On the Effect of Constraint Softening on the Stability and Performance of Model Predictive Controllers

dc.contributor.authorZafiriou, E.en_US
dc.contributor.authorChiou, Hung-Wenen_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:51:47Z
dc.date.available2007-05-23T09:51:47Z
dc.date.issued1992en_US
dc.description.abstractThe presence of constraints in the on-line optimization problem solved by Model Predictive Control algorithms results in a nonlinear control system, even if the plant and model dynamics are linear. This is the case both for physical constraints, like saturation constraints, as well for performance or safety constraints on outputs or other variables of the process. Performance constraints can usually be softened by allowing violation if necessary. This is advisable, as hard constraints can lead to stability problems. The determination of the necessary degree of softening is usually a trial-and-error matter. This paper utilizes a theoretical framework that allows to relate hard as well as soft constraints to closed-loop stability. The problem of determining the appropriate degree of softening is addressed by treating the parameters (weights) affecting the amount of softening as one-sided real-valued uncertainty and solving a robust stability problem.en_US
dc.format.extent442375 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5289
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1992-108en_US
dc.subjectpredictive controlen_US
dc.subjectChemical Process Systemsen_US
dc.titleOn the Effect of Constraint Softening on the Stability and Performance of Model Predictive Controllersen_US
dc.typeTechnical Reporten_US

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