Hybrid model-based and data-driven wind velocity estimator for an autonomous robotic airship
Apolo Silva Marton, André Ricardo Fioravanti, José Raul Azinheira, Ely Carneiro de Paiva
ARTIGO
Inglês
Agradecimentos: The present work was sponsored by the Brazilian agencies CNPq and FAPESP, through Projects DRONI (CNPq 402112/2013-0), INCT-SAC (CNPq 465755 /2014-3; FAPESP 2014/50851-0) and scholarships (CNPq 305 600/2017-6; FAPESP BEP 2017/11423-0). Also, this work was supported by Fundação para a...
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Agradecimentos: The present work was sponsored by the Brazilian agencies CNPq and FAPESP, through Projects DRONI (CNPq 402112/2013-0), INCT-SAC (CNPq 465755 /2014-3; FAPESP 2014/50851-0) and scholarships (CNPq 305 600/2017-6; FAPESP BEP 2017/11423-0). Also, this work was supported by Fundação para a Ciência e a Tecnologia (FCT), through IDMEC, under LAETA, project UID/EMS/ 50022/2013 (Portugal). Moreover, the authors are grateful to Erasmus Mundus SMART2 for the financial support through project reference 552042-EM-1-2014-1-FR-ERA MUNDUS-EMA2. Furthermore, the authors appreciate all the support given by members of the Advanced Computing, Control & Embedded Systems Laboratory (ACCES-Lab) and Laboratory of Study in Exterior Vehicles (LEVE) from University of Campinas
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In the context of autonomous airships, several works in control and guidance use wind velocity to design a control law. However, in general, this information is not directly measured in robotic airships. This paper presents three alternative versions for estimation of wind velocity. Firstly, an...
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In the context of autonomous airships, several works in control and guidance use wind velocity to design a control law. However, in general, this information is not directly measured in robotic airships. This paper presents three alternative versions for estimation of wind velocity. Firstly, an extended Kalman Filter is designed as a model-based approach. Then, a Neural Network is designed as a data-driven approach. Finally, a hybrid estimator is proposed by performing a fusion between the previous designed estimators: model-based and data-driven. All approaches consider only global positioning system, inertial measurement unit and a one-dimensional Pitot tube as available sensors. Simulations in a realistic nonlinear model of the airship suggest that the cooperation between these two techniques increases the estimation performance
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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ
402112/2013-0; 465755/2014-3; 305600/2017-6
FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP
2014/50851-0; 2017/11423-0
Fechado
Hybrid model-based and data-driven wind velocity estimator for an autonomous robotic airship
Apolo Silva Marton, André Ricardo Fioravanti, José Raul Azinheira, Ely Carneiro de Paiva
Hybrid model-based and data-driven wind velocity estimator for an autonomous robotic airship
Apolo Silva Marton, André Ricardo Fioravanti, José Raul Azinheira, Ely Carneiro de Paiva
Fontes
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Journal of the Brazilian Society of Mechanical Sciences and Engineering Vol. 42, no. 3 (Mar., 2020) |