Search

International audience; Cloud and High-Performance Computing (HPC) systems are increasingly facing issues of dynamic variability, in particular w.r.t. performance and power consumption. They are becoming less predictable, and therefore demand more runtime management by feedback loops. In this work, we describe results addressing autonomic administration in HPC systems through a control theoretical approach. We more specifically consider the need for controllers that can adapt to variations a long time in the behavior of controlled systems, but also to being reused on different systems and processors. We therefore explore the application of Model-Free Control (MFC) in the context of resource harvesting in a Computing Grid, by regulating the injection of flexible jobs while limiting perturbation of the prioritary applications.

Time series segmentation is one of the many data mining tools. This paper, in French, takes local extrema as perceptually interesting points (PIPs). The blurring of those PIPs by the quick fluctuations around any time series is treated via an additive decomposition theorem, due to Cartier and Perrin, and algebraic estimation techniques, which are already useful in automatic control and signal processing. Our approach is validated by several computer illustrations. They underline the importance of the choice of a threshold for the extrema detection., Comment: 13th International Conference on Modeling, Optimization and Simulation (MOSIM 2020), Agadir (Morocco), 12-14 November 2020, in French

In today's literature "Model-Free Control," or MFC, and "Active Disturbance Rejection Control," or ADRC, are the most prominent approaches in order to keep the benefits of PID controllers, that are so popular in the industrial world, and in the same time for attenuating their severe shortcomings. After a brief review of MFC and ADRC, several examples show the superiority of MFC, which permits to tackle most easily a much wider class of systems., in French

An elementary mathematical example proves, thanks to the Routh-Hurwitz criterion, a result that is intriguing with respect to today's practical understanding of model-free control, i.e., an "intelligent" proportional controller (iP) may turn to be more difficult to tune than an intelligent proportional-derivative one (iPD). The vast superiority of iPDs when compared to classic PIDs is shown via computer simulations. The introduction as well as the conclusion analyse model-free control in the light of recent advances., in French, https://www.openscience.fr/Un-resultat-intrigant-en-commande-sans-modele

The recent popularity of post-denitrification processes in the greater Paris area wastewater treatment plants has caused a resurgence of the presence of nitrite in the Seine river. Controlling the production of nitrite during the post-denitrification has thus become a major technical issue. Research studies have been led in the MOCOPEE program (www.mocopee.com) to better understand the underlying mechanisms behind the production of nitrite during wastewater denitrification and to develop technical tools (measurement and control solutions) to assist on-site reductions of nitrite productions. Prior studies have shown that typical methanol dosage strategies produce a varying carbon-to-nitrogen ratio in the reactor, which in turn leads to unstable nitrite concentrations in the effluent. The possibility of adding a model-free control to the actual classical dosage strategy has thus been tested on the SimBio model, which simulates the behavior of wastewater biofilters. The corresponding "intelligent" feedback loop, which is using effluent nitrite concentrations, compensates the classical strategy only when needed. Simulation results show a clear improvement in average nitrite concentration level and level stability in the effluent, without a notable overcost in methanol., in french, Journal of Water Science, to appear

International audience; The control design of an artificial pancreas, a hot research topic in diabetology, is tackled via the newly introduced model-free control and its corresponding "intelligent" proportional controller, which were already quite successful in many concrete and diverse situations. It results in an insulin injection for type 1 diabetes which displays via constant references a good nocturnal/fasting response, but unfortunately a poor postprandial behavior due to long hyperglycemia. When a variable reference is introduced, that switches between a constant one, when glycemia is more or less normal or moderate, and an exponential decay reference path, when a high glycemia rate indicates a meal intake, the results in silico, which employ real clinical data, become excellent. We obtain a bolus-shaped insulin injection rate during postprandial phases. The hyperglycemic peaks are therefore lowered a lot.

Recent advances in the understanding of time series permit to clarify seasonalities and cycles, which might be rather obscure in today's literature. A theorem due to P. Cartier and Y. Perrin, which was published only recently, in 1995, and several time scales yield, perhaps for the first time, a clear-cut definition of seasonalities and cycles. Their detection and their extraction, moreover, become easy to implement. Several computer experiments with concrete data from various fields are presented and discussed. The conclusion suggests the application of this approach to the debatable Kondriatev waves., Comment: in 2015 Paris Financial Management Conference (14-15 December 2015)

Systematic and multifactor risk models are revisited via methods which were already successfully developed in signal processing and in automatic control. The results, which bypass the usual criticisms on those risk modeling, are illustrated by several successful computer experiments., Comment: First Paris Financial Management Conference, Paris : France (2013)

International audience; It is shown that the "intelligent" controllers which are associated to the recently introduced model-free control synthesis may be easily implemented on cheap and small programmable devices. Several successful numerical experiments are presented with a special emphasis on fault tolerant control.

A new standpoint on financial time series, without the use of any mathematical model and of probabilistic tools, yields not only a rigorous approach of trends and volatility, but also efficient calculations which were already successfully applied in automatic control and in signal processing. It is based on a theorem due to P. Cartier and Y. Perrin, which was published in 1995. The above results are employed for sketching a dynamical portfolio and strategy management, without any global optimization technique. Numerous computer simulations are presented., Conf\'erence M\'editerran\'eenne sur l'Ing\'enierie S\^ure des Syst\`emes Complexes, MISC 2011, Agadir : Maroc (2011)

The experience gained with numerous successful applications permits to revisit some points of model-free control. The numerical differentiation of noisy signals may be replaced by a real time parameter identification which is much simpler. The strange ubiquity of classic PIDs is explained as well as the almost universal utilization of ultra-local models of order 1. We show that even with a partially known model the utilization of an intelligent PI controller remains profitable. Two examples, an inverted pendulum and a heat exchanger, seem to confirm the superiority of model-free control with respect to sliding modes control and techniques stemming from infinite-dimensional systems, such as delays or partial differential equations. Our paper is illustrated by several computer simulations.

A new concept called "Model-Free Control" is applied to hydroelectric run-of-the river power plants, with severe constraints and operating conditions. Numerous computer simulations display excellent results, which are obtained thanks to simple and robust algorithms.

International audience; We are settling a longstanding quarrel in quantitative finance by proving the existence of trends in financial time series thanks to a theorem due to P. Cartier and Y. Perrin, which is expressed in the language of nonstandard analysis (Integration over finite sets, F. & M. Diener (Eds): Nonstandard Analysis in Practice, Springer, 1995, pp. 195--204). Those trends, which might coexist with some altered random walk paradigm and efficient market hypothesis, seem nevertheless difficult to reconcile with the celebrated Black-Scholes model. They are estimated via recent techniques stemming from control and signal theory. Several quite convincing computer simulations on the forecast of various financial quantities are depicted. We conclude by discussing the rôle of probability theory.

The signal to noise ratio, which plays such an important r��le in information theory, is shown to become pointless for digital communications where the demodulation is achieved via new fast estimation techniques. Operational calculus, differential algebra, noncommutative algebra and nonstandard analysis are the main mathematical tools.

The signal to noise ratio, which plays such an important role in information theory, is shown to become pointless in digital communications where - symbols are modulating carriers, which are solutions of linear differential equations with polynomial coefficients, - demodulations is achieved thanks to new algebraic estimation techniques. Operational calculus, differential algebra and nonstandard analysis are the main mathematical tools.

This note is sketching a simple and natural mathematical construction for explaining the probabilistic nature of quantum mechanics. It employs nonstandard analysis and is based on Feynman's interpretation of the Heisenberg uncertainty principle, i.e., of the quantum fluctuations, which was brought to the forefront in some fractal approaches. It results, as in Nelson's stochastic mechanics, in stochastic differential equations which are deduced from infinitesimal random walks. An extended english abstract gives most of the details.

A control strategy without any precise mathematical model is derived for linear or nonlinear systems which are assumed to be finite-dimensional. Two convincing numerical simulations are provided.

This note is answering an old questioning about the F��nyes-Nelson stochastic mechanics. The Brownian nature of the quantum fluctuations, which are associated to this mechanics, is deduced from Feynman's interpretation of the Heisenberg uncertainty principle via infinitesimal random walks stemming from nonstandard analysis. It is therefore no more necessary to combine those fluctuations with a background field, which has never been well understood. Most of the technical details are contained in an extended english abstract.

New definitions are suggested for frequencies which may be instantaneous or not. The Heisenberg-Gabor inequality and the Shannon sampling theorem are briefly discussed.

Publication in the conference proceedings of EUSIPCO, Viena, Austria, 2004

A continuously time-varying transmission rate is suggested by many control-theoretic investigations on non-pharmaceutical interventions for mitigating the COVID-19 pandemic. However, such a continuously varying rate is impossible to implement in any human society. Here, we significantly extend a preliminary work (M. Fliess, C. Join, A. d’Onofrio, Feedback control of social distancing for COVID-19 via elementary formulae, MATHMOD, Vienna, 2022), based on the combination of flatness-based and model-free controls of the classic SIR model. Indeed, to take into account severe uncertainties and perturbations, we propose a feedback control where the transmission rate,i.e., the control variable, is piecewise constant. More precisely, the transmission rate remains constant during an appreciable time interval. Strict extended lockdowns may therefore be avoided. The poor knowledge of fundamental quantities such as the rate of infection hinders a precise calibration of the transmission rate. Thus, the results of our approach ought therefore not to be regarded as rules of action to follow accurately but as a guideline for a wise behavior.