Predictive Control Applied to Trajectory Tracking of Wheeled Mobile Robot

Detalhes bibliográficos
Autor(a) principal: Mariana Akeme Ogawa
Data de Publicação: 2014
Tipo de documento: Dissertação
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações da UFC
Texto Completo: http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=11933
Resumo: This work proposes a study and application of advanced controller to trajectory tracking of wheeled mobile robots. This kind of problem is a challenger for controllers once its models has two inputs and three outputs and is a non-linear model. In the literature there are various solutions to wheeled mobile robots trajectory tracking, among them the Model Predictive Control (MPC) with linearization model and a non linear control which in this work will be nominated as Klancar Controller. The Predictive Controllers can be applied efficiently in plants which has multiple inputs an multiple outputs, in situation that a future reference trajectory is known and systems with input and output constraints . However, the main disadvantage of MPC is the high computational effort which limits its practical application. Thus, this specific controller uses the plants linearization model. On the other hand, the Klancar Controller may be more efficient than the ones based on linear models, once the model is non linear. However, its solution, by definition, does not match the optimized criteria which can be a disadvantage mainly in systems that has constrains and a known future reference. Furthermore, this work proposes the application of the Predictive Control Extended Prediction Self Adaptive Control (EPSAC) to wheeled mobile robot trajectory tracking. This control strategy uses explicitly the non linear robot model, future reference, constraints on the variables and has a optimized solution. And, to the matter of this work, it has not been found reports of the EPSAC applied in mobile robotics, and is thus an unprecedented application. Simulation results are presented comparing the controllers studied using performance indices. Else, the controllers were applied in a mobile robot.
id UFC_903264ca7f5551d3e965cd350ee6340c
oai_identifier_str oai:www.teses.ufc.br:8158
network_acronym_str UFC
network_name_str Biblioteca Digital de Teses e Dissertações da UFC
spelling info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisPredictive Control Applied to Trajectory Tracking of Wheeled Mobile RobotControle preditivo aplicado ao seguimento de trajetÃria de robà mÃvel com rodas2014-04-29Bismark Claure Torrico00925127981 George Andrà Pereira ThÃ62147390372http://lattes.cnpq.br/6398510210462764Paulo Peixoto PraÃa 85869406315http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4779023P7FabrÃcio Gonzalez Nogueira8052613620000526639300Mariana Akeme OgawaUniversidade Federal do CearÃPrograma de PÃs-GraduaÃÃo em Engenharia ElÃtricaUFCBREPSAC EPSAC mobile robot Predictive Control trajectory trackingENGENHARIA ELETRICAThis work proposes a study and application of advanced controller to trajectory tracking of wheeled mobile robots. This kind of problem is a challenger for controllers once its models has two inputs and three outputs and is a non-linear model. In the literature there are various solutions to wheeled mobile robots trajectory tracking, among them the Model Predictive Control (MPC) with linearization model and a non linear control which in this work will be nominated as Klancar Controller. The Predictive Controllers can be applied efficiently in plants which has multiple inputs an multiple outputs, in situation that a future reference trajectory is known and systems with input and output constraints . However, the main disadvantage of MPC is the high computational effort which limits its practical application. Thus, this specific controller uses the plants linearization model. On the other hand, the Klancar Controller may be more efficient than the ones based on linear models, once the model is non linear. However, its solution, by definition, does not match the optimized criteria which can be a disadvantage mainly in systems that has constrains and a known future reference. Furthermore, this work proposes the application of the Predictive Control Extended Prediction Self Adaptive Control (EPSAC) to wheeled mobile robot trajectory tracking. This control strategy uses explicitly the non linear robot model, future reference, constraints on the variables and has a optimized solution. And, to the matter of this work, it has not been found reports of the EPSAC applied in mobile robotics, and is thus an unprecedented application. Simulation results are presented comparing the controllers studied using performance indices. Else, the controllers were applied in a mobile robot. Este trabalho propÃe o estudo e aplicaÃÃo de controladores avanÃados ao seguimento de trajetÃrias de robÃs mÃveis com rodas. Este tipo de problema à bastante desafiador do ponto de vista de controle uma vez que o modelo tem duas entradas e trÃs saÃdas, alÃm disso, trata-se de um modelo nÃo linear. Na literatura existem diversas soluÃÃes para o controle de trajetÃria de robÃs mÃveis, dentre eles tem-se o Controle Preditivo Baseado em Modelo (MPC) por meio de modelos linearizados e um controlador nÃo linear denominado neste trabalho de controlador de Klancar. Os controladores preditivos podem ser aplicados de forma eficiente em plantas com modelos multivariÃveis, em situaÃÃes na qual a trajetÃria futura de referÃncia à conhecida e em sistemas com restriÃÃes nas vaiÃveis de entrada e de saÃda. PorÃm, a principal desvantagem do MPC linearizado à o alto custo computacional o que limita as aplicaÃÃes prÃticas. AlÃm disso, esse controlador especÃfico utiliza um modelo linearizado da planta. Por outro lado, o controlador de Klancar pode ser mais eficiente que os baseados em modelos lineares, devido Ãs nÃo linearidades inerentes do modelo. No entanto, a sua soluÃÃo, por definiÃÃo, nÃo corresponde a critÃrios Ãtimos o que pode representar uma desvantagem principalmente em sistemas com restriÃÃes e referÃncia futura conhecida. AlÃm disso, neste trabalho à proposta a aplicaÃÃo do controle preditivo EPSAC (Extended Prediction Self Adaptive Control) para o controle de seguimento de trajetÃrias. Esta estratÃgia utiliza de forma explÃcita o modelo nÃo linear do robÃ, a referÃncia futura, as restriÃÃes nas variÃveis do robà e soluÃÃo corresponde a um critÃrio Ãtimo. Atà onde foi pesquisado pelo autor deste trabalho, nÃo existem relatos da utilizaÃÃo do EPSAC na robÃtica mÃvel, sendo desta forma uma aplicaÃÃo inÃdita. Resultados de simulaÃÃo sÃo apresentados comparando os controladores estudados, utilizando Ãndices de desempenhos. AlÃm disso, os mesmo foram implementados em um robà mÃvel.CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=11933application/pdfinfo:eu-repo/semantics/openAccessporreponame:Biblioteca Digital de Teses e Dissertações da UFCinstname:Universidade Federal do Cearáinstacron:UFC2019-01-21T11:25:14Zmail@mail.com -
dc.title.en.fl_str_mv Predictive Control Applied to Trajectory Tracking of Wheeled Mobile Robot
dc.title.alternative.pt.fl_str_mv Controle preditivo aplicado ao seguimento de trajetÃria de robà mÃvel com rodas
title Predictive Control Applied to Trajectory Tracking of Wheeled Mobile Robot
spellingShingle Predictive Control Applied to Trajectory Tracking of Wheeled Mobile Robot
Mariana Akeme Ogawa
EPSAC
EPSAC
mobile robot
Predictive Control
trajectory tracking
ENGENHARIA ELETRICA
title_short Predictive Control Applied to Trajectory Tracking of Wheeled Mobile Robot
title_full Predictive Control Applied to Trajectory Tracking of Wheeled Mobile Robot
title_fullStr Predictive Control Applied to Trajectory Tracking of Wheeled Mobile Robot
title_full_unstemmed Predictive Control Applied to Trajectory Tracking of Wheeled Mobile Robot
title_sort Predictive Control Applied to Trajectory Tracking of Wheeled Mobile Robot
author Mariana Akeme Ogawa
author_facet Mariana Akeme Ogawa
author_role author
dc.contributor.advisor1.fl_str_mv Bismark Claure Torrico
dc.contributor.advisor1ID.fl_str_mv 00925127981
dc.contributor.referee1.fl_str_mv George Andrà Pereira ThÃ
dc.contributor.referee1ID.fl_str_mv 62147390372
dc.contributor.referee1Lattes.fl_str_mv http://lattes.cnpq.br/6398510210462764
dc.contributor.referee2.fl_str_mv Paulo Peixoto PraÃa
dc.contributor.referee2ID.fl_str_mv 85869406315
dc.contributor.referee2Lattes.fl_str_mv http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4779023P7
dc.contributor.referee3.fl_str_mv FabrÃcio Gonzalez Nogueira
dc.contributor.referee3ID.fl_str_mv 80526136200
dc.contributor.authorID.fl_str_mv 00526639300
dc.contributor.author.fl_str_mv Mariana Akeme Ogawa
contributor_str_mv Bismark Claure Torrico
George Andrà Pereira ThÃ
Paulo Peixoto PraÃa
FabrÃcio Gonzalez Nogueira
dc.subject.por.fl_str_mv EPSAC
topic EPSAC
EPSAC
mobile robot
Predictive Control
trajectory tracking
ENGENHARIA ELETRICA
dc.subject.eng.fl_str_mv EPSAC
mobile robot
Predictive Control
trajectory tracking
dc.subject.cnpq.fl_str_mv ENGENHARIA ELETRICA
dc.description.sponsorship.fl_txt_mv CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior
dc.description.abstract.por.fl_txt_mv This work proposes a study and application of advanced controller to trajectory tracking of wheeled mobile robots. This kind of problem is a challenger for controllers once its models has two inputs and three outputs and is a non-linear model. In the literature there are various solutions to wheeled mobile robots trajectory tracking, among them the Model Predictive Control (MPC) with linearization model and a non linear control which in this work will be nominated as Klancar Controller. The Predictive Controllers can be applied efficiently in plants which has multiple inputs an multiple outputs, in situation that a future reference trajectory is known and systems with input and output constraints . However, the main disadvantage of MPC is the high computational effort which limits its practical application. Thus, this specific controller uses the plants linearization model. On the other hand, the Klancar Controller may be more efficient than the ones based on linear models, once the model is non linear. However, its solution, by definition, does not match the optimized criteria which can be a disadvantage mainly in systems that has constrains and a known future reference. Furthermore, this work proposes the application of the Predictive Control Extended Prediction Self Adaptive Control (EPSAC) to wheeled mobile robot trajectory tracking. This control strategy uses explicitly the non linear robot model, future reference, constraints on the variables and has a optimized solution. And, to the matter of this work, it has not been found reports of the EPSAC applied in mobile robotics, and is thus an unprecedented application. Simulation results are presented comparing the controllers studied using performance indices. Else, the controllers were applied in a mobile robot.
Este trabalho propÃe o estudo e aplicaÃÃo de controladores avanÃados ao seguimento de trajetÃrias de robÃs mÃveis com rodas. Este tipo de problema à bastante desafiador do ponto de vista de controle uma vez que o modelo tem duas entradas e trÃs saÃdas, alÃm disso, trata-se de um modelo nÃo linear. Na literatura existem diversas soluÃÃes para o controle de trajetÃria de robÃs mÃveis, dentre eles tem-se o Controle Preditivo Baseado em Modelo (MPC) por meio de modelos linearizados e um controlador nÃo linear denominado neste trabalho de controlador de Klancar. Os controladores preditivos podem ser aplicados de forma eficiente em plantas com modelos multivariÃveis, em situaÃÃes na qual a trajetÃria futura de referÃncia à conhecida e em sistemas com restriÃÃes nas vaiÃveis de entrada e de saÃda. PorÃm, a principal desvantagem do MPC linearizado à o alto custo computacional o que limita as aplicaÃÃes prÃticas. AlÃm disso, esse controlador especÃfico utiliza um modelo linearizado da planta. Por outro lado, o controlador de Klancar pode ser mais eficiente que os baseados em modelos lineares, devido Ãs nÃo linearidades inerentes do modelo. No entanto, a sua soluÃÃo, por definiÃÃo, nÃo corresponde a critÃrios Ãtimos o que pode representar uma desvantagem principalmente em sistemas com restriÃÃes e referÃncia futura conhecida. AlÃm disso, neste trabalho à proposta a aplicaÃÃo do controle preditivo EPSAC (Extended Prediction Self Adaptive Control) para o controle de seguimento de trajetÃrias. Esta estratÃgia utiliza de forma explÃcita o modelo nÃo linear do robÃ, a referÃncia futura, as restriÃÃes nas variÃveis do robà e soluÃÃo corresponde a um critÃrio Ãtimo. Atà onde foi pesquisado pelo autor deste trabalho, nÃo existem relatos da utilizaÃÃo do EPSAC na robÃtica mÃvel, sendo desta forma uma aplicaÃÃo inÃdita. Resultados de simulaÃÃo sÃo apresentados comparando os controladores estudados, utilizando Ãndices de desempenhos. AlÃm disso, os mesmo foram implementados em um robà mÃvel.
description This work proposes a study and application of advanced controller to trajectory tracking of wheeled mobile robots. This kind of problem is a challenger for controllers once its models has two inputs and three outputs and is a non-linear model. In the literature there are various solutions to wheeled mobile robots trajectory tracking, among them the Model Predictive Control (MPC) with linearization model and a non linear control which in this work will be nominated as Klancar Controller. The Predictive Controllers can be applied efficiently in plants which has multiple inputs an multiple outputs, in situation that a future reference trajectory is known and systems with input and output constraints . However, the main disadvantage of MPC is the high computational effort which limits its practical application. Thus, this specific controller uses the plants linearization model. On the other hand, the Klancar Controller may be more efficient than the ones based on linear models, once the model is non linear. However, its solution, by definition, does not match the optimized criteria which can be a disadvantage mainly in systems that has constrains and a known future reference. Furthermore, this work proposes the application of the Predictive Control Extended Prediction Self Adaptive Control (EPSAC) to wheeled mobile robot trajectory tracking. This control strategy uses explicitly the non linear robot model, future reference, constraints on the variables and has a optimized solution. And, to the matter of this work, it has not been found reports of the EPSAC applied in mobile robotics, and is thus an unprecedented application. Simulation results are presented comparing the controllers studied using performance indices. Else, the controllers were applied in a mobile robot.
publishDate 2014
dc.date.issued.fl_str_mv 2014-04-29
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
status_str publishedVersion
format masterThesis
dc.identifier.uri.fl_str_mv http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=11933
url http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=11933
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do CearÃ
dc.publisher.program.fl_str_mv Programa de PÃs-GraduaÃÃo em Engenharia ElÃtrica
dc.publisher.initials.fl_str_mv UFC
dc.publisher.country.fl_str_mv BR
publisher.none.fl_str_mv Universidade Federal do CearÃ
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações da UFC
instname:Universidade Federal do Ceará
instacron:UFC
reponame_str Biblioteca Digital de Teses e Dissertações da UFC
collection Biblioteca Digital de Teses e Dissertações da UFC
instname_str Universidade Federal do Ceará
instacron_str UFC
institution UFC
repository.name.fl_str_mv -
repository.mail.fl_str_mv mail@mail.com
_version_ 1643295189090959360