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Fitted Q-Function Control Methodology Based on Takagi-Sugeno Systems

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Fitted Q-Function Control Methodology Based on Takagi-Sugeno Systems

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dc.contributor.author Diaz-Iza, Henry Paul es_ES
dc.contributor.author Armesto, Leopoldo es_ES
dc.contributor.author Sala, Antonio es_ES
dc.date.accessioned 2020-11-04T04:32:17Z
dc.date.available 2020-11-04T04:32:17Z
dc.date.issued 2020-03 es_ES
dc.identifier.issn 1063-6536 es_ES
dc.identifier.uri http://hdl.handle.net/10251/154029
dc.description "© 2020 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works." es_ES
dc.description.abstract [EN] This paper presents a combined identification/ Q-function fitting methodology that involves identification of a Takagi-Sugeno model, computation of (sub)optimal controllers from linear matrix inequalities (LMIs), and subsequent data-based fitting of the Q-function via monotonic optimization. The LMI-based initialization provides a conservative solution, but it is a sensible starting point to avoid convergence/local-minima issues in raw data-based fitted Q-iteration or Bellman residual minimization. An inverted-pendulum experimental case study illustrates the approach. es_ES
dc.description.sponsorship This work was supported in part by the Spanish Ministry of Economy and European Union (AEI/FEDER, UE) under Grant DPI2016-81002-R and in part by the Government of Ecuador through the Ph.D. Grant SENESCYT. es_ES
dc.language Inglés es_ES
dc.publisher Institute of Electrical and Electronics Engineers es_ES
dc.relation.ispartof IEEE Transactions on Control Systems Technology es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Adaptive dynamic programming (DP) es_ES
dc.subject Fitted Q-function es_ES
dc.subject Linear matrix inequality (LMI) es_ES
dc.subject Reinforcement learning (RL) es_ES
dc.subject Takagi-Sugeno (TS) es_ES
dc.subject.classification INGENIERIA DE SISTEMAS Y AUTOMATICA es_ES
dc.title Fitted Q-Function Control Methodology Based on Takagi-Sugeno Systems es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1109/TCST.2018.2885689 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//DPI2016-81002-R/ES/CONTROL AVANZADO Y APRENDIZAJE DE ROBOTS EN OPERACIONES DE TRANSPORTE/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería de Sistemas y Automática - Departament d'Enginyeria de Sistemes i Automàtica es_ES
dc.description.bibliographicCitation Diaz-Iza, HP.; Armesto, L.; Sala, A. (2020). Fitted Q-Function Control Methodology Based on Takagi-Sugeno Systems. IEEE Transactions on Control Systems Technology. 28(2):477-488. https://doi.org/10.1109/TCST.2018.2885689 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1109/TCST.2018.2885689 es_ES
dc.description.upvformatpinicio 477 es_ES
dc.description.upvformatpfin 488 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 28 es_ES
dc.description.issue 2 es_ES
dc.relation.pasarela S\389638 es_ES
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Secretaría de Educación Superior, Ciencia, Tecnología e Innovación, Ecuador es_ES


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