Self-optimizing control – A survey

dc.contributor.authorJäschke, Johannes
dc.contributor.authorCao, Yi
dc.contributor.authorKariwala, Vinay
dc.date.accessioned2017-04-06T10:07:38Z
dc.date.available2017-04-06T10:07:38Z
dc.date.issued2017-04-04
dc.description.abstractSelf-optimizing control is a strategy for selecting controlled variables. It is distinguished by the fact that an economic objective function is adopted as a selection criterion. The aim is to systematically select the controlled variables such that by controlling them at constant setpoints, the impact of uncertain and varying disturbances on the economic optimality is minimized. If a selection leads to an acceptable economic loss compared to perfectly optimal operation then the chosen control structure is referred to as “self-optimizing”. In this comprehensive survey on methods for finding self-optimizing controlled variables we summarize the progress made during the last fifteen years. In particular, we present brute-force methods, local methods based on linearization, data and regression based methods, and methods for finding nonlinear controlled variables for polynomial systems. We also discuss important related topics such as handling changing active constraints. Finally, we point out open problems and directions for future research.en_UK
dc.identifier.citationJäschke J, Cao Y, Kariwala V, Self-optimizing control – A survey, Annual Reviews in Control, Vol. 43, 2017, pp. 199-223en_UK
dc.identifier.issn1367-5788
dc.identifier.urihttp://dx.doi.org/10.1016/j.arcontrol.2017.03.001
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/11735
dc.language.isoenen_UK
dc.publisherElsevier Science B.V., Amsterdam.en_UK
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectSelf-optimizing controlen_UK
dc.subjectControl structure selectionen_UK
dc.subjectControlled variablesen_UK
dc.subjectPlant-wide controlen_UK
dc.titleSelf-optimizing control – A surveyen_UK
dc.typeArticle (Literature review, Editorial)en_UK

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