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Integración de la estrategia FMBPC en una estructura de control predictivo en lazo cerrado. Aplicación al control de fangos activados

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Integración de la estrategia FMBPC en una estructura de control predictivo en lazo cerrado. Aplicación al control de fangos activados

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dc.contributor.author Vallejo, Pedro M. es_ES
dc.contributor.author Vega, Pastora es_ES
dc.date.accessioned 2021-12-21T09:12:16Z
dc.date.available 2021-12-21T09:12:16Z
dc.date.issued 2021-12-17
dc.identifier.issn 1697-7912
dc.identifier.uri http://hdl.handle.net/10251/178682
dc.description.abstract [ES] En este trabajo se aborda la integración de dos métodos o estrategias de Control Predictivo basado en Modelos, a saber: Control Predictivo basado en Modelos Borrosos (FMBPC) y Control Predictivo en Lazo Cerrado (CLP MPC). La primera de estas estrategias utiliza principios de Control Predictivo Funcional (PFC) y está enmarcada, al mismo tiempo, en el ámbito del Control Inteligente (IC). La integración tiene como principal objetivo proporcionar a la estrategia de control no lineal FMBPC un procedimiento de optimización que permita el manejo automático de restricciones en la variable de control. La solución propuesta consiste en hacer uso de una estructura complementaria de tipo CLP MPC para determinar mediante optimización, en cada instante de muestreo, los valores óptimos de un cierto término aditivo, a sumar a la ley de control FMBPC, de tal modo que se satisfagan las restricciones. El modelo de predicciones y la ley de control base necesarios para realizar los cálculos en la estructura CLP MPC son proporcionados por la estrategia FMBPC. La estrategia mixta FMBPC/CLP propuesta ha sido validada, en simulación, aplicándola al control de fangos activados en plantas de tratamiento de aguas residuales (EDAR), poniendo el foco en la imposición de restricciones a la acción de control. Los resultados obtenidos son satisfactorios, observando un buen rendimiento del algoritmo de control diseñado, al tiempo que se garantiza tanto la satisfacción de las restricciones, que era el principal objetivo, como la estabilidad del sistema en lazo cerrado. es_ES
dc.description.abstract [EN] This work addresses the integration of two methods or strategies of Model-Based Predictive Control, namely: Fuzzy Model-Based Predictive Control (FMBPC) and Closed-Loop Predictive Control (CLP-MPC). The first of these strategies uses principles of Predictive Functional Control (PFC) and is framed, at the same time, in the field of Intelligent Control (IC). The main objective of the integration is to provide to the FMBPC nonlinear control strategy an optimization procedure that allows the automatic handling of constraints in the control variable. The proposed solution consists of making use of a complementary structure of the CLP-MPC type to determine by optimization, at each sampling instant, the optimal values of a certain additive term, to be added to the FMBPC control law, in such a way that they are satisfied the constraints. The prediction model and base control law necessary to perform the calculations on the CLP-MPC structure are provided by the FMBPC strategy. The proposed FMBPC/CLP mixed strategy has been validated, in simulation, applying it to the control of activated sludge processes in wastewater treatment plants (WWTP), focusing on the imposition of constraints on the control action. The results obtained are satisfactory, observing a good performance of the designed control algorithm, while guaranteeing both the satisfaction of the constraints, which was the main objective, and the stability of the closed-loop system. es_ES
dc.description.sponsorship Este trabajo contó con el apoyo económico del Gobierno de España a través del proyecto MICINN PID2019-105434RB-C31 y de la Fundación Samuel Solórzano a través del proyecto FS / 20-2019. es_ES
dc.language Español es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Revista Iberoamericana de Automática e Informática industrial es_ES
dc.rights Reconocimiento - No comercial - Compartir igual (by-nc-sa) es_ES
dc.subject Model-based predictive control es_ES
dc.subject Fuzzy control and fuzzy systems in control es_ES
dc.subject Intelligent control techniques es_ES
dc.subject Control of systems with restrictions es_ES
dc.subject Multivariable control es_ES
dc.subject Automatic control of water treatment systems es_ES
dc.subject Control predictivo basado en modelo es_ES
dc.subject Control borroso y sistemas borrosos en control es_ES
dc.subject Técnicas de control inteligente es_ES
dc.subject Control de sistemas con restricciones es_ES
dc.subject Control multivariable es_ES
dc.subject Control automático de sistemas de tratamiento de aguas es_ES
dc.title Integración de la estrategia FMBPC en una estructura de control predictivo en lazo cerrado. Aplicación al control de fangos activados es_ES
dc.title.alternative Integration of the FMBPC strategy in a Closed-Loop Predictive Control structure. Application to the control of activated sludge es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/riai.2021.15793
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105434RB-C31/ES/DESARROLLO DE TECNICAS DE CONTROL DISTRIBUIDO INTELIGENTE BASADAS EN TEORIA DE JUEGOS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Vallejo, PM.; Vega, P. (2021). Integración de la estrategia FMBPC en una estructura de control predictivo en lazo cerrado. Aplicación al control de fangos activados. Revista Iberoamericana de Automática e Informática industrial. 19(1):13-26. https://doi.org/10.4995/riai.2021.15793 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/riai.2021.15793 es_ES
dc.description.upvformatpinicio 13 es_ES
dc.description.upvformatpfin 26 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 19 es_ES
dc.description.issue 1 es_ES
dc.identifier.eissn 1697-7920
dc.relation.pasarela OJS\15793 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
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