Commande rÃ©siliente et backstepping adaptatif des systÃ¨mes Quasi ...

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Figure 1: Drone Quadrotor développé au CReSTICProfil du candidat :Le candidat devra posséder des connaissances en Automatique et/ou MathématiquesAppliquées ainsi qu’avoir des compétences sur la synthèse de lois de commande linéaire etnon-linéaire. Des connaissances sur les modèles LPV ou Quasi-LPV et/ou l’élaboration decommande à partir de fonction de Lyapunov assignables pourront constituer un plus.Démarche de candidature :- Le recrutement est effectué sur concours. L’inscription au concours doit êtreeffectuée à partir du site internet de l’école doctorale de Reims (date limite 27/05/13):https://www.adum.fr/as/ed/proposition.pl?site=sts358en cliquant sur le sujet « CoRéBaF – Commande Résiliente et Backstepping dessystèmes Flous » et en suivant la procédure indiquée.- En plus de cette inscription, le dossier constitué d’un CV, d’une lettre de motivationainsi que des notes de Master / Ecole d’ingénieurs sont à envoyer obligatoirement àkevin.guelton@univ-reims.fr et laurent.arcese@univ-reims.fr.Financement :Bourse Ministère ou Bourse Région (pas de distinction entre supports ministériels et régionau niveau de l’URCA, environ 1400€ net/mois)Laboratoire d’accueil et contacts :Kevin Guelton, kevin.guelton@univ-reims.fr, 03 26 91 32 61Laurent Arcese, laurent.arcese@univ-reims.fr, 03 26 91 31 93CReSTICUFR Sciences Exactes et NaturellesMoulin de la Housse - BP103951687 Reims Cedex 22
Resilient and adaptive backstepping control of Quasi-LPV systemsApplication to a quadrotor UAVThis project of three years takes place within the framework of the work in the automaticteam from the CReSTIC on continuous control of nonlinear systems. The development ofrobust and fault-tolerant control is currently an active research area since the systemsbecome more and more complex and difficult to model precisely.The goal of this project is to propose innovative theoretical solutions related to the synthesisof resilient controllers to stabilize non-linear systems described by Quasi-LPV multi-model(Takagi-Sugeno). The advantage of this approach is to extend some theories of linear controlto the control of non-linear system. To date, few techniques devoted to the synthesis ofresilient controllers for Quasi-LPV systems have been proposed, that is to say, sensitive touncertainties on the control (information loss, sensor fault and actuators, numericalapproximations). The challenge is therefore to extend the concepts of linear resilientcontrollers to the case of non-linear systems described by Quasi-LPV systems.In addition, combined with robust approaches, resilient control would propose an alternativeapproach to conventional techniques for reconfiguration of the fault-tolerant control of nonlinearsystems. Thus, we propose to study and to use two techniques to achieve these goals:- synthesis of robust control laws (based on LMI),- finding Lyapunov functions (from an adaptive backstepping approach) for estimatingunknown parameters.From a technical point of view, the objective is to provide a Matlab toolbox that will enable, ina systematic way, for potential users and non-specialists of convex optimization to applythese tools to the synthesis of control laws for a wide generic class of physical and/orindustrial systems described by Quasi-LPV models.From an application point of view, we propose to validate these theoretical approaches to thecontrol of a quadrotor UAV developed in the automatic team. Indeed, resilience is expectedto ensure the safety of the system in real time, in the presence of loss of information betweenthe base control and the drone itself, power loss, engine failures, parametric drifts, etc…Figure 1: Quadrotor UAV3
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