Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function

Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function

ID:40706541

大?。?77.29 KB

頁數(shù):7頁

時(shí)間:2019-08-06

Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function_第1頁
Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function_第2頁
Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function_第3頁
Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function_第4頁
Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function_第5頁
資源描述:

《Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function》由會(huì)員上傳分享,免費(fèi)在線閱讀,更多相關(guān)內(nèi)容在學(xué)術(shù)論文-天天文庫(kù)。

1、IEEETRANSACTIONSONNEURALNETWORKS,VOL.21,NO.8,AUGUST20101339BriefPapersAdaptiveNeuralControlforOutputFeedbackNonlinearSystemsUsingaBarrierLyapunovFunctionItiswellknownthatNNapproximation-basedcontrolreliesonuniversalapproximationpropertyinacompactsetinorderBeibeiRen,Member,IEEE,Shuz

2、hiSamGe,Fellow,IEEE,toapproximateunknownnonlinearitiesintheplantdynamics.KengPengTee,Member,IEEE,andForanyinitialcompactset0,aslongastheargumentsTongHengLee,Member,IEEE0oftheunknownfunctionstartfromandremainwithinacompactsuperset,asshowninFig.1[8],NNapproximationisvalid.Therefor

3、e,howtodetermineapriorithecompactsupersetAbstractInthisbrief,adaptiveneuralcontrolispresentedandhowtoensuretheargumentsoftheunknownfunc-foraclassofoutputfeedbacknonlinearsystemsinthepresenceofunknownfunctions.Theunknownfunctionsarehandledtionremainwithinthecompactsuperset,aretwoo

4、penviaon-lineneuralnetwork(NN)controlusingonlyoutputandchallengingproblemsintheneuro-controlarea[2].Onemeasurements.AbarrierLyapunovfunction(BLF)isintroducedmethodofensuringthattheNNapproximationconditionholdstoaddresstwoopenandchallengingproblemsintheneuro-isbycarefulselectionofth

5、econtrolparameters,viarigorouscontrolarea:1)foranyinitialcompactset,howtodeterminetransientperformanceanalysis,sothatthesystemstatesdoapriorithecompactsuperset,onwhichNNapproximationisvalid;and2)howtoensurethattheargumentsofthenottransgressthecompactsupersetofapproximation[6],unkn

6、ownfunctionsremainwithinthespeci?edcompactsuperset.[8],butthecompactsupersetisonlygivenqualitatively,notByensuringboundednessoftheBLF,weactivelyconstrainthequantitively.Anothermethodistorelyonslidingmodecontrolargumentoftheunknownfunctionstoremainwithinacompactoperatinginparallelt

7、otheapproximation-basedcontrol,suchsupersetsuchthattheNNapproximationconditionshold.Thethatthecompactsupersetisrenderedpositivelyinvariantsemiglobalboundednessofallclosed-loopsignalsisensured,andthetrackingerrorconvergestoaneighborhoodofzero.[5],[27].Thecompactsupersetcanbespeci?

8、edapriori,Simulationresult

當(dāng)前文檔最多預(yù)覽五頁,下載文檔查看全文

此文檔下載收益歸作者所有

當(dāng)前文檔最多預(yù)覽五頁,下載文檔查看全文
溫馨提示:
1. 部分包含數(shù)學(xué)公式或PPT動(dòng)畫的文件,查看預(yù)覽時(shí)可能會(huì)顯示錯(cuò)亂或異常,文件下載后無此問題,請(qǐng)放心下載。
2. 本文檔由用戶上傳,版權(quán)歸屬用戶,天天文庫(kù)負(fù)責(zé)整理代發(fā)布。如果您對(duì)本文檔版權(quán)有爭(zhēng)議請(qǐng)及時(shí)聯(lián)系客服。
3. 下載前請(qǐng)仔細(xì)閱讀文檔內(nèi)容,確認(rèn)文檔內(nèi)容符合您的需求后進(jìn)行下載,若出現(xiàn)內(nèi)容與標(biāo)題不符可向本站投訴處理。
4. 下載文檔時(shí)可能由于網(wǎng)絡(luò)波動(dòng)等原因無法下載或下載錯(cuò)誤,付費(fèi)完成后未能成功下載的用戶請(qǐng)聯(lián)系客服處理。