dc.creatorFlores Moltedo, Andrés Ricardo
dc.creatorSáez Hueichapán, Doris
dc.creatorAraya, Juan
dc.creatorBerenguel, M.
dc.creatorCipriano, Aldo
dc.date.accessioned2022-05-18T14:39:52Z
dc.date.available2022-05-18T14:39:52Z
dc.date.created2022-05-18T14:39:52Z
dc.date.issued2005
dc.identifier10.1109/TFUZZ.2004.839658
dc.identifier1941-0034
dc.identifierhttps://doi.org/10.1109/TFUZZ.2004.839658
dc.identifierhttps://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=1393001
dc.identifierhttps://repositorio.uc.cl/handle/11534/64189
dc.description.abstractThis work presents the application of fuzzy predictive control to a solar power plant. The proposed predictive controller uses fuzzy characterization of goals and constraints, based on the fuzzy optimization framework for multi-objective satisfaction problems. This approach enhances model based predictive control (MBPC) allowing the specification of more complex requirements. A brief description of the solar power plant and its simulator is given. Basic concepts of predictive control and fuzzy predictive control are introduced. Two fuzzy predictive controllers using different membership functions are designed for a solar power plant, and they are compared with a classical predictive controller. The simulation results show that the fuzzy MBPC formulation, based on a well proven successful algorithm, gives a greater flexibility to characterize the goals and constraints than classical control.
dc.languageen
dc.rightsacceso restringido
dc.subjectFuzzy control
dc.subjectPredictive control
dc.subjectSolar energy
dc.subjectPetroleum
dc.subjectConstraint optimization
dc.subjectPredictive models
dc.subjectSolar radiation
dc.subjectRegulators
dc.subjectClouds
dc.subjectHumidity
dc.titleFuzzy predictive control of a solar power plant
dc.typeartículo


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