Comparison of LMI Solvers for Robust Control of a DC-DC Boost Converter

This work deals with a robust Fault-Tolerant Control (FTC) design for a class of uncertain systems. Fault resilience is associated with a robustness bound generated by a sufficient Linear Matrix Inequality (LMI) condition for static state feedback stabilization. This design control approach is based on solving an optimization problem expressed in terms of LMI with three different programming solvers which are mincx (Matlab), lmisolver (Scilab) and cvxopt (Python). Numerical validations were carried out, first on an academic model, then on the model of a PV energy conversion system connected to a DC-DC boost converter. Then, a robustness analysis for fault resilience associated with a control law gains, obtained using the three solvers, was realized to investigate the best performance. This approach was finally validated on an experimental test bench

Computer-aided screening of autism spectrum disorder: Eye-tracking study using data visualization and deep learning

Background: The early diagnosis of autism spectrum disorder (ASD) is highly desirable but remains a challenging task, which requires a set of cognitive tests and hours of clinical examinations. In addition, variations of such symptoms exist, which can make the identification of ASD even more difficult. Although diagnosis tests are largely developed by experts, they are still subject to human bias. In this respect, computer-assisted technologies can play a key role in supporting the screening process. Objective: This paper follows on the path of using eye tracking as an integrated part of screening assessment in ASD based on the characteristic elements of the eye gaze. This study adds to the mounting efforts in using eye tracking technology to support the process of ASD screening Methods: The proposed approach basically aims to integrate eye tracking with visualization and machine learning. A group of 59 school-aged participants took part in the study. The participants were invited to watch a set of age-appropriate photographs and videos related to social cognition. Initially, eye-tracking scanpaths were transformed into a visual representation as a set of images. Subsequently, a convolutional neural network was trained to perform the image classification task. Results: The experimental results demonstrated that the visual representation could simplify the diagnostic task and also attained high accuracy. Specifically, the convolutional neural network model could achieve a promising classification accuracy. This largely suggests that visualizations could successfully encode the information of gaze motion and its underlying dynamics. Further, we explored possible correlations between the autism severity and the dynamics of eye movement based on the maximal information coefficient. The findings primarily show that the combination of eye tracking, visualization, and machine learning have strong potential in developing an objective tool to assist in the screening of ASD. Conclusions: Broadly speaking, the approach we propose could be transferable to screening for other disorders, particularly neurodevelopmental disorders

Placement de pôles robuste par retour statique de sortie

National audienc

Analyse robuste en Du-stabilité et commande par placement de pôles

Dans le cadre de cette thèse, il est question de développer des outils d'analyse et des techniques de calcul de loi de commande par retour statique d'état et de sortie. Les modèles utilisés pour décrire les comportements des systèmes sont des représentations d'état linéaires invariantes dans le temps et de dimension finie. Les modèles considérés sont sujets à des incertitudes résultant d'approximations lors de la modélisation. Les techniques d'analyse et de commande doivent tenir compte de ces incertitudes et sont alors dites robustes. Les techniques d'analyse et de commande robustes proposées dans la thèse reposent sur la notion de D-stabilite (cloisonnement des valeurs propres d'une matrice dans une région D du plan complexe) et sur la résolution de problèmes numériques souvent de type LMI.This work aims at developing tools for the computation of state or output feedback control law. The considered model are Linear Time Invariant state-space models of finite dimension. They are subject to uncertainties that can result from approximations while building the model. Techniques relevant to analysis and control have to take those uncertainties into account. All those tools, for both robust analysis and robust control, rely upon the notion of D-stability, i.e. matrix root-clustering in a subregion D of the complex plane, as well as upon numerical solutions to problems expressed in terms of LMI.POITIERS-BU Sciences (861942102) / SudocSudocFranceF

Placement de pôles robuste par retour statique de sortie

National audienc

A robust stabilization method for a saturated LPV system : application to the lateral dynamics of vehicles. * *This work was supported by the Conseil Regional de Picardie and the FEDER within the framework of the project SYSCOVI

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Sliding mode control of parallel active filters associated with multilevel space vector based controllers

International audienc

Sliding mode control of parallel active filters associated with multilevel space vector based controllers

International audienc

A robust output feedback control technique for improving vehicle lateral dynamic behavior

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