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Model predictive control of greenhouse climate using RBF models
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This paper presents the methodology and simulation results regarding the application of model predictive control to greenhouse environmental control and crop production optimisation.
External climate (solar radiation, temperature and humidity) and greenhouse environmental (temperature and humidity)
predictive models are built using radial basis function neural networks. Multi-Objective Genetic Algorithms were applied to
select the input-output structure of models. The control actions over the prediction horizon are selected using a branch-andbound
algorithm minimising a cost function. A tomato crop was grown in order to collect data to develop a crop production model to enable production optimisation in the proposed control strategy.
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Ferreira, P. M.; Ruano, A. E. Model predictive control of greenhouse climate using RBF models, Trabalho apresentado em Global Education Techology Symposium (GETS 2006), In Proceedings of the Global Education Techology Symposium (GETS 2006), Faro, 2006.