Formation flight of UAV\'s with obstacle avoidance
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da USP |
Texto Completo: | https://www.teses.usp.br/teses/disponiveis/18/18161/tde-13102022-092006/ |
Resumo: | This thesis presents a control methodology to address the problem of formation flight of autonomous aircraft with a control system capable of avoiding obstacles. A literature review was performed to explore some of the essential fields needed to implement a control system that can solve this problem. The main configurations of formations of autonomous vehicles were studied, as well as the principal control techniques available in the literature, and applied to formation flight. The sensors for UAV navigation and sensors for obstacle identification were also studied. Eventually, some results obtained from the literature were presented, which show benefits coming from formation flight, like induced drag reduction for the aircraft set. Also, some formation geometries like V formation, Echelon, Chevron, and inverted V were studied. A quadrotor model was developed, which is used as the standard model for aircraft formation. The theory used to perform model predictive control is also presented, as well as the technique used to track the desired planned trajectory. Moreover, it is described how the sensors, disturbance, and noise were simulated, as well as the techniques and modifications implemented in the control methodology to perform obstacle avoidance, make use of soft constraints, and improve algorithm runtime. Eventually, it is presented the simulation results using the quadrotor model previously developed. In these simulations, the aircraft perform formation flight in an obstacle-laden environment. The simulations included disturbance and noise effects as well as other real-world issues. The main contribution of this work is the establishment of a new controller design methodology using the MPC technique applied to the formation flight with obstacle avoidance problem. Such that the nonlinear aircraft model as well as the uncertainty, noise, disturbance, and other problems, which occur during an aircraft\'s mission are taken into account. |
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Formation flight of UAV\'s with obstacle avoidanceVoo em formação de VANT\'s com desvio de obstáculosautonomous flightcontrolcontroledesvio de obstáculosdinâmica de vooflight dynamicsformation flightobstacle avoidanceUAVVANTvoo autônomovoo em formaçãoThis thesis presents a control methodology to address the problem of formation flight of autonomous aircraft with a control system capable of avoiding obstacles. A literature review was performed to explore some of the essential fields needed to implement a control system that can solve this problem. The main configurations of formations of autonomous vehicles were studied, as well as the principal control techniques available in the literature, and applied to formation flight. The sensors for UAV navigation and sensors for obstacle identification were also studied. Eventually, some results obtained from the literature were presented, which show benefits coming from formation flight, like induced drag reduction for the aircraft set. Also, some formation geometries like V formation, Echelon, Chevron, and inverted V were studied. A quadrotor model was developed, which is used as the standard model for aircraft formation. The theory used to perform model predictive control is also presented, as well as the technique used to track the desired planned trajectory. Moreover, it is described how the sensors, disturbance, and noise were simulated, as well as the techniques and modifications implemented in the control methodology to perform obstacle avoidance, make use of soft constraints, and improve algorithm runtime. Eventually, it is presented the simulation results using the quadrotor model previously developed. In these simulations, the aircraft perform formation flight in an obstacle-laden environment. The simulations included disturbance and noise effects as well as other real-world issues. The main contribution of this work is the establishment of a new controller design methodology using the MPC technique applied to the formation flight with obstacle avoidance problem. Such that the nonlinear aircraft model as well as the uncertainty, noise, disturbance, and other problems, which occur during an aircraft\'s mission are taken into account.Esta dissertação apresenta uma pesquisa a respeito de voo autônomo de aeronaves em formação, com sistema de controle capaz de efetuar desvio de obstáculos. É feita uma revisão bibliográfica que explora tópicos essenciais para se implementar um sistema de controle capaz de resolver o problema. São estudadas as principais configurações de formação de veículos autônomos, assim como as principais técnicas de controle presentes na literatura aplicadas para voo em formação. São estudados também sensores utilizados para navegação de VANT\'s assim como sensores capazes de identificar obstáculos. Por último são apresentados alguns resultados que indicam benefícios advindos do voo em formação, como a redução no arrasto induzido do conjunto das aeronaves, também são estudadas geometrias de formação como V, echelon, chevron e V invertido. Foi desenvolvido um modelo para um quadrirrotor, que é utilizado como modelo padrão das aeronaves na formação. É apresentada a teoria utilizada para implementação de controle preditivo e a técnica utilizada para se realizar o seguimento da trajetória planejada. Além disso, é descrito como os sensores, distúrbios e ruídos foram simulados, assim como as técnicas e modificações realizadas na metodologia de controle apresentada, para que seja possível realizar desvio de obstáculos, utilizar restrições flexíveis e obter um melhor desempenho computacional do algoritmo. Por fim são apresentados os resultados de simulações realizadas, se utilizando o modelo de quadrirrotor encontrado, onde as aeronaves voam em formação em regiões com obstáculos. Nas simulações é incluído o efeito de distúrbios, ruídos e outros aspectos relativos à implementação no mundo real. A principal contribuição deste trabalho é o estabelecimento de uma metodologia para projeto de controlador utilizando a técnica de controle preditivo, para o problema de voo em formação com desvio de obstáculos. De forma a se levar em consideração um modelo não linear da aeronave simulada, assim como incertezas, distúrbio, ruído e outros problemas típicos encontrados durante a missão da aeronave.Biblioteca Digitais de Teses e Dissertações da USPBelo, Eduardo MorgadoRosa, Victor Stafy Megda2022-08-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://www.teses.usp.br/teses/disponiveis/18/18161/tde-13102022-092006/reponame:Biblioteca Digital de Teses e Dissertações da USPinstname:Universidade de São Paulo (USP)instacron:USPLiberar o conteúdo para acesso público.info:eu-repo/semantics/openAccesseng2022-10-31T20:48:23Zoai:teses.usp.br:tde-13102022-092006Biblioteca Digital de Teses e Dissertaçõeshttp://www.teses.usp.br/PUBhttp://www.teses.usp.br/cgi-bin/mtd2br.plvirginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.bropendoar:27212022-10-31T20:48:23Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Formation flight of UAV\'s with obstacle avoidance Voo em formação de VANT\'s com desvio de obstáculos |
title |
Formation flight of UAV\'s with obstacle avoidance |
spellingShingle |
Formation flight of UAV\'s with obstacle avoidance Rosa, Victor Stafy Megda autonomous flight control controle desvio de obstáculos dinâmica de voo flight dynamics formation flight obstacle avoidance UAV VANT voo autônomo voo em formação |
title_short |
Formation flight of UAV\'s with obstacle avoidance |
title_full |
Formation flight of UAV\'s with obstacle avoidance |
title_fullStr |
Formation flight of UAV\'s with obstacle avoidance |
title_full_unstemmed |
Formation flight of UAV\'s with obstacle avoidance |
title_sort |
Formation flight of UAV\'s with obstacle avoidance |
author |
Rosa, Victor Stafy Megda |
author_facet |
Rosa, Victor Stafy Megda |
author_role |
author |
dc.contributor.none.fl_str_mv |
Belo, Eduardo Morgado |
dc.contributor.author.fl_str_mv |
Rosa, Victor Stafy Megda |
dc.subject.por.fl_str_mv |
autonomous flight control controle desvio de obstáculos dinâmica de voo flight dynamics formation flight obstacle avoidance UAV VANT voo autônomo voo em formação |
topic |
autonomous flight control controle desvio de obstáculos dinâmica de voo flight dynamics formation flight obstacle avoidance UAV VANT voo autônomo voo em formação |
description |
This thesis presents a control methodology to address the problem of formation flight of autonomous aircraft with a control system capable of avoiding obstacles. A literature review was performed to explore some of the essential fields needed to implement a control system that can solve this problem. The main configurations of formations of autonomous vehicles were studied, as well as the principal control techniques available in the literature, and applied to formation flight. The sensors for UAV navigation and sensors for obstacle identification were also studied. Eventually, some results obtained from the literature were presented, which show benefits coming from formation flight, like induced drag reduction for the aircraft set. Also, some formation geometries like V formation, Echelon, Chevron, and inverted V were studied. A quadrotor model was developed, which is used as the standard model for aircraft formation. The theory used to perform model predictive control is also presented, as well as the technique used to track the desired planned trajectory. Moreover, it is described how the sensors, disturbance, and noise were simulated, as well as the techniques and modifications implemented in the control methodology to perform obstacle avoidance, make use of soft constraints, and improve algorithm runtime. Eventually, it is presented the simulation results using the quadrotor model previously developed. In these simulations, the aircraft perform formation flight in an obstacle-laden environment. The simulations included disturbance and noise effects as well as other real-world issues. The main contribution of this work is the establishment of a new controller design methodology using the MPC technique applied to the formation flight with obstacle avoidance problem. Such that the nonlinear aircraft model as well as the uncertainty, noise, disturbance, and other problems, which occur during an aircraft\'s mission are taken into account. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-08-10 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://www.teses.usp.br/teses/disponiveis/18/18161/tde-13102022-092006/ |
url |
https://www.teses.usp.br/teses/disponiveis/18/18161/tde-13102022-092006/ |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
|
dc.rights.driver.fl_str_mv |
Liberar o conteúdo para acesso público. info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Liberar o conteúdo para acesso público. |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.coverage.none.fl_str_mv |
|
dc.publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
publisher.none.fl_str_mv |
Biblioteca Digitais de Teses e Dissertações da USP |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da USP instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Biblioteca Digital de Teses e Dissertações da USP |
collection |
Biblioteca Digital de Teses e Dissertações da USP |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da USP - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
virginia@if.usp.br|| atendimento@aguia.usp.br||virginia@if.usp.br |
_version_ |
1815256947690045440 |