Safran (France)

We analyze the convergence aspects of the invariant extended Kalman filter (IEKF), when the latter is used as a deterministic nonlinear observer on Lie groups, for continuous-time systems with discrete observations. One of the main features of invariant observers for left-invariant systems on Lie groups is that the estimation error is autonomous. In this paper we first generalize this result by characterizing the (much broader) class of systems for which this property holds. For those systems, the Lie logarithm of the error turns out to obey a linear differential equation. Then, we leverage this “log-linear” property of the error evolution, to prove for those systems the local stability of the IEKF around any trajectory, under the standard conditions of the linear case. One mobile robotics example and one inertial navigation example illustrate the interest of the approach. Simulations evidence the fact that the EKF is capable of diverging in some challenging situations, where the IEKF with identical tuning keeps converging.

In this paper, we propose a novel accurate method for dead-reckoning of wheeled vehicles based only on an Inertial Measurement Unit (IMU). In the context of intelligent vehicles, robust and accurate dead-reckoning based on the IMU may prove useful to correlate feeds from imaging sensors, to safely navigate through obstructions, or for safe emergency stops in the extreme case of exteroceptive sensors failure. The key components of the method are the Kalman filter and the use of deep neural networks to dynamically adapt the noise parameters of the filter. The method is tested on the KITTI odometry dataset, and our dead-reckoning inertial method based only on the IMU accurately estimates 3D position, velocity, orientation of the vehicle and self-calibrates the IMU biases. We achieve on average a 1.10% translational error and the algorithm competes with top-ranked methods which, by contrast, use LiDAR or stereo vision.

International audience

The Kalman filter—or, more precisely, the extended Kalman filter (EKF)—is a fundamental engineering tool that is pervasively used in control and robotics and for various estimation tasks in autonomous systems. The recently developed field of invariant extended Kalman filtering uses the geometric structure of the state space and the dynamics to improve the EKF, notably in terms of mathematical guarantees. The methodology essentially applies in the fields of localization, navigation, and simultaneous localization and mapping (SLAM). Although it was created only recently, its remarkable robustness properties have already motivated a real industrial implementation in the aerospace field. This review aims to provide an accessible introduction to the methodology of invariant Kalman filtering and to allow readers to gain insight into the relevance of the method as well as its important differences with the conventional EKF. This should be of interest to readers intrigued by the practical application of mathematical theories and those interested in finding robust, simple-to-implement filters for localization, navigation, and SLAM, notably for autonomous vehicle guidance.

This paper proposes a learning method for denoising gyroscopes of Inertial\nMeasurement Units (IMUs) using ground truth data, and estimating in real time\nthe orientation (attitude) of a robot in dead reckoning. The obtained algorithm\noutperforms the state-of-the-art on the (unseen) test sequences. The obtained\nperformances are achieved thanks to a well-chosen model, a proper loss function\nfor orientation increments, and through the identification of key points when\ntraining with high-frequency inertial data. Our approach builds upon a neural\nnetwork based on dilated convolutions, without requiring any recurrent neural\nnetwork. We demonstrate how efficient our strategy is for 3D attitude\nestimation on the EuRoC and TUM-VI datasets. Interestingly, we observe our dead\nreckoning algorithm manages to beat top-ranked visual-inertial odometry systems\nin terms of attitude estimation although it does not use vision sensors. We\nbelieve this paper offers new perspectives for visual-inertial localization and\nconstitutes a step toward more efficient learning methods involving IMUs. Our\nopen-source implementation is available at\nhttps://github.com/mbrossar/denoise-imu-gyro.\n

The aim of this paper is to present a fully integrated solution for synchronous motor control. The implemented controller is based on Actel Fusion field-programmable gate array (FPGA). The objective of this paper is to evaluate the ability of the proposed fully integrated solution to ensure all the required performances in such applications, particularly in terms of control quality and time/area performances. To this purpose, a current control algorithm of a permanent-magnet synchronous machine has been implemented. This machine is associated with a resolver position sensor. In addition to the current control closed loop, all the necessary motor control tasks are implemented in the same device. The analog-to-digital conversion is ensured by the integrated analog-to-digital converter (ADC), avoiding the use of external converters. The resolver processing unit, which computes the rotor position and speed from the resolver signals, is implemented in the FPGA matrix, avoiding the use of external resolver-to-digital converter (RDC). The sine patterns used for the Park transformation are stored in the integrated flash memory blocks.

Abstract The compact Earth system model OSCARv2.2 is used to assess the climate impact of present and future civil aviation carbon dioxide (CO 2 ) emissions. The impact of aviation CO 2 on future climate is quantified over the 1940–2050 period, extending some simulations to 2100 and using different aviation CO 2 emission scenarios and two background Representative Concentrations Pathways (RCP2.6 and RCP6.0) for other emission sectors. Several aviation scenarios including weak to strong mitigation options are considered with emissions ranging from 386 MtCO 2 /year (Factor 2 scenario) to 2338 MtCO 2 /year (ICAO based scenario) in 2050. As a reference, in 2000, the calculated impact of aviation CO 2 emissions is 9.1 ± 2 mK (0.8% of the total anthropogenic warming associated to fossil fuel emissions). In 2050, on a climate trajectory in line with the Paris Agreement limiting the global warming below 2 °C (RCP2.6), the impact of the aviation CO 2 emissions ranges from 26 ± 2 mK (1.4% of the total anthropogenic warming associated to fossil fuel emissions) for an ambitious mitigation strategy scenario (Factor 2) to 39 ± 4 mK (2.0% of the total anthropogenic warming associated to fossil fuel emissions) for the least ambitious mitigation scenario of the study (ICAO based). On the longer term, if no significant emission mitigation is implemented for the aviation sector, the associated warming could further increase and reach a value of 99.5 mK ± 20 mK in 2100 (ICAO based), which corresponds to 5.2% of the total anthropogenic warming under RCP2.6. The contribution of CO 2 is estimated to represent 36%–51% of the total aviation radiative forcing of climate including short-term climate forcers. However, due to its long residence time in the atmosphere, aviation CO 2 will have a major contribution on decadal time scales. These additional short-terms forcers are subject to large uncertainties and will be analysed in forthcoming studies.

Abstract The increasing need to demonstrate the correctness of computer simulations has highlighted the importance of benchmarks. We define in this paper a representative simulation case to study low-temperature partially-magnetized plasmas. Seven independently developed particle-in-cell codes have simulated this benchmark case, with the same specified conditions. The characteristics of the codes used, such as implementation details or computing times and resources, are given. First, we compare at steady-state the time-averaged axial profiles of three main discharge parameters (axial electric field, ion density and electron temperature). We show that the results obtained exhibit a very good agreement within 5% between all the codes. As <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mi mathvariant="bold-italic">E</mml:mi> <mml:mo>×</mml:mo> <mml:mi mathvariant="bold-italic">B</mml:mi> </mml:math> discharges are known to cause instabilities propagating in the direction of electron drift, an analysis of these instabilities is then performed and a similar behaviour is retrieved between all the codes. A particular attention has been paid to the numerical convergence by varying the number of macroparticles per cell and we show that the chosen benchmark case displays a good convergence. Detailed outputs are given in the supplementary data, to be used by other similar codes in the perspective of code verification.

Whereas the world inertial navigation community was wondering, for decades, if FOG would ultimately replace RLG, Safran is demonstrating with its HRG that technology prospective is not such an easy game. With its HRG, Safran is proving that the HRG innovative approach is a real game changer in high end navigation. This paper sums up the overall principles of HRG, how it works and its intrinsic properties. Current applications of HRG are described to illustrate how HRG benefits are capitalized in valued-added products. More prospective aspects of the HRG are also addressed with the latest tests results of performance limits exploration.

Context. The LOw Frequency ARray (LOFAR) radio telescope is a giant digital phased array interferometer with multiple antennas distributed in Europe. It provides discrete sets of Fourier components of the sky brightness. Recovering the original brightness distribution with aperture synthesis forms an inverse problem that can be solved by various deconvolution and minimization methods.

This paper investigates a damping strategy for integrally bladed disks (blisks) based on the use of friction rings. The steady-state forced response of the blisk with friction rings is derived using the so-called dynamic Lagrangian frequency-time method adapted to cyclic structures with rotating excitations. In addition, an original approach for optimal determination of the number of Fourier harmonics is proposed. In numerical applications, a representative compressor blisk featuring several rings is considered. Each substructure is modeled using finite-elements and a reduced-order modeling technique is used for the blisk. The efficiency of this damping technology is investigated, and friction dissipation phenomena are interpreted with respect to frequency responses. It is shown that the friction damping effectiveness depends mainly on the level of dynamic coupling between blades and disk, and on whether the dynamics features significant alternating stick/slip phases. Through parameter studies, design guidelines are also proposed.

In many continuous combustion processes the flame is stabilized by swirling the injected flow. This is the case for example in aeroengine combustors or in gas turbines where aerodynamic injectors impart a rotating component to the flow to create a central recirculation zone which anchors the flame. Swirling flame dynamics is of technical interest and also gives rise to interesting scientific issues. Some of the recent progress in this field will be reviewed. It is first shown that the swirler response to incident acoustic perturbations generates a vorticity wave which is convected by the flow. A result of this process is that the swirl number fluctuates. It is then shown that the flame response is defined by a combination of heat release rate fluctuations induced by the incoming acoustic and convective perturbations. This is confirmed by experimental measurements and by large eddy simulations of the reactive flow. Measured flame describing functions (FDFs) are then used to characterize the nonlinear response of swirling flames to incident perturbations and determine the regimes of instability of a generic system comprising an upstream manifold, an injector equipped with a swirler and a combustion chamber confining the flame. The last part of this article is concerned with interactions of the precessing vortex core (PVC) with incoming acoustic perturbations. The PVC is formed at high swirl number and this hydrodynamic helical instability gives rise to some interesting nonlinear interactions between the acoustic frequency, the PVC frequency and their difference frequency.

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Common-mode (CM) choke saturation is a practical problem in CM filter applications. It is generally believed that the leakage inductance of CM chokes makes the core saturated. This paper analyzes two new mechanisms for CM choke saturation due to CM voltage, and these mechanisms are verified in experiment. CM choke saturation is particularly important for motor drive systems, which have a high CM voltage and comparably higher stray grounding capacitance. A model is established to describe the relationship between the CM voltage and the volume of the CM magnetic components. According to the analysis, line impedance stabilization networks (LISNs) play an important role in the design of CM magnetic components. </para>

Abstract In this paper we propose a representative simulation test-case of E × B discharges accounting for plasma wall interactions with the presence of both the electron cyclotron drift instability and the modified-two-stream-instability. Seven independently developed particle-in-cell (PIC) codes have simulated this benchmark case, with the same specified conditions. The characteristics of the different codes and computing times are given. Results show that both instabilities were captured in a similar fashion and good agreement between the different PIC codes is reported as main plasma parameters were closely related within a 5% interval. The number of macroparticles per cell was also varied and statistical convergence was reached. Detailed outputs are given in the supplementary data, to be used by other similar groups in the perspective of code verification.

Abstract In this paper, we propose a general framework for projection-based model order reduction assisted by deep neural networks. The proposed methodology, called ROM-net , consists in using deep learning techniques to adapt the reduced-order model to a stochastic input tensor whose nonparametrized variabilities strongly influence the quantities of interest for a given physics problem. In particular, we introduce the concept of dictionary-based ROM-nets , where deep neural networks recommend a suitable local reduced-order model from a dictionary. The dictionary of local reduced-order models is constructed from a clustering of simplified simulations enabling the identification of the subspaces in which the solutions evolve for different input tensors. The training examples are represented by points on a Grassmann manifold, on which distances are computed for clustering. This methodology is applied to an anisothermal elastoplastic problem in structural mechanics, where the damage field depends on a random temperature field. When using deep neural networks, the selection of the best reduced-order model for a given thermal loading is 60 times faster than when following the clustering procedure used in the training phase.

Annular combustors may give rise to various types of combustion instabilities. Some of the resulting oscillations coupled by transverse acoustic modes are commonly observed in practice and their suppression or reduction is an important issue which needs to be considered. The present study is carried out in a system comprising an annular plenum feeding 16 swirling injectors confined by two cylindrical quartz tubes opened to the atmosphere. Calculations based on a Helmholtz solver provide a suitable estimate of frequencies observed experimentally and reveal the modal structure corresponding to the longitudinal and transverse oscillations. High speed images obtained under reactive conditions are then processed to extract the structure of heat release rate perturbations and match this structure with that of the coupling acoustic mode. It is found that the transverse instability is coupled by a first azimuthal mode which is characterized by a time varying spin ratio. This index gives the respective levels of rotating components in the azimuthal mode. Another instability arising at a lower frequency is coupled by a longitudinal acoustic mode giving rise to high-amplitude oscillations in heat release rate in which most of the flames (but not all) are synchronized and in phase with the pressure perturbation.

ABSTRACT The RemoveDEBRIS mission has been the first mission to successfully demonstrate, in-orbit, a series of technologies that can be used for the active removal of space debris. The mission started late in 2014 and was sponsored by a grant from the EC that saw a consortium led by the Surrey Space Centre to develop the mission, from concept to in-orbit demonstrations, that terminated in March 2019. Technologies for the capture of large space debris, like a net and a harpoon, have been successfully tested together with hardware and software to retrieve data on non-cooperative target debris kinematics from observations carried out with on board cameras. The final demonstration consisted of the deployment of a drag-sail to increase the drag of the satellite to accelerate its demise.

Short carbon fiber-reinforced Polyamide 12 composite materials were prepared and used as filaments for additive manufacturing (AM) of structures using the Fused Filament Fabrication (FFF) method. The effect of carbon fibers concentration and type, infill pattern and environmental temperatures on mechanical properties of the printed test samples were investigated. The measured tensile modulus of the printed composite ranged from 1.4 to 8.8 GPa, an increase of up to 6.3 times the value of the neat printed polymer. The tensile strength ranged from 40 to 90 MPa, for an increase of up to 2.15 times. Optimization of the environmental temperature for improved coalescence of filaments led to a fair increase in values of the tensile modulus and strength, with an improvement up to 1.5 and 2 times, respectively, for the printed samples with pattern orthogonal to the loading directions. Microstructure characterizations were performed for mechanical results interpretations, with the help of a specialized homogenization model. The combination of FFF and carbon fiber-reinforced composite shows high promises for applications in the transportation industry.

Lower-limb exoskeletons have shown increasing potential to augment human performance in many locomotion tasks. However, most lower-limb exoskeletons use highly geared, nonback-drivable actuators with limited power and force bandwidth in order to be light enough to be carried without metabolic penalty. Moreover, they rely on controllers that depend on past motion history to assist the user, which limits the multifunctional capabilities of exoskeletons. Here, we study the potential of delocalized magnetorheological (MR) clutches to provide transparent but yet powerful multifunctional exoskeleton assistance. A single high-speed, lightweight motor is coupled with two MR clutches that modulate the plantar-flexion torque at each ankle. The exoskeleton is controlled by a state map controller that can assist users in real time while walking, jumping, and landing. Results confirm the potential of the MR actuation approach by demonstrating instantaneous adaptation to transient walking and by producing a maximal torque of 90 N·m per ankle with a total power of 1.4 kW when jumping. The system also actively braked landing impact and achieved multifunctional assistance in a sequence of walking, jumping, and landing. With a total mass of 6.2 kg including 0.9 kg on each leg, the system reduces metabolic cost of walking by 5.6% on average with tethered electronics and power supply.

Increasingly stringent regulations and the need to tackle rising fuel prices have placed great emphasis on the design of aeronautical gas turbines, which are unfortunately more and more prone to combustion instabilities. In the particular field of annular combustion chambers, these instabilities often take the form of azimuthal modes. To predict these modes, one must compute the full combustion chamber, which remained out of reach until very recently and the development of massively parallel computers. In this article, full annular Large Eddy Simulations (LES) of two helicopter combustors, which differ only on the swirlers' design, are performed. In both computations, LES captures self-established rotating azimuthal modes. However, the two cases exhibit different thermo-acoustic responses and the resulting limit-cycles are different. With the first design, a self-excited strong instability develops, leading to pulsating flames and local flashback. In the second case, the flames are much less affected by the azimuthal mode and remain stable, allowing an acceptable operation. Hence, this study highlights the potential of LES for discriminating injection system designs.