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1、102IEEETRANSACTIONSONNEURALNETWORKS,VOL.11,NO.1,JANUARY2000ANewMethodfortheControlofDiscreteNonlinearDynamicSystemsUsingNeuralNetworksO.Adetona,Member,IEEE,E.Garcia,andL.H.Keel,SeniorMember,IEEEAbstract—Anewcontrollerdesignmethodfornonaffinenon-neighborhoodofth
2、eequilibriumstatefortheclassofsystemslineardynamicsystemsispresentedinthispaper.Anidentifiedconsideredinthispaper.neuralnetworkmodelofthenonlinearplantisusedinthepro-Aniterativeinversionofanidentifiedneuralnetworkmodelposedmethod.Themethodisbasedonanewcontrolla
3、wthatisofthenonlinearplanthasbeenproposedfortheneural-controldevelopedforanydiscretedeterministictime-invariantnonlineardynamicsysteminasubregion8ofanasymptoticallystableequi-problem.Theidentificationmodelcouldbeamultilayerneurallibriumpointoftheplant.Theperfor
4、manceofthecontrollawisnotnetworkoraradialbasisfunctionneuralnetwork.Theidentifiednecessarilydependentonthedistancebetweenthecurrentstateofmodeloftheplantanditscurrentstateareusedtoiterativelytheplantandtheequilibriumstateifthenonlineardynamicsystemdeterminethec
5、ontrolinputthatwillyieldthedesiredresponsesatisfiessomemildrequirementsin8Thecontrollawissimpleto(e.g.,[3]–[5]).Unfortunately,thequalityofthecomputedcon-implementandisbasedonanovellinearizationoftheinput–outputmodeloftheplantateachinstantintime.Itcanbeusedtocon
6、troltrolsignalwillbeadverselyaffectedifthesamplingintervalofbothminimumphaseandnonminimumphasenonaffinenonlinearthesystemisnotlargeenoughtoallowtheiterativeprocesstoplants.Extensiveempiricalstudieshaveconfirmedthatthecontrolachieveasufficientnumberofiterations.
7、lawcanbeusedtocontrolarelativelygeneralclassofhighlynon-Mostcontrolmethodsdirectlyorindirectlyimposeatleastlinearmultiinput–multioutput(MIMO)plants.oneofthefollowingrestrictiveconditions:1)theplantislinearIndexTerms—Linearization,neuralnetworks,nonaffine,non-wi
8、threspecttothecontrolinput;2)theoperatingregionoflinearcontrol,nonminimumphase.theplantislimitedtoasufficientlysmallneighborhoodoftheorigin;and3)theplantisaminimumphase1plan