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Data-driven predictive control for solid oxide fuel cells
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DOI：10.1016/j.jprocont.2006.09.004.png)
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This paper is concerned with predictive control of solid oxide fuel cells (SOFC) based on a benchmark model commonly studied in the dynamic SOFC modeling/control literature. It has been shown in previous studies that control of SOFC is challenging owing to the slow response and tight operating constraints. In this paper, we apply a data-driven predictive control approach to solving the control problem of the SOFC system. The predictive control applied is completely data based. In addition, unlike other data-driven predictive control designs, the proposed approach can deal with systems without complete on-line measurement of all output variables. Simulation results have demonstrated the feasibility of the control application. (C) 2006 Elsevier Ltd. All rights reserved.
Keyword:
SOFC
predictive control
subspace matrices
data-driven methods
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