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1、ProcessSystemsEnaineerinaModelPredictiveControlwithLinearModelsKennethR.MuskeandJamesB.RawlingsDept.ofChemicalEngineering,UniversityofTexasatAustin,Austin,TX78712Thisarticlediscussestheexistinglinearmodelpredictivecontrolconceptsinaunifiedtheoreticalframeworkbasedonastabilizing,infinit
2、ehorizon,linearquad-raticregulator.Inordertorepresentunstableaswellasstablemultivariablesystems,thestandardstate-spaceformulationisusedfortheplantmodel.Theincorporationofanominallystabilizingconstrainedregulatoreliminatesthecurrentrequirementoftuningfornominalstability.Outputfeedbackis
3、addressedinthewell-establishedframeworkofthelinearquadraticstate-estimationproblem.Thisframeworkallowstheflexibilitytohandlenonsquaresystems,noisyinputsandoutputs,andnonzeroinput,output,andstatedisturbances.Thisformulationsubsumestheintegralcontrolschemesdesignedtoremovesteady-stateoff
4、setcurrentlyinindustrialuse.Theon-lineimplementationofthecontrollerrequiresthesolutionofastandardquadraticprogramthatisnomorecomputationallyintensivethanexistingalgorithms.IntroductionLinearmodelpredictivecontrolreferstoaclassofcontrolstrained,multivariableprocesses.Theemphasisinthedev
5、el-algorithmsthatcomputeamanipulatedvariableprofilebyopmentofthesecontrollerswasarobustalgorithmwithutilizingalinearprocessmodeltooptimizealinearorquadraticacceptableperformancethatcouldbeimplementedon-line.open-loopperformanceobjectivesubjecttolinearconstraintsTherefore,severalaspects
6、ofthesecontrollersweredesignedoverafuturetimehorizon.Thefirstmoveofthisopenloopbasedonaheuristicapproachwithlittletheoreticaljustifi-optimalmanipulatedvariableprofileisthenimplemented.Thiscation.Thisproducedcontrollersthatperformedverywellforprocedureisrepeatedateachcontrolintervalwith
7、theprocessaspecificclassofplants,butwereunabletoadequatelyaddressmeasurementsusedtoupdatetheoptimizationproblem.others.Theseremarksarenotintendedtominimizethesig-Thisclassofcontrolalgorithms,whichisalsoreferredtonificanceofthecontributionmadebyindustry.Wereitnotasrecedinghorizoncontr
