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Heat Transfer Research
Impact-faktor: 0.404 5-jähriger Impact-Faktor: 0.8 SJR: 0.264 SNIP: 0.504 CiteScore™: 0.88

ISSN Druckformat: 1064-2285
ISSN Online: 2162-6561

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Heat Transfer Research

DOI: 10.1615/HeatTransRes.v36.i3.10
pages 151-169

Predictive Control of a Humidifying Process Modelled on Reproducing Kernel Hilbert Spaces

El Aissi
Institut Supérieur des Etudes Technologiques de Sousse, Cité Erriadh Sousse, France
Hassani Messaoud
Research Unit ATSI, National School of Engineers of Monastir, University of Monastir, Rue Ibn El Jazzar, 5019 Monastir, Tunisia


This paper focuses on the Model Based Predictive Control (MBPC) of the humidifying process inside a drying blower. This process is known to have a nonlinear behavior. To synthesize the MBP control, we used a Reproducing Kernel Hilbert Space (RKHS) model with reduced complexity. The identification of this model is carried in a black box context with no a priori information needed, using the Statistical Learning Techniques (SLT). This model is linear with respect to its parameters and copes well with the nonlinear systems approximation problems. The proposed algorithm is used to regulate the humidity inside a drying blower.

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