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EnglishPartial enumeration (PE) is presented as a method for treating large, linear model predictive control applications that are out of reach with available MPC methods. PE uses both a table storage method and online optimization to achieve this goal. Versions of PE are shown to be closed-loop stable. PE is applied to an industrial example with more than 250 states, 32 inputs, and a 25-sample control horizon. The performance is less than 0.01% suboptimal, with average speedup factors in the range of 80-220, and worst-case speedups in the range of 4.9-39.2, compared to an existing MPC method. Small tables with only 25-200 entries were used to obtain this performance, while full enumeration is intractable for this example. © 2007 Elsevier Ltd. All rights reserved.
| Autori interni: | ||
| Autori: | PANNOCCHIA G; RAWLINGS JB; WRIGHT SJ | |
| Titolo: | Fast, Large-scale Model Predictive Control by Partial Enumeration | |
| Anno del prodotto: | 2007 | |
| Digital Object Identifier (DOI): | 10.1016/j.automatica.2006.10.019 | |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
File in questo prodotto:
http://hdl.handle.net/11568/117983
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