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Effect of Metallic Ion Implantation on Dark Current Distributions of Silicon-Based CMOS Image Sensors
No full textInternational audienceAccidental metallic contamination is known to have a deleterious impact on the dark current characteristics of silicon-based CMOS image sensors (CIS), especially when metallic species are present in the depletion region of the photodiode. Solving a contamination issue requires a clear identification of the contaminant signature on the sensor response. In this study, different metallic species were voluntarily introduced in the photodiode region of Si-based CIS wafers, using ion implantation at relatively low doses. The dark current spectroscopy (DCS) technique is used to quantify the influence of each of these metallic species on the sensor performance. The results presented herein could aid in their identification after accidental contamination in a clean room environment, particularly in the cases of Pd, Mn and Nb, for which the references in the literature are scarce
Data-driven control of input saturated systems: a LMI-based approach
No full textInternational audienceThis paper addresses three complex control challenges related to input-saturated systems from a data-driven perspective. Unlike the traditional two-stage process involving system identification and model-based control, the proposed approach eliminates the need for an explicit model description. The method combines data-based closed-loop representations, Lyapunov theory, instrumental variables, and a generalized sector condition to formulate data-driven linear matrix inequalities (LMIs). These LMIs are applied to maximize the origin’s basin of attraction, minimize the closed-loop reachable set with bounded disturbances, and introduce a new data-driven ℓ2-gain minimization problem. Demonstrations on benchmark examples highlight the advantages and limitations of the proposed approach compared to an explicit identification of the system, emphasizing notable benefits in handling nonlinear dynamics
On Analyzing Filters with Bayesian Parameter Inference and Poisson-Sampled Observations
No full textInternational audienceThe problem of state estimation in continuous-time linear stochastic systems is considered with several constraints on the available information. It is stipulated that the model of the system contains several unknown parameters and the observation process is randomly time-sampled. The classical solution due to Kalman-Bucy cannot be implemented in that case, and we revisit the idea of partitioning the set of unknown parameters, and consider multiple filters corresponding to each possible value of the unknown parameter. The posterior distribution of the unknown parameters conditioned upon available observations is computed from Bayes' rule. The resulting state estimate is a weighted sum of the state estimates generated by multiple Kalman filters, where the weights are determined by the posterior distribution of the unknown parameters. We analyze the performance of the algorithm by looking at its asymptotic behavior and establishing boundedness of the error covariance matrix
Constrained Zonotope-based localization of mobile agents with uncertain observation times
No full textSubmitted to IEEE TCST journal on 09/12/2024This paper presents an extended set-membership state estimator based on constrained zonotopes, addressing the practical challenge of uncertain asynchronous observation arrival times, including timing errors. Additionally, the proposed estimator accounts for parametric uncertainty in the observation equation and incorporates multiple state propagation models. The filter provides valid state enclosures despite observation time uncertainty, which is a critical feature for real-world applications. To demonstrate its effectiveness, we present an academic problem simulating a real-world application. Performance comparisons with existing nonlinear estimation algorithms, including the ellipsoidal set state estimator, Iteration Estimation Set Membership Filter (IESMF), the set inversion algorithm (SIVIA), and the classic Extended Kalman Filter (EKF), highlight the superior efficiency and performance improvements of the proposed approach
Hybridizing photovoltaics and thermoelectrics: a detailed-balance analysis
No full textNational audienceThe combination of photovoltaic and thermoelectric converters could potentially lead to an improvement in the efficiency with which solar energy is converted into electricity, thanks to the improved exploitation of the residual heat generated in the PV cells. Using the detailed balance formalism, we develop a simple model enabling to derive the ultimate efficiency limits of PV-TE systems based on a restricted number of operating parameters, including the bandgap of the semiconductor materials used, the cell temperature and the concentration ratio of the solar flux to which the PV cells are subjected. It is shown that in the radiative limit, the added value of PV-TE systems remains relatively modest, with an improvement in the electrical power generated of the order of 5% relative to conventional PV systems, and up to 15% for CPV systems. Secondly, the limited capacity of real photovoltaic cells to approach their own theoretical limits is taken into account. We demonstrate a substantial improvement in the performance of PV-TE systems incorporating realistic solar cells operating at a fraction of their theoretical limit, compared with reference PV systems. The value of solar concentration, which provides an additional leverage in the quest for high temperatures, while mitigating the adverse effect of temperature on PV efficiency, is also highlighted. Finally, we discuss the practical limitations of the model and outline the operating and material parameters that need to be taken into account in order to rigorously determine the added value of these systems compared with conventional PV modules
Développement d’une Méthodologie pour l’Étude de la Susceptibilité Électromagnétique en Champ Proche
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Visual Predictive Control for Mobile Manipulator: Visibility, Manipulability, and Stability
No full textInternational audienceThis paper proposes a visual predictive control solution adapted to mobile manipulators and able to cope with several issues related to visibility, manipulability, and stability. To address these problems, the proposed strategy relies on (i) the use of two complementary cameras, (ii) the definition of a cost function depending on both the vision-based task and the manipulability, (iii) the integration of time-varying constraints allowing to prioritize the former against the latter. The strategy has been analyzed through simulation using ROS and Gazebo and implemented on our TIAGo robot. The obtained results fully validate the proposed approach
Innovative 3D Power Module Defaults Detection via Thermal Impedance Analysis and Simulations
No full textInternational audienceThis article presents a method for detecting physical defects in an innovative 3D Silicon (Si) power module by measuring thermal impedance (Zth). A non-invasive method for measuring the junction temperature of dies is introduced (voltage drop across a diode under constant current), and a comparison is made with simulation results (CELSIUS EC SOLVER software). The observed differences are analyzed to propose hypotheses for defects origins and location. A scanning electron microscopy (SEM) observation is also used to validate these hypotheses. The results confirm that the comparison between experimental and simulation data of Zth is a precise method for determining the areas of physical defects
Multi-layered Model for Performance Evaluation of oneM2M-based IoT Solution
No full textInternational audienceIn this paper we evaluate the impact of standards in terms of performance and their applicability in the field of IoT system design and deployment. We focus on the global IoT oneM2M standard. Our objective is to evaluate a oneM2M-based IoT solution regarding different relevant Key Performance Indicators. We propose a multi layered-model of an IoT standardized solution, able to tackle applicative, infrastructure and deployment aspects. Based on this model, we are able to globally evaluate and analyze, through simulation, the adequacy of a deployment with respect to the initial applicative constraints and the chosen oneM2M standard implementation. In our case, the constraints are mix-critical coming from the e-Health remote monitoring of patient by their physician but also the management of the patient in case of vital emergency situation. By tuning the system configuration and parameters of the proposed applicative scenario, we evaluate, by simulation, the KPIs of a oneM2M-based IoT solution by exploiting (1) the different features of the standard, (2) the capabilities of the underlying infrastructure, and (3) the performance of the oneM2M stacks used in the solution. The simulation and performance evaluation are based on two tools developed by the authors. One is a specific profiler for oneM2M open-source stack, whereas the simulation and performance evaluation is build on top of the OMNeT++ discrete event simulator
Etude de couches minces de titanate de barium déposées par pulvérisation
No full textNational audienceLe titanate de barium (BaTiO3 ) est un matériau qui suscite beaucoup d'intérêt car ses propriétés électro-optique, piézo-électrique et même thermo-optique peuvent dépasser significativement celles du niobate de lithium (LiNbO3), le matériau phare de l'optique et de la photonique non-linéaire. Néanmoins, la valeur exacte de ces paramètres est intimement liée à la méthode d'élaboration du matériau (pulvérisation, dépôt par laser pulsé ou épitaxie à jets moléculaires) et à la cristallinité du matériau atteinte.Cette contribution présente nos résultats récents portant sur le dépôt par pulvérisation de couches minces de BaTiO3 sur des substrats de silice fondue (SiO2), d'oxyde de magnésium (MgO) et de titanate de strontium (SrTiO3) et ainsi que leur post-traitement par recuit flash.