Cerpa, professor at the Universidad Catolica de Chile.

David Hill

LIMOS (UMR CNRS 6158 – UCA – Clermont Auvergne INP)

30 mars 2023, 14.00
Salle des commissions
Campus St. Jérôme

Reproductibilité et répétabilité des simulations stochastiques.

L’un des critères majeurs de la scientificité d’une étude de recherche est la reproductibilité. Dans cet exposé, nous présenterons les principales définitions autour de la reproductibilité, elles ont évolué récemment à l’ACM en 2020. Nous examinerons dans quelle mesure les travaux d’informatique et de simulation sont concernés. Nous donnerons quelques exemples d’applications incluant des simulations stochastiques parallèles, qui sont trop souvent présentées comme non reproductibles. Toute personne souhaitant produire un travail scientifique en simulation a intérêt à prêter attention à la reproductibilité numérique de ses résultats. Des différences significatives peuvent être observées dans les résultats de simulations parallèles si les meilleures pratiques ne sont pas appliquées. Nous verrons que même dans ce contexte, il est possible de reproduire les mêmes résultats numériques en mettant en œuvre une méthode rigoureuse testée jusqu’à un milliard de threads. Il est ainsi possible de vérifier les résultats parallèles avec leurs contreparties séquentielles et ce avant un passage « à l’échelle », gagnant ainsi en confiance dans les modèles développés. Ce séminaire présentera quelques bonnes pratiques pour des simulations stochastiques parallèles, permettant même de faire face erreurs silencieuses qui impactent les supercalculateurs (dont la machine Exascale présentée l’an passé à Hambourg). 

Biographie :

David Hill est professeur à l’Université Clermont Auvergne, il effectue ses recherches au LIMOS (UMR CNRS 6158 – UCA – Clermont Auvergne INP). Après un doctorat en 1993 et une Habilitation à diriger les recherches en 2000 dans le domaine de la simulation stochastique à événements discrets appliquée à l’environnement ou aux Sciences Fondamentales, il a servi à l’Université Blaise Pascal en tant que Vice-Président délégué au TIC, à la direction du centre Régional de Calcul (CRRI) et 2 fois en tant que directeur adjoint de l’ISIMA (école d’ingénieur clermontoise membre de Clermont Auvergne INP). David Hill s’occupe actuellement de la Graduate Track de l’INP. Il s’intéresse à la thématique de la recherche reproductible à partir de 2014 et a récemment supervisé des recherches au CERN en calcul à hautes performances. 

Térence Bayen

LMA (Avignon)

19 janvier 2023, 11.00
Salle X 133
Campus Toulon

A hybrid maximum principle including regional switching parameters.

 In this presentation, we consider a Mayer optimal control problem where the controlled system is defined over a partition of the euclidean space, and we assume that the dynamics depends on some additional regionally switching parameter. This means that the parameter should remain constant as long as the trajectory belongs to a given stratum, but, in contrast with optimal control problems including (constant) parameters, it is now authorized to change its value each time the system enters into a new stratum. This framework is motivated by several applications arising in the context of aerospace engineering or in epidemiology (typically when a loss of control occurs). In this presentation, we give the necessary optimality conditions in this framework in the spirit of a hybrid maximum principle. The necessary optimality conditions involve a jump of the covector at the interface between two strata and also an averaged gradient condition related to the regionally switching parameter. We shall also give some insights how to obtain such a result using needle’s type variations. 

Eugenio Pozzoli

Eugenio Pozzoli
IMB

20 octobre 2022, 14.30
Salle X 133
Campus Toulon

Contrôlabilité des systèmes quantiques en dimension infinie

L’étude des propriétés de contrôlabilité d’un système quantique joue un rôle important dans les applications en physique et en chimie, comme par example la spectroscopie et l’information quantique. Les questions que j’aborderai dans cet exposé sont principalement deux : (i) le système (fermé) peut-il être contrôlé parmi tous ses états ? (ii) quels états peuvent être atteints en temps petit ? La question (i) est un problème de contrôlabilité bilinéaire (globale). La question (ii) est un problème d’accessibilité bilinéaire en petit temps, lié au problème du temps minimal. Dans le cadre où l’état évolue dans un espace infini-dimensionnel, je présenterai quelques réponses aux questions (i) en utilisant des approximations fini-dimensionnelles avec des contrôles périodiques et (ii) en utilisant une technique de saturation issue du contrôle géométrique avec des contrôles pas bornés. Je montrerai aussi des applications de ces résultats au contrôle de la dynamique rotationelle des molécules, vues comme des corps rigides quantiques.