The Closed-Form Control Laws of the Constrained Model Predictive Control Algorithm

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dc.contributor.authorChiou, Hung-Wenen_US
dc.contributor.authorZafiriou, Evanghelosen_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:54:48Z
dc.date.available2007-05-23T09:54:48Z
dc.date.issued1993en_US
dc.description.abstractThe Analysis of quadratic Stability and strongly Hperformance of Model Predictive Control (MPC) with hard constraints (or called Constrained Model Predictive Control (CMPC)) can be accomplished by reformulating the hard constraints of CMPC. From the CMPC algorithm, each term of the closed-form of CMPC control law corresponding to an active constraint situation can be decomposed to have an uncertainty block, which is time varying over the control period. The control law also contains a bias from the bounds of the constraints which cause difficulty in stability and performance analysis. An alternative way to avoid this difficulty is to reformulate the hard constraints to adjustable constraints with time varying adjustable weights on the adjustable variables added to the on-line objective function. The time varying weights in the adjustable constraint control law make the control action just the same as the hard constrained control. Theoretical derivatives and examples are given. The same reformulation is applied to the softened constraint cases.<P>On the analysis of the quadratic stability and strongly H performance, the control system for hard constraint control law without bias satisfies the stability and performance criteria if and only if the control system for adjustable constraint control law with time varying adjustable weights satisfies the same criteria. The details will be shown in the technical reports on quadratic stability and strongly Hperformance analysis, which are in preparation.en_US
dc.format.extent981939 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5433
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1993-89en_US
dc.subjectchemical process controlen_US
dc.subjectoptimizationen_US
dc.subjectpredictive controlen_US
dc.subjectChemical Process Systemsen_US
dc.titleThe Closed-Form Control Laws of the Constrained Model Predictive Control Algorithmen_US
dc.typeTechnical Reporten_US

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