Bonjour à tous,
Je vous rappelle la journée SYNOBS qui aura lieu le 6 décembre au CNAM à Paris ! Voici le programme :
10h15 : Accueil
10h30 - 11h30 : Mira Khalil (CRAN), State estimation for enhanced low dimensional electrochemical models of lithium-ion batteries
11h30 - 12h : Ghadeer Shaaban (GIPSA), MARG Sensors-based Attitude Estimation on SO(3) Under Unknown External Acceleration
12h – 12h30 : Ruth Line Tagne Mogue (PRISME), Conception d'un observateur intervalle impulsif à gain L1 fini contre les attaques par déni de service
14h – 15h : Loic Michel (LS2N), Experimental validation of two semi-implicit homogeneous discretized differentiators on a cable-driven parallel robot
15h – 16h : Lucas Brivadis (L2S), Adaptive observer and control of spatiotemporal delayed neural fields
16h - 16h30 : Bao Tran (CAS), Kalman-like observer for linear hybrid systems
Les abstracts sont listés ci-dessous ! Pour les retardataires, n’hésitez pas à nous proposer d’autres présentations et nous essaierons de les rajouter.
A très bientôt j’espère !
Pauline
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Title : Adaptive observer and control of spatiotemporal delayed neural fields
Abstract: We propose an adaptive observer to asymptotically estimate the synaptic distribution between neurons from the online measurement of part of the neuronal activity and a delayed neural field evolution model. The convergence of the observer is ensured under a persistency of excitation condition. We show how it can be used to derive a feedback law ensuring asymptotic stabilization of the neural fields. Under additional restrictions that we will discuss, we propose a modification of the feedback law to ensure simultaneously practical stabilization of the neural fields and asymptotic convergence of the observer.
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Title: State estimation for enhanced low dimensional electrochemical models of lithium-ion batteries
Abstract: Accurate estimation of the internal states of lithium-ion batteries is key towards improving their management for safety, efficiency and longevity purposes. Various approaches exist in the literature in this context, among which designing an observer based on an electrochemical model of the battery dynamics. With this approach, the performance of the observer depends on the accuracy of the considered model. It appears that electrochemical models, and thus their associated observers, typically require to be of high dimension to generate accurate internal variables. In this work, we present a method to mitigate this limitation by correcting the lithium concentrations generated by a general class of finite-dimensional electrochemical models such that they asymptotically match those generated by the original partial differential equations (PDE) they are based on, for constant input currents. These corrections apply irrespectively of the order of the considered finite-dimensional model. The proposed correction leads to a new state space model for which we design observers, whose global, robust convergences are supported by a Lyapunov analysis. Both numerical and experimental validations are presented, which show the improvement of the accuracy of the state estimates as a result of the proposed corrections.
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Title: MARG Sensors-based Attitude Estimation on SO(3) Under Unknown External Acceleration
Abstract: In many applications, attitude estimation algorithms rely mainly on magnetic and inertial measurements from MARG sensors (a magnetometer, a gyroscope, and an accelerometer). One of the main challenges facing these algorithms is that the accelerometer measures both gravity and an unknown external acceleration, while these algorithms assume that the accelerometer measures only the gravity. In this paper, an attitude estimation algorithm on the special orthogonal group SO(3) is designed, considering the external acceleration as an unknown input with direct feedthrough to the output. The proposed algorithm is validated through Monte Carlo simulations and real datasets, demonstrating better accuracy and enhanced performance than existing solutions.
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Title : Experimental validation of two semi-implicit homogeneous discretized differentiators on a cable-driven parallel robot »
Joint work of Loïc Michel, Marceau Métillon, Stéphane Caro, Malek Ghanes, Franck Plestan, Jean-Pierre Barbot et Yannick Aoustin
Abstract : This work addresses the application of our recent results about the design of an homogeneous semi-implicit based differentiator in order to estimate the angular velocity and the angular acceleration of each motorized component of a cable-driven parallel robot. The results show that this differentiator is an extremely efficient tool for estimating the angular velocities and accelerations from the experimental measured positions, which are much less noisy than their corresponding velocity and acceleration reference signals obtained by the classical backward difference. Moreover, the estimated quantities obtained using this differentiator have been successfully compared to those obtained by a non-linear observer based on numerical interpolation of the measured position variable.
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Title : Kalman-like observer for linear hybrid systems
Abstract : We propose a hybrid Kalman-like observer for general hybrid systems with linear (time-varying) dynamics and output maps, where the solutions’ jump times are exactly known. After defining a hybrid observability Gramian and the corresponding hybrid uniform complete observability, we show that the estimate provided by this observer converges asymptotically to the system solution if this observability holds together with some boundedness and invertibility conditions along the considered system solution. Then, under additional uniformity and strictness of the forgetting factors, we show exponential
stability of the estimation error with an arbitrarily fast rate. The robust stability of this error against input disturbances and measurement noise is also studied. The results are illustrated on several benchmark examples, including switched systems, hybrid systems with discontinuous solutions, and continuous-time systems with multi-rate sporadic outputs.
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Title : Conception d'un observateur intervalle impulsif à gain L1 fini contre les attaques par déni de service
Abstract : The design of a robust observer under denial-of-service attacks is addressed for linear time invariant systems in the bounded-error framework. The cyber-attacks occur between the output of the sensors localized on the physical plantand the cyber part embedding the observer. The data required by the observer are thus available at sporadic measurement time instants. In this setting, an interval impulsive observeris synthesized. The stability analysis of the dynamics of the state estimation error is done leveraging finite-gain L1-stability theory for hybrid systems. The observer L1-gain is computed by combining interval analysis and the resolution of algebraic inequalities that greatly reduces the synthesis complexity when compared to the state-of-the-art approaches that usually rely on solving many bilinear matrix inequalities. A numerical example illustrates the approach and the performance of the designed robust observer.