Adaptive nonlinear guidance law using neural networks applied to a quadrotor

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/174157

dc.contributor	Universitat Politècnica de Catalunya. Doctorat en Automàtica, Robòtica i Visió
dc.contributor	Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.author	Rubí Perelló, Bartomeu
dc.contributor.author	Morcego Seix, Bernardo
dc.contributor.author	Pérez Magrané, Ramon
dc.date	2019
dc.identifier.citation	Rubi, B.; Morcego, B.; Perez, R. Adaptive nonlinear guidance law using neural networks applied to a quadrotor. A: IEEE International Conference on Control and Automation. "Proceedings of the IEEE 15th International Conference on Control and Automation". 2019, p. 1626-1631.
dc.identifier.citation	https://www.researchgate.net/publication/334604765_Adaptive_Nonlinear_Guidance_Law_Using_Neural_Networks_Applied_to_a_Quadrotor
dc.identifier.citation	10.1109/icca.2019.8899601
dc.identifier.uri	http://hdl.handle.net/2117/174157
dc.language.iso	eng
dc.relation	https://ieeexplore.ieee.org/abstract/document/8899601
dc.relation	info:eu-repo/grantAgreement/ES/2PE/DPI2017-88403-R
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject	Àrees temàtiques de la UPC::Informàtica::Robòtica
dc.subject	Adaptive control systems
dc.subject	Robotics
dc.subject	Drone aircraft
dc.subject	Automated guided vehicles
dc.subject	Adaptive control
dc.subject	Intelligent and AI based control
dc.subject	Sistemes adaptatius
dc.subject	Avions no tripulats
dc.subject	Robòtica
dc.title	Adaptive nonlinear guidance law using neural networks applied to a quadrotor
dc.type	info:eu-repo/semantics/submittedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	© 2019IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstract	The NonLinear Guidance Law (NLGL) is a geometric algorithm commonly employed to solve the path following problem on different unmanned vehicles. NLGL is simple (does no depend on the model of the vehicle), effective and has only one tunning parameter. Its control parameter (L) depends on various factors, such as the velocity of the vehicle, the shape of the reference path and the dynamics of the vehicle. This paper analyses the effect of parameter L on the performance of NLGL when it is applied to a quadrotor vehicle. An Adaptive NLGL, which includes a velocity reduction term, is proposed. Stability proofs are given. Simulation results show that the proposed algorithm enhances the performance of the standard NLGL. Furthermore, it has no parameters to tune.
dc.description.abstract	Peer Reviewed

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