A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking

Autores
Guevara Bermeo, Bryan Stefano; Recalde, Luis F.; Varela Aldás, José; Andaluz Ortiz, Victor Hugo; Gandolfo, Daniel; Toibero, Juan Marcos
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Transport, rescue, search, surveillance, and disaster relief tasks are some applications that can be developed with unmanned aerial vehicles (UAVs), where accurate trajectory tracking is a crucial property to operate in a cluttered environment or under uncertainties. However, this is challenging due to high nonlinear dynamics, system constraints, and uncertainties presented in cluttered environments. Hence, uncertainties in the form of unmodeled dynamics, aerodynamic effects, and external disturbances such as wind can produce unstable feedback control schemes, introducing significant positional tracking errors. This work presents a detailed comparative study between controllers such as nonlinear model predictive control (NMPC) and non-predictive baseline feedback controllers, with particular attention to tracking accuracy and computational efficiency. The development of the non-predictive feedback controller schemes was divided into inverse differential kinematics and inverse dynamic compensation of the aerial vehicle. The design of the two controllers uses the mathematical model of UAV and nonlinear control theory, guaranteeing a low computational cost and an asymptotically stable algorithm. The NMPC formulation was developed considering system constraints, where the simplified dynamic model was included; additionally, the boundaries in control actions and a candidate Lyapunov function guarantees the stability of the control structure. Finally, this work uses the commercial simulator DJI brand and DJI Matrice 100 UAV in real-world experiments, where the NMPC shows a reduction in tracking error, indicating the advantages of this formulation.
Fil: Guevara Bermeo, Bryan Stefano. Universidad Nacional de San Juan; Argentina. Universidad Tecnologica Indoamerica.; Ecuador
Fil: Recalde, Luis F.. Universidad Nacional de San Juan; Argentina. Universidad Tecnologica Indoamerica.; Ecuador
Fil: Varela Aldás, José. Universidad Tecnologica Indoamerica.; Ecuador
Fil: Andaluz Ortiz, Victor Hugo. Universidad de Las Fuerzas Armadas; Ecuador. Universidad Tecnologica Indoamerica.; Ecuador
Fil: Gandolfo, Daniel. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Toibero, Juan Marcos. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
Materia
NONLINEAR CONTROL
OPTIMAL CONTROL
QUADROTOR UAV
TRAJECTORY TRACKING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/218976
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/218976
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory trackingGuevara Bermeo, Bryan StefanoRecalde, Luis F.Varela Aldás, JoséAndaluz Ortiz, Victor HugoGandolfo, DanielToibero, Juan MarcosNONLINEAR CONTROLOPTIMAL CONTROLQUADROTOR UAVTRAJECTORY TRACKINGhttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Transport, rescue, search, surveillance, and disaster relief tasks are some applications that can be developed with unmanned aerial vehicles (UAVs), where accurate trajectory tracking is a crucial property to operate in a cluttered environment or under uncertainties. However, this is challenging due to high nonlinear dynamics, system constraints, and uncertainties presented in cluttered environments. Hence, uncertainties in the form of unmodeled dynamics, aerodynamic effects, and external disturbances such as wind can produce unstable feedback control schemes, introducing significant positional tracking errors. This work presents a detailed comparative study between controllers such as nonlinear model predictive control (NMPC) and non-predictive baseline feedback controllers, with particular attention to tracking accuracy and computational efficiency. The development of the non-predictive feedback controller schemes was divided into inverse differential kinematics and inverse dynamic compensation of the aerial vehicle. The design of the two controllers uses the mathematical model of UAV and nonlinear control theory, guaranteeing a low computational cost and an asymptotically stable algorithm. The NMPC formulation was developed considering system constraints, where the simplified dynamic model was included; additionally, the boundaries in control actions and a candidate Lyapunov function guarantees the stability of the control structure. Finally, this work uses the commercial simulator DJI brand and DJI Matrice 100 UAV in real-world experiments, where the NMPC shows a reduction in tracking error, indicating the advantages of this formulation.Fil: Guevara Bermeo, Bryan Stefano. Universidad Nacional de San Juan; Argentina. Universidad Tecnologica Indoamerica.; EcuadorFil: Recalde, Luis F.. Universidad Nacional de San Juan; Argentina. Universidad Tecnologica Indoamerica.; EcuadorFil: Varela Aldás, José. Universidad Tecnologica Indoamerica.; EcuadorFil: Andaluz Ortiz, Victor Hugo. Universidad de Las Fuerzas Armadas; Ecuador. Universidad Tecnologica Indoamerica.; EcuadorFil: Gandolfo, Daniel. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Toibero, Juan Marcos. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaMultidisciplinary Digital Publishing Institute2023-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/218976Guevara Bermeo, Bryan Stefano; Recalde, Luis F.; Varela Aldás, José; Andaluz Ortiz, Victor Hugo; Gandolfo, Daniel; et al.; A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking; Multidisciplinary Digital Publishing Institute; Drones; 7; 2; 2-2023; 1-232504-446XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2504-446X/7/2/144info:eu-repo/semantics/altIdentifier/doi/10.3390/drones7020144info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:20:40Zoai:ri.conicet.gov.ar:11336/218976instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:20:40.503CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking
title A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking
spellingShingle A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking
Guevara Bermeo, Bryan Stefano
NONLINEAR CONTROL
OPTIMAL CONTROL
QUADROTOR UAV
TRAJECTORY TRACKING
title_short A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking
title_full A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking
title_fullStr A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking
title_full_unstemmed A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking
title_sort A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking
dc.creator.none.fl_str_mv Guevara Bermeo, Bryan Stefano
Recalde, Luis F.
Varela Aldás, José
Andaluz Ortiz, Victor Hugo
Gandolfo, Daniel
Toibero, Juan Marcos
author Guevara Bermeo, Bryan Stefano
author_facet Guevara Bermeo, Bryan Stefano
Recalde, Luis F.
Varela Aldás, José
Andaluz Ortiz, Victor Hugo
Gandolfo, Daniel
Toibero, Juan Marcos
author_role author
author2 Recalde, Luis F.
Varela Aldás, José
Andaluz Ortiz, Victor Hugo
Gandolfo, Daniel
Toibero, Juan Marcos
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv NONLINEAR CONTROL
OPTIMAL CONTROL
QUADROTOR UAV
TRAJECTORY TRACKING
topic NONLINEAR CONTROL
OPTIMAL CONTROL
QUADROTOR UAV
TRAJECTORY TRACKING
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Transport, rescue, search, surveillance, and disaster relief tasks are some applications that can be developed with unmanned aerial vehicles (UAVs), where accurate trajectory tracking is a crucial property to operate in a cluttered environment or under uncertainties. However, this is challenging due to high nonlinear dynamics, system constraints, and uncertainties presented in cluttered environments. Hence, uncertainties in the form of unmodeled dynamics, aerodynamic effects, and external disturbances such as wind can produce unstable feedback control schemes, introducing significant positional tracking errors. This work presents a detailed comparative study between controllers such as nonlinear model predictive control (NMPC) and non-predictive baseline feedback controllers, with particular attention to tracking accuracy and computational efficiency. The development of the non-predictive feedback controller schemes was divided into inverse differential kinematics and inverse dynamic compensation of the aerial vehicle. The design of the two controllers uses the mathematical model of UAV and nonlinear control theory, guaranteeing a low computational cost and an asymptotically stable algorithm. The NMPC formulation was developed considering system constraints, where the simplified dynamic model was included; additionally, the boundaries in control actions and a candidate Lyapunov function guarantees the stability of the control structure. Finally, this work uses the commercial simulator DJI brand and DJI Matrice 100 UAV in real-world experiments, where the NMPC shows a reduction in tracking error, indicating the advantages of this formulation.
Fil: Guevara Bermeo, Bryan Stefano. Universidad Nacional de San Juan; Argentina. Universidad Tecnologica Indoamerica.; Ecuador
Fil: Recalde, Luis F.. Universidad Nacional de San Juan; Argentina. Universidad Tecnologica Indoamerica.; Ecuador
Fil: Varela Aldás, José. Universidad Tecnologica Indoamerica.; Ecuador
Fil: Andaluz Ortiz, Victor Hugo. Universidad de Las Fuerzas Armadas; Ecuador. Universidad Tecnologica Indoamerica.; Ecuador
Fil: Gandolfo, Daniel. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
Fil: Toibero, Juan Marcos. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentina
description Transport, rescue, search, surveillance, and disaster relief tasks are some applications that can be developed with unmanned aerial vehicles (UAVs), where accurate trajectory tracking is a crucial property to operate in a cluttered environment or under uncertainties. However, this is challenging due to high nonlinear dynamics, system constraints, and uncertainties presented in cluttered environments. Hence, uncertainties in the form of unmodeled dynamics, aerodynamic effects, and external disturbances such as wind can produce unstable feedback control schemes, introducing significant positional tracking errors. This work presents a detailed comparative study between controllers such as nonlinear model predictive control (NMPC) and non-predictive baseline feedback controllers, with particular attention to tracking accuracy and computational efficiency. The development of the non-predictive feedback controller schemes was divided into inverse differential kinematics and inverse dynamic compensation of the aerial vehicle. The design of the two controllers uses the mathematical model of UAV and nonlinear control theory, guaranteeing a low computational cost and an asymptotically stable algorithm. The NMPC formulation was developed considering system constraints, where the simplified dynamic model was included; additionally, the boundaries in control actions and a candidate Lyapunov function guarantees the stability of the control structure. Finally, this work uses the commercial simulator DJI brand and DJI Matrice 100 UAV in real-world experiments, where the NMPC shows a reduction in tracking error, indicating the advantages of this formulation.
publishDate 2023
dc.date.none.fl_str_mv 2023-02
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/218976
Guevara Bermeo, Bryan Stefano; Recalde, Luis F.; Varela Aldás, José; Andaluz Ortiz, Victor Hugo; Gandolfo, Daniel; et al.; A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking; Multidisciplinary Digital Publishing Institute; Drones; 7; 2; 2-2023; 1-23
2504-446X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/218976
identifier_str_mv Guevara Bermeo, Bryan Stefano; Recalde, Luis F.; Varela Aldás, José; Andaluz Ortiz, Victor Hugo; Gandolfo, Daniel; et al.; A comparative study between NMPC and Baseline Feedback Controllers for UAV trajectory tracking; Multidisciplinary Digital Publishing Institute; Drones; 7; 2; 2-2023; 1-23
2504-446X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/2504-446X/7/2/144
info:eu-repo/semantics/altIdentifier/doi/10.3390/drones7020144
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842981130174726144
score 12.48226

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