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dc.contributor.authorHenriques, Jorgeen_US
dc.contributor.authorCardoso, Albertoen_US
dc.contributor.authorDourado, Antónioen_US
dc.identifier.citationInternational Journal of Approximate Reasoning. 22:1-2 (1999) 73-91en_US
dc.description.abstractA hierarchical control strategy consisting on a supervisory switching of PID controllers, simplified using the c-Means clustering technique, is developed and applied to the distributed collector field of a solar power plant. The main characteristic of this solar plant is that the primary energy source, the solar radiation, cannot be manipulated. It varies throughout the day, causing changes in plant dynamics conducting to distinct several operating points. To guarantee good performances in all operating points, a local PID controller is tuned to each operating point and a supervisory strategy is proposed and applied to switch among these controllers accordingly to the actual measured conditions. Each PID controller has been tuned off-line, by the combination of a dynamic recurrent non-linear neural network model with a pole placement control design. To reduce the number of local controllers, to be selected by the supervisor, a c-Means clustering technique was used. Simulation and experimental results, obtained at Plataforma Solar de Almería, Spain, are presented showing the effectiveness of the proposed approach.en_US
dc.subjectFuzzy supervisoren_US
dc.subjectSwitching controlen_US
dc.subjectPID controlen_US
dc.subjectNeural networksen_US
dc.subjectSolar power plantsen_US
dc.titleSupervision and c-Means clustering of PID controllers for a solar power planten_US
item.fulltextCom Texto completo-
item.grantfulltextopen- de Ciências e Tecnologia, Universidade de Coimbra- FOR INFORMATICS AND SYSTEMS OF THE UNIVERSITY OF COIMBRA-
Appears in Collections:FCTUC Eng.Informática - Artigos em Revistas Internacionais
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