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dc.contributor.authorLouca, Loucas S.en
dc.contributor.authorStein, J. L.en
dc.contributor.authorHulbert, G. M.en
dc.creatorLouca, Loucas S.en
dc.creatorStein, J. L.en
dc.creatorHulbert, G. M.en
dc.date.accessioned2019-05-06T12:24:06Z
dc.date.available2019-05-06T12:24:06Z
dc.date.issued2010
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/48601
dc.description.abstractIn recent years, algorithms have been developed to help automate the production of dynamic system models. Part of this effort has been the development of algorithms that use modeling metrics for generating minimum complexity models with realization preserving structure and parameters. Existing algorithms, add or remove ideal compliant elements from a model, and consequently do not equally emphasize the contribution of the other fundamental physical phenomena, i.e., ideal inertial or resistive elements, to the overall system behavior. Furthermore, these algorithms have only been developed for linear or linearized models, leaving the automated production of models of nonlinear systems unresolved. Other model reduction techniques suffer from similar limitations due to linearity or the requirement that the reduced models be realization preserving. This paper presents a new modeling metric, activity, which is based on energy. This metric is used to order the importance of all energy elements in a system model. The ranking of the energy elements provides the relative importance of the model parameters and this information is used as a basis to reduce the size of the model and as a type of parameter sensitivity information for system design. The metric is implemented in an automated modeling algorithm called model order reduction algorithm (MORA) that can automatically generate a hierarchical series of reduced models that are realization preserving based on choosing the energy threshold below which energy elements are not included in the model. Finally, MORA is applied to a nonlinear quarter car model to illustrate that energy elements with low activity can be eliminated from the model resulting in a reduced order model, with physically meaningful parameters, which also accurately predicts the behavior of the full model. The activity metric appears to be a valuable metric for automating the reduction of nonlinear system models - providing in the process models that provide better insight and may be more numerically efficient. © 2010 American Society of Mechanical Engineers.en
dc.language.isoengen
dc.sourceJournal of Dynamic Systems, Measurement and Control, Transactions of the ASMEen
dc.subjectMathematical modelsen
dc.subjectAlgorithmsen
dc.subjectAutomationen
dc.subjectNonlinear systemsen
dc.subjectSystem modelsen
dc.subjectSystem behaviorsen
dc.subjectDynamic system modelsen
dc.subjectEnergy-based modelsen
dc.subjectModel order reductionen
dc.subjectAutomated modelingen
dc.subjectAutomated productionsen
dc.subjectEnergy thresholdsen
dc.subjectFull modelen
dc.subjectLinearized modelsen
dc.subjectModel automobilesen
dc.subjectModel parametersen
dc.subjectModel reduction techniquesen
dc.subjectParameter sensitivitiesen
dc.subjectPhysical phenomenaen
dc.subjectProcess modelen
dc.subjectQuarter car modelen
dc.subjectReduced modelen
dc.subjectReduced order modelsen
dc.subjectRelative importanceen
dc.subjectResistive elementsen
dc.subjectSystem designen
dc.titleEnergy-based model reduction methodology for automated modelingen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1115/1.4002473
dc.description.volume132
dc.author.facultyΠολυτεχνική Σχολή / Faculty of Engineering
dc.author.departmentΤμήμα Μηχανικών Μηχανολογίας και Κατασκευαστικής / Department of Mechanical and Manufacturing Engineering
dc.type.uhtypeArticleen
dc.contributor.orcidLouca, Loucas S. [0000-0002-0850-2369]


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