Sensor-network-based robust distributed control and estimation

This paper proposes a novel distributed estimation and control method for uncertain plants. It is of application in the case of large-scale systems, where each control unit is assumed to have access only to a subset of the plant outputs, and possibly controls a restricted subset of input channels. A...

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Detalles Bibliográficos
Autores: Millán Gata, Pablo, Orihuela Espina, Diego Luis, Vivas Venegas, Carlos, Rodríguez Rubio, Francisco, Dimaronogas, D.V., Johansson, Karl H.
Tipo de recurso: artículo
Fecha de publicación:2013
País:España
Institución:Universidad Loyola Andalucía
Repositorio:Brújula
OAI Identifier:oai:repositorio.uloyola.es:20.500.12412/1080
Acceso en línea:http://hdl.handle.net/20.500.12412/1080
Access Level:acceso abierto
Palabra clave:Distributed estimation and control
Sensor networks
Process control
Linear matrix inequalities
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spelling Sensor-network-based robust distributed control and estimationMillán Gata, PabloOrihuela Espina, Diego LuisVivas Venegas, CarlosRodríguez Rubio, FranciscoDimaronogas, D.V.Johansson, Karl H.Distributed estimation and controlSensor networksProcess controlLinear matrix inequalitiesThis paper proposes a novel distributed estimation and control method for uncertain plants. It is of application in the case of large-scale systems, where each control unit is assumed to have access only to a subset of the plant outputs, and possibly controls a restricted subset of input channels. A constrained communication topology between nodes is considered so the units can benefit from estimates of neighboring nodes to build their own estimates. The paper proposes a methodology to design a distributed control structure so that the system is asymptotically driven to equilibrium with L2-gain disturbance rejection capabilities. A difficulty that arises is that the separation principle does not hold, as every single unit ignores the control action that other units might be applying. To overcome this, a twostage design is proposed: firstly, the distributed controllers are obtained to robustly stabilize the plant despite the observation errors in the controlled output. At the second stage, the distributed observers are designed aiming to minimize the effects of the communication noise in the observation error. Both stages are formulated in terms of linear matrix inequalities. The performance is shown on a level-control real plant.2013info:eu-repo/semantics/articlehttp://hdl.handle.net/20.500.12412/1080reponame:Brújulainstname:Universidad Loyola AndalucíaIngléshttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:repositorio.uloyola.es:20.500.12412/10802026-06-24T12:48:37Z
dc.title.none.fl_str_mv Sensor-network-based robust distributed control and estimation
title Sensor-network-based robust distributed control and estimation
spellingShingle Sensor-network-based robust distributed control and estimation
Millán Gata, Pablo
Distributed estimation and control
Sensor networks
Process control
Linear matrix inequalities
title_short Sensor-network-based robust distributed control and estimation
title_full Sensor-network-based robust distributed control and estimation
title_fullStr Sensor-network-based robust distributed control and estimation
title_full_unstemmed Sensor-network-based robust distributed control and estimation
title_sort Sensor-network-based robust distributed control and estimation
dc.creator.none.fl_str_mv Millán Gata, Pablo
Orihuela Espina, Diego Luis
Vivas Venegas, Carlos
Rodríguez Rubio, Francisco
Dimaronogas, D.V.
Johansson, Karl H.
author Millán Gata, Pablo
author_facet Millán Gata, Pablo
Orihuela Espina, Diego Luis
Vivas Venegas, Carlos
Rodríguez Rubio, Francisco
Dimaronogas, D.V.
Johansson, Karl H.
author_role author
author2 Orihuela Espina, Diego Luis
Vivas Venegas, Carlos
Rodríguez Rubio, Francisco
Dimaronogas, D.V.
Johansson, Karl H.
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Distributed estimation and control
Sensor networks
Process control
Linear matrix inequalities
topic Distributed estimation and control
Sensor networks
Process control
Linear matrix inequalities
description This paper proposes a novel distributed estimation and control method for uncertain plants. It is of application in the case of large-scale systems, where each control unit is assumed to have access only to a subset of the plant outputs, and possibly controls a restricted subset of input channels. A constrained communication topology between nodes is considered so the units can benefit from estimates of neighboring nodes to build their own estimates. The paper proposes a methodology to design a distributed control structure so that the system is asymptotically driven to equilibrium with L2-gain disturbance rejection capabilities. A difficulty that arises is that the separation principle does not hold, as every single unit ignores the control action that other units might be applying. To overcome this, a twostage design is proposed: firstly, the distributed controllers are obtained to robustly stabilize the plant despite the observation errors in the controlled output. At the second stage, the distributed observers are designed aiming to minimize the effects of the communication noise in the observation error. Both stages are formulated in terms of linear matrix inequalities. The performance is shown on a level-control real plant.
publishDate 2013
dc.date.none.fl_str_mv 2013
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12412/1080
url http://hdl.handle.net/20.500.12412/1080
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Brújula
instname:Universidad Loyola Andalucía
instname_str Universidad Loyola Andalucía
reponame_str Brújula
collection Brújula
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812455

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