Metodología de control óptimo para sistemas no lineales diferencialmente planos, basado en control por rechazo activo de perturbaciones (ADRC) y control predictivo basado en modelo (MPC)

dc.contributorCortés Romero, John Alexander
dc.contributorDorado Rojas, Sergio
dc.creatorAguilar Pérez, Santiago
dc.date.accessioned2022-06-29T18:30:04Z
dc.date.available2022-06-29T18:30:04Z
dc.date.created2022-06-29T18:30:04Z
dc.date.issued2022
dc.identifierhttps://repositorio.unal.edu.co/handle/unal/81667
dc.identifierUniversidad Nacional de Colombia
dc.identifierRepositorio Institucional Universidad Nacional de Colombia
dc.identifierhttps://repositorio.unal.edu.co/
dc.description.abstractLas metodologías para diseño de controladores basadas en modelo requieren un alto nivel de conocimiento del sistema dinámico para poder diseñar una ley de control, en contraste de las metodologías basadas en error; estos enfoques pueden limitar la aplicación de metodologías de control óptimo, dado que para ciertas situaciones puede ser difícil establecer un modelo que describa al sistema dinámico adecuadamente, así mismo, para modelos muy rigurosos existen dificultadas asociadas a resolver el problema de optimización y para metodologías basadas en error el desempeño no siempre es el deseado. Como alternativa, este trabajo propone una metodología de control óptimo para sistemas diferencialmente planos no lineales, basado en control por rechazo activo de perturbaciones (ADRC - por sus siglas en inglés active disturbance rejection control), el cual es usado para estimar y rechazar las incertidumbres y perturbaciones (internas y externas) a partir de un modelo simplificado que permite plantear un problema de optimización. Luego, se sintetiza el controlador empleando la metodología de control predictivo basado en modelo (MPC - por sus siglas en inglés model predictive control). A través de distintos casos de estudio, se validan y evalúan algunas características de las estructuras asociadas a la metodología de control propuesta. Finalmente se logra establecer una metodología de control que otorga al sistema dinámico un comportamiento estable y robusto, mientras minimiza una función de costo de desempeño. (Texto tomado de la fuente).
dc.description.abstractMethodologies for model-based controller design require a high level of knowledge of the dynamic system in order to design a control law, as opposed to error-based methodologies; these approaches may limit the application of optimal control methodologies, as for certain situations it may be difficult to establish a model that describes the dynamic system properly, also, for very rigorous models there are difficulties associated with solving the optimization problem and for error-based methodologies performance is not always desired. As an alternative, this paper proposes an optimal control methodology for differentially flat non-linear systems, based on active disturbance rejection control (ADRC), which is used to estimate and reject uncertainties and disturbances (internal and external) from a simplified model that allows to pose an optimization problem for design. The controller is then synthesized using model predictive control (MPC). Through different case studies, some characteristics of the structures associated with the proposed control methodology are validated and evaluated. Finally, it is possible to establish a control methodology that gives the dynamic system a stable and robust behavior, while minimizing a performance cost function.
dc.languagespa
dc.publisherUniversidad Nacional de Colombia
dc.publisherBogotá - Ingeniería - Maestría en Ingeniería - Automatización Industrial
dc.publisherDepartamento de Ingeniería Eléctrica y Electrónica
dc.publisherFacultad de Ingeniería
dc.publisherBogotá, Colombia
dc.publisherUniversidad Nacional de Colombia - Sede Bogotá
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dc.rightsAtribución-NoComercial-SinDerivadas 4.0 Internacional
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.titleMetodología de control óptimo para sistemas no lineales diferencialmente planos, basado en control por rechazo activo de perturbaciones (ADRC) y control predictivo basado en modelo (MPC)
dc.typeTrabajo de grado - Maestría


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