Adaptive Neural Network Nonlinear Control Of A Flexible Robot Manipulator / Imane Touhami

Public ISBD Titre : Adaptive Neural Network Nonlinear Control Of A Flexible Robot Manipulator Type de document : texte manuscrit Auteurs : Imane Touhami, Auteur ; Fatima Bensayeh, Auteur ; Mohamed Belkheiri, Directeur de thèse Editeur : Laghouat : Université Amar Telidji - Département d'électronique Année de publication : 2020 Importance : 55p. Accompagnement : +1 CD ROM Optique Némérique Note générale : Option: Control Systems And Industrial Computing Langues : Anglais Mots-clés : flexible robot, benchmark, feedback linearisation, neural networks Résumé : In this project, we present the design of an adaptive output feedback control methodology for the flexible robot benchmark problem. Its model is presented with some proposed solutions for the uncertainties due to unmodeled dynamics and parameteric uncertainties/ Our objective is to design a controller that forces the system output (the angular joint positions) to track a smooth reference trajectory with bounded errors. The proposed method is based on a feedback linearization controller associated to a feed-forward neural network and it has proven to be a very effective way to design controllers based on approximate knowledge of the system dynamics. note de thèses : Memoire de Master en Electronique Adaptive Neural Network Nonlinear Control Of A Flexible Robot Manipulator [texte manuscrit] / Imane Touhami, Auteur ; Fatima Bensayeh, Auteur ; Mohamed Belkheiri, Directeur de thèse . - Laghouat : Université Amar Telidji - Département d'électronique, 2020 . - 55p. + +1 CD ROM Optique Némérique. Option: Control Systems And Industrial Computing Langues : Anglais Mots-clés : flexible robot, benchmark, feedback linearisation, neural networks Résumé : In this project, we present the design of an adaptive output feedback control methodology for the flexible robot benchmark problem. Its model is presented with some proposed solutions for the uncertainties due to unmodeled dynamics and parameteric uncertainties/ Our objective is to design a controller that forces the system output (the angular joint positions) to track a smooth reference trajectory with bounded errors. The proposed method is based on a feedback linearization controller associated to a feed-forward neural network and it has proven to be a very effective way to design controllers based on approximate knowledge of the system dynamics. note de thèses : Memoire de Master en Electronique

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
the 09-69	the 09-69	Thése	BIBLIOTHEQUE DE FACULTE DE TECHNOLOGIE	Genie electrique (TEC)	Disponible

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