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...(Problems pasted from Keshets book.) (1) Determine if Bendixsons criterion can be used to rule out periodic orbits in the following systems, in the indicated regions of the plane:
(2) Suppose that all the steady states (indicated by large dots) in t...
...Proceedings of the 40th IEEE Conference on Decision and Control Orlando, Florida USA, December 2001
LMI approach to spectral stabilizability of linear delay systems and stabilizability of linear systems with complex parameter
Pierre-Alexandre Bliman...
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eritne -ni eht revo tnemeriuqer gnikcart mrofinu tub lav -retni etin :sksat lortnoc gnikcart elbatae per )1 .srot -caf owt gniwollof eht yb de ice ps si tnemnorivne lort -noc gnikcart elbatae per A .elbanrael era seitniatrecnu cirtemarap gniyrav-emit eht ,tnemnorivne lortnoc elba -tae per rednU .elpmaxe evitartsulli na sedivorp 5 noitceS .sliated ni dessucsid dna den -ed era gninrael lamitpo-bus dna FEC eht ,4 noitceS nI .3 noitceS ni detneserp si lortnoc lamitpo raenilnon fo noitcud ortni feirb A .nevig si noitalumrof melborp eht ,2 noitceS nI .swollof sa dezinagro si re pap sihT .tce e gninrael eht setaulave dna wal lortnoc gninrael fo noitavired eht setatilicaf hcihw rorre gninrael cirtemarap fo mron .sdnuo b ytniatrecnu eht fo egdelwonk roirp eht tuohtiw seitniatrecnu cirtemarap gniyrav-emit htiw smetsys raenilnon ot deilppa dna lortnoc lamitpo -bus htiw detargetni si lortnoc gninrael ,krow siht nI .secnabrutsid dna seitniatrecnu metsys fo ecneserp eht ni sdohtem eseht ylppa ot tluc id e b dluow ti revewoH .]4-1[ lortnoc lamitpo raenilnon fo ngised eht ni deso p -orp nee b evah )FLC( noitcnuf vonupayL lortnoc no desab lortnoc lamitpo esrevni dna lortnoc lamitpo-bus ,noitauqe laitnere id )BJH( namlleB-ibocaJ-notlimaH laitrap raenilnon eht gnivlos ni seitluc id fo esuaceB .sedaced wef tsap revo krow hcraeser elbaredisnoc fo tcej bus evitca na nee b sah lortnoc lamitpo raenilnoN si trap dnoces ehT .elcyc gninrael hcae rof noziroh emit gnola roivahe b metsys sessessa dna wal lortnoc lamitpo -bus fo noitavired eht setatilicaf hcihw )FLC( noitcnuf vonupayL lortnoc a si trap tsr ehT .strap owt fo stsis -noc hcihw ,lortnoc gninrael otni )FEC( noitcnuf ygre -ne etiso pmoc levon a ecudortni ew ,sisylana suorogir dna noitargetni lortnoc rof noitadnuof eht yal oT .]8-5[ deso porp nee b evah semehcs lortnoc gninrael citsinim -reted fo re bmun A .noziroh noitite per gninrael gnola ecnamrofre p lamitpo dna noziroh emit gnola ecnam -rofre p lamitpo-bus eht deniater e b nac lortnoc gni -nrael dna lortnoc lamitpo hto b fo segatnavda eht ,noit -argetni yB .smetsys raenilnon ni detsixe seitniatrecnu elbanrael eht gnilecnac fo esnes eht ni semehcs lortnoc lamitpo fo dnik rehtona sa dedrager e b nac lortnoc gni -nrael ecneH .ecnamrofre p gnikcart morf seitniatrecnu metsys fo ecneu ni eht yfillun yletelpmoc nac msina -hcem lortnoc gninrael eht ,elpicnirp led om lanretni fo eutriv yB .seitniatrecnu cirtemarap gniyrav-emit met -sys eht fo ytilibanrael eht stnarraw ytilibatae per met -sys ehT .cte ,enil ylbmessa no lortnoc to bor lairtsud -ni ,ssecorp gnidlew CI ,lortnoc rotcaer hctab ,ssecorp refaw sa hcus saera lortnoc ssec orp dna lortnoc noitom ni hto b deretnuocne llew era smelborp lortnoc elbatae p -eR .seitniatrecnu lavretni dna seitniatrecnu cirtemarap gniyrav-emit ot tcej bus ylbisso p dna ,noitidnoc laitini emas eht htiw metsys cimanyd citsinimreted )2 ;lavret 2 La noitcudortnI 1 .derusne osla era noziroh emit gnola rorre gnikcart eht fo ecnegrevnoc esiwtnio p dna ssende -dnuo b eht ,emit emas eht tA .noziroh noitite per gni -nrael gnola ecnegrevnoc lacitotpmysa seveihca emehcs lortnoc deso porp ehT .stce e niatrecnu etanimile ot sa os seitniatrecnu cirtemarap gniyrav-emit nwonknu nrael ot seirt msinahcem gninraeL .metsys cimanyd rae -nilnon eht fo trap lanimon eht rof noziroh emit gnola ytilibats sa llew sa ecnamrofre p lamitpo-bus a sediv -orp alumrof s gatnoS dna )FLC( noitcnuf vonupayL lortnoc no desab ygetarts lortnoc lamitpo-buS .seitniat -recnu cirtemarap gniyrav-emit htiw metsys raenilnon fo ssalc a rof ecnamrofre p lortnoc ecnahne ot lortnoc lamitpo-bus raenilnon htiw detargetni si lortnoc gni -nrael ,FEC eht no desaB .noziroh noitite per gninrael dna emit hto b gnola noitamrofni metsys gnitaro proc -ni rof krowemarf lareneg a edivorp ot decud ortni si )FEC( noitcnuf ygrene etiso pmoc levon a ,re pap siht nI tc artsbA A Composite Energy Function Based Sub-optimal Learning Control Approach for Nonlinear Systems with Tima-varying Parametric Uncertainties Tan Ying and Xu Jian-xin Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 )4( = = = ) (d t x )( ) )t(u)t ,e( B + )t ,e( f t u t , x( B + )t , x( f )t( d x )t( x ) ( te :si scimanyd rorre eht )3( 0 = ) , 0( f u)t , x( B + )t , x( f = x swol .metsys cimanyd eht fo ytilibats eht erusne dna seitniatrecnu elbanrael eht htiw laed ot detar -oprocni si lortnoc gninrael ,melborp siht emocrevo oT .)1( ni )t ,x( )t( = d seitniatrecnu gniyrav-emit rae -nilnon lareneg htiw laed ot elbissopmi tub ,)seitiraenil -non rotces( ecnabrutsid tupni fo sessalc niatrec ot tceps -er htiw tsubor )9( wal lortnoc lamitpo-bus eht sekam nigram rotces fo ecnetsixe ehT .) ,1[ nigram rotces eht sah )9( wal lortnoc lamitpo-bus ehT 1 krameR .)4( metsys fo ytilib -ats rof noitidnoc tneic us a si FLC fo ecnetsixe ehT )01( -lof sa )1( metsys niatrecnu raenilnon fo trap lanimon eht rof lortnoc lamitpo raenilnon eht redisnoc ew ,tsriF ..0 < eV f 0= e , BV t lortnoC lamitpO raenilnoN 3 .) ( d FLC fo ecnetsixe eht ,)4( metsys roF .noitcnuf dednuo b -nu yllaidar dna ,evitiso p ,elbaitnere id ylsuounitnoc a si hcihw ]1[ )FLC( noitcnuf vonupayL lortnoc yrartib = e , e = erehw -ra na si 0 = e taht seilpmi si ) ( )2( x )( t x = )t(e sa den ed rorre gnikcart eht || || V dna n 1R T V e V BV 0 te .srotcev rof mron naedilcuE eht si ]f erehw T ,0[ t 0 = || ) t( ie|| li mi swollof 0= )9( 0 = T T } T )e(q+ 2) eV( + eV { f f = po u sa ecnamrofre p gnikcart tcefre p eht eveihca ot sa os etairporppa na dn ot si evitcej bo lortnoc ehT .elbaitne -re id ylsuounitnoc si swollof sa )4( metsys raenilnon ot noitulos lamitpo-bus a edivorp ot decud ortni si ]4[ alumrof s gatnoS de id om ehT .)4( metsys rof rellort -noc elbats a sedivorp ]2[ alumrof s gatnoS .lareneg ni noitauqe BJH evlos ot elbisso pmi tsomla ro tluc id si ti revewoH .ecno ta lla noitidnoc laitini yreve rof melborp lortnoc lamitpo eht sevlos noitauqe laitrap BJH ehT )8( )1( metsys raenilnon eht rof iu ecneuqes tupni lortnoc x yrotcejart derised ehT nR d .elcyc gninrael ht-i eht setoned i erehw selcyc gninrael l la rof de sitas si )0( dx = )0( ix noitidnoc gnitteser laitini ehT 1 noitpmussA .tnem noit -norivne lortnoc elbatae per a rof yrassecen si 1 .regetni etin a si 1 eV B 2 T T 1 = u A -pmussa ,)1( metsys raenilnon niatrecnu eht gnidrageR sa nevig si wal lortnoc lamitpo eht ,stsixe )6( fo noitulos elbaitnere id ylsuounitnoc eht fI n ereH .tesbus eht sa snoitcnuf naiztihcspiL lac ol dna labolg eht edulcni lareneg ni yam hcihw noitcnuf deulav rotcev raenilnon )7( d] ) ( u ) ( T u + ) ) ( e ( q[ t ) (u fT f ni = )) ( ( t e V ] 9[ ) ( t e etats rorre tnerruc morf deniatbo eb nac dna e V B B e V ) e( q 0 = )t , e f e V + T T 1 ( 4 si )5( noitcnuf noitcnuf eulav eht sa ot derrefer ylnommoc si V erehw )6( evitcej bo dna )4( metsys evo ba morf noitauqe BJH ehT .wal lortnoc kcabdeef-etats a gnie b noitulos derised eht htiw noitcnuf RK-ssalc : ) ( erehw elbaitnere id ylsuounitnoc a si + +R nwonk si 1 nR nR : )t ,x( dna seitniatrecnu gniyrav-emit eht si 1 n mR erehw ,)t ,x( )t( = d sa dezirotcaf e b nac hcihw seitniatrecnu raenilnon eht si d ;t dna x tnemugra eht ot tce pser htiw snoitcnuf +R suounitnoc nwonk era n m R nR : )t ,x( B dna +R nR nR : )t ,x( noitcnuf raenilnon ;n < m erehw ,rotcev tupni lortnoc eht si mR u ;)1( metsys eht fo rotcev etats elbarusaem eht si R x erehw n )1( ,0 = ) ,0( f ])t ,x( )t( + u[)t ,x( B + )t ,x( f = d + u ()t , x( B + )t , x( f = x ) )esira ot ylekil si noisufnoc on nehw dettimo semitemos era stnemugra ,ytiverb fo ekas eht rof ,re pap siht tuohguorht( noitauqe gniwollof eht yb detneserper seitniatrecnu gniyrav-emit htiw metsys citsi -nimreted cimanyd raenilnon OMIM fo ssalc a redisnoC R nR eq )5( td )u T u + )e(q( 0 ) (u fT f ni = J =) + e( B = )t , e( B , )t ( d x :si lortnoc lamitpo fo noitcnuf evitcej bo ehT .)t , dx f t ,e( erehw ) t , d x + e( f noitalumroF melborP 2 i d)t , ie( T)t , ie( T i v 0 t 0 d] ) , i e ( + ) t , i e ( 1 i [ i ))0( i ( e V+ 0 t = )) ( i ( d])) ,e( + iu() , ie( B + i [ ieV f t t e V )11( ytre porp dna )61( wal gnitad pu ,)51( wal lortnoc ,1 noitpmussa ot gnidroccA )71( ot tcepser htiw tce e gninrael eht yltneuqesnoC .FEC otni detaroprocni osla si srorre gninrael cirtemarap fo mron 2L A .noitidnoc ztihcspiL labolg gniyfsitas tuo -htiw metsys raenilnon lareneg ot elbacilppa emehcs gni -nrael sekam osla tub lavretni etin a nihtiw setats metsys fo ssenetin eht seetnaraug ylno ton FEC ni ))t(e( V trap noitcnuf vonupayL lortnoC .FEC ni strap owt era erehT .selcyc gninrael evitucesnoc ot dednet -xe yltneuqesbus dna noitcnuf vonupayL morf detani -giro si )FEC( noitcnuf ygrene etisopmoC 3 krameR .noitite per gninrael ht- ta rorre gninrael cirtemarap eht si ) ( i t )t( i = i d] i i T ,noitin ed yB .)01( se sitas dna d] ) 1 i d] ) i ( i ( )1 T [ i 0 ([ eca rt ))t( 1 ie( V 0v 2 1 3 noitceS ni den ed FLC yrartibra na e b nac )41( ) (i [ t V erehw T eca rt t = = eca rt 0 v 2 t 1 + )) ( i ( t e V = )t( i E ) (1 v 2 + ))t ( ie( V 1 t i E )t( i E tE :sa elcyc gninrael .) )31( ht i eht ta si iE fo ecnere id eht ,)41( morF FEC fo ecnere id ehT :A traP .C traP ni devorp si slangis lortnoc lanretni eht fo ytre porp ssendednuo b-mroN .ecnamrofre p gnikcart tcefre p eht sevorp B traP .)FEC( noitcnuf ygrene etiso p -moc eht fo ecnere id eht fo ssenetin ed evitagen eht sevired A traP .strap eerht fo stsisnoc foorp ehT :fo orP )FEC( noitcnuf ygrene etiso pmoc evitagen-non a en eD t , dx + e( = )t ,e( erehw = ) ( ,])t ,e( + u[)t ,e( B + )t ,e( f te :si )1( metsys fo scimanyd rorre ehT hcaorppA lortnoC gninraeL lamitpo-buS dna FEC 4 )21( .ytin -ni ot sehcaorppa noititeper gninrael eht nehw ] fT ,0[ revo dednuob-mron si langis lortnoc eht dna rorre gni -kcart fo ecnegrevnoc esiwtniop dna dednuob eht eetna -raug 1A noitidnoc gnitteser rednu )9( wal lortnoc lamit -po dna )61 ,51( wal lortnoc gninrael ehT 1 meroehT .meroeht gniwollof eht yb nevig si emehcs lortnoc | | | | | ) e( q 2 || || || || | | || ||)e(q + |b| + |b| 2|| || | || pou|| || ||)e(q + 2b + |b| 2 en e D , deso porp fo ecnegrevnoc ehT .1 = i elcyc gninrael tsr eht morf ecnamrofre p gnikcart redisnoc eW .] fT ,0[ t 0 = )t( 0 sa tes si trap gninrael fo eulav laitini eht v tnatsnoc evitisop eht erehw ereH .etar gninrael eht si )61( = = f ne ht , T = || || dna R eV = b f .0 < ) 0e( eV dna , < |)e( B eV| era ereht < || 0e e|| nehw taht hcus ,0 > ,0 > ,elbaitne B |B V iB ie V )t , i ( i v + 1 i TT e i i -re id ylsuounitnoc si dna ,stnemugra lla ot tce pser 0 e =e e htiw suounitnoc era dna hto b ecniS .0 e tnio p a ta taht emussA dna 0 = 0e =e ,0 V e f < |f V .rorre gnikcart fo ssende swollof sa detad pu si dna trap lortnoc || gninrael eht si )t , ie( i ,)9( morf semoc hcihw elcyc gni ht i ta trap lortnoc lamitpo-bus eht si o,iu erehw -nrael )51( = = -no n a si ere h w , ) ( neh w ecneH . = e ecafrus eht rof tpecxe suounitnoc si po ,)9( wal lortnoc lamitpo-bus eht fo noitin ed eht morF -dnuo b eht morf dednuo b si pou ,tnatsnoc ni lamisetin e B e V|| 0 u BV .dednuo b si )9( wal lortnoc lamitpo-bus eht taht wohs ew ,txeN ) )t , ie( i t , ie( l,iu + )t , ie( o,iu ) )t , ie( l,iu t , ie( iu strap owt fo stsisnoc wal lortnoc detargetni ehT .0 V ecnis dednuob si )4( fo e rorre gnikcart )11( .deveihca eb l liw gnikcart tcefrep eht ,noziroh noititeper gninrael eht gnola FEC fo ecnegrevnoc lacitotpmysa eht gnitarts -nomed yB .detaulave eb nac selcyc gninrael detaeper ,0 ) ou B + ( eV f taht nees eb nac ti ,)9( wal lortnoc lamitpo-bus evoba eht morF 2 krameR ,emit emas eht tA .rorre gnikcart fo ssendednuo b eht morf derusne si trap lortnoc gninrael fo ssendednuo b ehT .lavretni emit etin ni suounitnoc si trap lortnoc gninrael eht ,etin si noitite per gninrael eht nehw ,)51( wal lortnoc eht fo noitcurtsnoc eht morf nees e b nac tI )42( ) . ) 2|| || (e c a r t 2 v 2 1 + || ||(ecart v 2 1 2 2 )92( 0 fT 2 1 ||)t , 1e( || 2|| 1 || v 1 1 1 . d 2|| u|| = ] f T, 0[ || u|| mron gniwollof eht sa den ed elcyc gninrael eht revo ytirohtua lortnoc eht fo ygrene latot eht redisnoc eW el orp lortnoc dednuob-mroN :C traP .ytin ni ot sehcaorppa noitite per gninrael eht sa yltcefre p yrot -cej art derised eht kcart nac etats metsys ehT .] f T , 0[ + )t , e( )t , e ( v TT v 2 ) || || (e c a r t + )t , 1e( 1 + 2 1 )t , 1e( )t , 1e( 1 1 v )t ,e( 1 TT v 2 ] 1 1 [e c a r t + ]))t , 1e( + T 1 t , 1e( 1 1,ou() , 1e( B + 1 [ 1eV = f ) ) (1 tE t orez ot segrevnoc osla rorre gnikcart eht ecneH noitcnuf ygrene etiso pmoc eht fo evitavired eht gnikaT )32( )82( ]f mi .0 = )t( ie li T ,0[ t 0 = ))t( 1 ie( V li mi . d] 1 T 1 [ ecart 0 v 2 1 t + ) (1 tV = si 1 ) (1 tE E noitcnuf ygrene ehT .dednuo b si elcyc gninrael tsr eht ta rorre gnikcart eht taht eetnaraug nac )9( wal lortnoc lamitpo -bus dna )51( wal lortnoc gninrael eht taht pets gniwol -lof eht ni evorp eW .) fo = ,erofereht ,noitcnuf dednuo bnu yllaidar si V ,FLC noitin ed eht morF .deetnaraug si ] fT ,0[ t 0 t i e( V 1 =i )) ( 1 t ie( V li mi k dna segrevnoc )) ( 1 )72( )) ( 1 1 =i t , 1 e( , t i e( V k mil 1 v = 1 T T ,1 = i nehW )t ( 1 E ) (k t E lk mi .dnuo b re ppu htiw seires gnisaercni-non a si ) ( k ecniS .stsixe ) ( k t E lk eroferehT mi ) (k t E ,] fT ,0[ t t E lk mi , .etar ecnegrevnoc eht evorpmi yam v niag gninrael regral a taht swohs ti ,)22( morF 4 krameR .etin si )t( 1E dedivorp elcyc gninrael yna rof derusne si )t( iE fo ssenetin ehT .0 ))t( 1 ie( V )22( 2 )62( )) ( 1 . t i e( V 1 =i k mil k )t ( 1 E d 2|| ) t , i e ( || 2|| i || v 0 t ) (i tE k nehW =) i t , ie( T)t , ie( T i evah ew , ) ( 2 2 ,)12( dna )81( ot gnidroccA = || t , i e || | | i || 1 =i )52( . ))t( 1 i e( V ) (i 2 =i k k )t ( 1 E + ) (1 )12( 2 i .)t , ie( T i v )t( T e e tE tE = ) (k tE :si elcyc gni ]) 2 1 i + i 2 T T + )t , i ( )t , i ( i i v i 1 i i )t , i ( i )t , ( v 2 e e = = ( ) T 1 i i ([ecart ([ -nrael ht- k ta FEC eht )22( gniwollof ,0 )t( iE ecniS ecnegrevnoc gninraeL :B traP i }] 1 i 1 T [ecart ] i gnidroccA )02( i T eca rt{ v 2 1 1 .nonemonehp emit epacse etin eht tneverp nac emehcs lortnoc desoporp eht taht os elcyc gninrael hcae ta dednuob si rorre gnikcart ehT 5 krameR eV .) ( i ( )61( wal etad pu gninrael eht ot t FLC fo ssendednuo b eht morf semoc rorre gnikcart fo )91( ) )81( . 1 nR y dna 1 mR v , n mR Q erehw vQ Ty = )Q Tvy(ecart ecart fo ytreporp gniwollof eht etoN . )t , i e( i i i v T)t , e( T t , i e( 1 i i )t , i e( i = )t( ssendednuo b ehT .] fT ,0[ lavretni emit etin eht ni dednuo b si fT 0 )t( 1E eroferehT .] fT ,0[ t 0 v 2 ,noitcnuf suounitnoc a si )t( ecniS ) 2|| ||(ecart 1 d) ( 0 t s|| i u|| tnere iD .| ) t ( u | ] f T , 0[ xa m t = s|| i u|| en eD .sesac )33( )t ( u + )t(s oc21 + 3y y1.0 = y owt evo ba ni stupni lortnoc eht erapmoc su tel woN .1 = k nehw noitite per gninrael emas eht htiw derapmoc regral osla si rorre gnikcart mumi -xam eht ,emit emas eht tA .dnuo b rorre de ice pserp eht hcaer ot dedeen era snoitite per gninrael erom ,taht nees e b nac tI .2 .giF ni nwohs si noziroh noitite per gni -nrael gnola el orp rorre gnikcart ehT .1000.0 e b ot nes -ohc si k rellams a ,deriuqer si tro e lortnoc ssel nehW .deredisnoc si metsys gn uD citoahc gniwollof eht ,d ohtem lort -noc gninrael deso porp eht fo ssenevitce e eht wohs oT elpmaxE evitartsullI 5 .elcyc gninrael yreve ta dednuo b syawla si trap lortnoc lamitpo-bus eht esuace b derus -ne si tupni lortnoc eht fo ssendednuo b-mron eht ecneh 1 = k nehw noziroh noititeper gninrael gnola rorre gnikcart fo ecnegrevnoc ehT :1 erugiF 10 3 )23( , d 2|| || 0 fT 2 M 0 .tnedive si tce e gninrael eht hcihw morf ,1 .giF ni nwohs si noz -iroh noitite per gninrael gnola el orp rorre gnikcart ehT .detceles si 1 = k ,ecnegrevnoc rorre gnikcart tsaf rof ,tsriF .deredisnoc era sgnithgiew tnere id htiw noitcnuf evitcej bo eht ,ecnamrofre p lortnoc eht erapmoc oT .500.0 =0 e b ot nesohc si dnuo b rorre eht , elpmaxe siht nI )53( 0 || ) t ( k || e ] f T , 0[ xam t .e.i ,dnuob rorre den ed-erp eht sehcaer rorre gnikcart eht nehw desaec si etadpu gninraeL .semit etin ni detaeper eb yl drah nac elcyc gninrael eht ,noitacilppa laer nI 6 krameR .tro e lortnoc ssel dna gnikcart rette b neewte b ecnam -rofre p eht secnalab hcihw rotcaf ytlane p a si k erehw )43( d] u + ) 2e + 1e( k[ 0 2 2 2 2 =J )03( si )33( metsys eht fo noitcnuf evitcej bo ehT . 1e + ) 2e + 1ec( = V e b ot nesohc si noitcnuf vonupayL lortnoc ehT .] 2 , 0[ si d oire p gnikcart ehT . ])t3(soc3 ,)t3(nis[ yrotcej art nevig eht wollof ot ot si evitcej bo ehT T 2 2 ])t( 2x ,)t( 1x[ etats metsys eht evird .ytniatrecnu cirtemarap nwonknu T eht si )t(soc21 ereH .0 = )t(u nehw roivahe b citoahc swohs dna metsys gniyrav-emit raenilnon a si hcihw 10 Error 10 10 10 2 1 0 1 2 4 maximum tracking error at each learning cycle when k=1 6 8 10 12 Learning Repetition 14 16 18 d 2||)t , e( || 2|| || d 2|| l , u|| fT fT = 0 ] f T , 0[ || l, u|| -dnuo b e hT . )t , e( = u ] f T , 0[ t ecniS . < 2M ||)t ,e( || xam sa detoned si hcihw ,||)t ,e( || fo ssendednuo b eht ot sdael ||)t(e|| fo ssende j d k,2 fT0 d 2|| || fT0 si os ,dednuo b si )13( j , d k,2 0 fT 0 fT fT 0 d| k,j | 1 M 2 + d | k , j a| 2 j d k,2 0 fT 0 d| k,j | | k,j | 0 fT 2+ d 2| k , j a| fT j d k,2 0 fT , 1n , . . . ,1 = k ,m , . . . ,1 = j rof 1M ] fT ,0[ t |)t( k,j | xam taht emussA . k,j dna d| k,ja| fT0 fo ssendednuo b eht morf derusne si d| k,j | 0 fT fo ssendednuo b ehT . 1n , . . . ,1 = k ,m , . . . ,1 = j k,j} { = k,j , k,j} { = k,j en eD .dednuo b osla si d| k,ja| 0 ,L . 1n , . . . ,1 1 2L ecniS fT k ,m , . . . ,1 = j rof dednuob si d 2| k,ja| fT0 ecneh = k,j fT , M d 2| k , j a| 0 = d] [ecart T 0 fT en e D M ) f (1 ot , 1n , . . . ,1 = k ,m , . . . ,1 = j , k,j} { = k,ja .)t( 1E fo eulav mumixam eht si M erehw T E ) f T ( E d] [e c a r t 0 sehcaorppa noitite per gninrael ,ytin ni T fT nehW .snoitite per gninrael etin rof derusne si wal lortnoc fo ssendednuo b-mron eht ecneH .dednuo b si trap lort -noc lamitpo-bus ,dednuo b si rorre gnikcart eht ecnis )5791( ..C.D notgnihsaW ,.proC .lbuP erehpsimeH ,lort -noC lamitpO deilppA oH.H.Y dna nosyrB .E.A )8991(,8441 5441pp,11.on ,43.lov , acitamotuA ]8[ ]9[ 1000.0 = k nehw noziroh noitite -per gninrael gnola tupni lortnoc mumixam ehT :4 erugiF 5 10 15 20 25 30 35 ,lortnoc gninrael evitareti htiw smetsys raenilnon emit etercsid fo tsubor dna ecnegrevnoC ,gnaW .W.D )5991( ,2411 8311pp ,6.on ,64.lov,lortnoC .tamotuA .snarT EEEI ,tnairavni-emit raenil fo ssalc a rof mhtir ]7[ )2991(,1221 5121pp ,82.lov , -ogla lortnoc gninrael emit-etercsid A baaS.S.S acitamotuA ,smet ]6[ maximum control input at each learning cycle when k=0.0001 -sys cimanyd raenilnon fo ssalc a rof yroeht lortnoc gni -nrael evitareti nA naN.K dna eeL.S.J ,cuK.Y.T .)4891( ,041 321.pp ,1.lov ,smet -syS citoboR .J ,gninrael yb tsubor fo noitarepo gniret ]5[ )9991( .42-41 ,1 -teB ,ikazayiM .F dna arumawaK .S ,otomirA.S lortnoC fo lanruoJ naisA ,evitceps ]4[ -re p noziroh gnidecer dna noitcnuf vonupayL lortnoc A :lortnoc lamitpo raenilnoN ,.la te ,sbmirP.A.J 1 = k nehw noziroh noitite -per gninrael gnola tupni lortnoc mumixam ehT :3 erugiF 10 15 0 2 4 6 8 10 12 14 16 18 20 )9991( .9401-2401 ,)5(44 lortnoC citamotuA .snarT EEEI ,tfarcecaps digir a fo noitazil ]3[ -ibats lamitpo esrevnI sartoisT.P dna citsirK .M .)9891( ,174-264 ,12 , .zim ]2[ -itpO .rtnoC .J MAIS ,ytiliballortnoc citotpmysa fo .)7991( ,7991c,regnirpS noitaziretcarahc ekil-vonupayL A ,.D .E ,gatnoS :kroY weN ;:nodnoL , lortnoc raenilnon evitcurtsnoC ,civotokoK .V.P dna civoknaJ .M ,erhclupeS.R ]1[ maximum control input at each learning cycle when k=1 secnerefeR .stluser noitalumis yb demr noc nee b sah emehcs deso porp eht fo ytidilav ehT . deetnaraug si lan -gis lortnoc fo ssendednuo b-mron eht emit emas eht tA os noziroh noitite per gninrael gnola decnahne si ecnam -rofre p lortnoc ehT .seitniatrecnu cirtemarap gniyrav -emit nwonknu eht eldnah ylevitce e nac ,dnah rehto eht no ,trap lortnoc gninrael ehT .ecnabrutsid tupni ot tce pser htiw ssentsubor eht ecnahne ot sa os metsys cimanyd eht fo nigram ytilibats sedivorp osla emehcs lortnoc lamitpo-bus ehT .tro e lortnoc eht fo edutin .yllacitotpmysa deveihca e b nac gnikcart tcefre p taht 1000.0 = k nehw noziroh noititeper gninrael gnola rorre gnikcart fo ecnegrevnoc ehT :2 erugiF 10 3 -gam eht dna rorre gnikcart eht fo etar ecnegrevnoc eht egnahc ylevitce e ot dezilitu si alumrof s gatnoS no desab lortnoc lamitpo-buS .seitniatrecnu cirtemarap gniyrav-emit eht htiw smetsys raenilnon fo ssalc a rof ecnamrofre p lortnoc lamitpo-bus htiw gnikcart etats tcefre p eht eveihca nac d ohtem deso porp ehT .smet -sys lortnoc gninrael lamitpo-bus fo sisylana dna ngised eht etatilicaf ot krowemarf a sedivorp hcihw ,decud ort -ni si )FEC( noitcnuf ygrene etiso pmoc eht fo aedi ehT .re pap siht ni deso porp si lortnoc lamitpo-bus raenil -non dna lortnoc gninrael gnitargetni fo d ohtem wen A .tro e lortnoc eht fo edutingam eht dna rorre gnikcart eht fo etar ecnegrevnoc eht egnahc ylevitce e nac ew , k rotcaf ytlane p eht fo eulav eht gninut yb ,drow a nI .esac remrof eht fo flah naht ssel level rewol a ta tpek e b nac tro e lortnoc mumixam eht ,derreferp si tro e lortnoc ssel ,.e.i ,1000.0 = k ne h W .egral etiuq era snoitite per gninrael wef tsr .ylevitce pser eht ta stupni lortnoc mumixam eht ,derreferp si ecneg -revnoc gnikcart tsaf ,.e.i ,1 = k nehW 1000.0 = k dna 1 = k rof 4 .giF dna 3 .giF ni nwohs era noisulcnoC 6 10 15 20 25 30 10 Error 10 10 10 20 25 30 35 40 45 50 55 5 2 1 0 1 5 maximum tracking error at each learning cycle when k=0.0001 10 15 20 Learning Repetition 25 30 35
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Rutgers >> 640 >> 252 (Fall, 2008)
ARTICLE IN PRESS Journal of Theoretical Biology 243 (2006) 214221 www.elsevier.com/locate/yjtbi External noise and feedback regulation: Steady-state statistics of auto-regulatory genetic network Bing-Liang Xua, Yi Taob, b College of Grassland Scie...
Rutgers >> 640 >> 252 (Fall, 2008)
Available online at www.sciencedirect.com Systems 1 , Eduardo Sontagb;2 , Murat Arcakc;3 SYSTeMS, Ghent University, Technologiepark 91...
Rutgers >> 640 >> 252 (Fall, 2008)
Nonlinear Analysis 60 (2005) 1111 1150 www.elsevier.com/locate/na On the representation of switched systems with inputs by perturbed control systems J.L. Mancilla-Aguilara , R. Garcab , E. Sontagc,1 , Y. Wangd,2 a Department of Mathematics, Faculty...
Rutgers >> 640 >> 252 (Fall, 2008)
Molecular Systems Biology and Control Eduardo D. Sontag Department of Mathematics and BioMaPS Institute for Quantitative Biology Rutgers University, New Brunswick, NJ 08903, USA E-mail: sontag@math.rutgers.edu Abstract This paper, prepared for a tut...
Rutgers >> 640 >> 252 (Fall, 2008)
Proceedings of the 45th IEEE Conference on Decision & Control Manchester Grand Hyatt Hotel San Diego, CA, USA, December 13-15, 2006 WeA10.4 Filtered Lyapunov functions and their applications in the stability analysis of nonlinear systems Stefano Ba...
Rutgers >> 640 >> 252 (Fall, 2008)
Proceedings of the 46th IEEE Conference on Decision and Control New Orleans, LA, USA, Dec. 12-14, 2007 FrA04.5 Realization Theory of Stochastic Jump-Markov Linear Systems Mih ly Petreczky a Eindhoven University of Technology, The Netherlands M.Petr...
Rutgers >> 640 >> 252 (Fall, 2008)
COMMENTS ON \"SOME RESULTS ON POLE-PLACEMENT AND REACHABILITY\"* Eduardo D. Sontag* Department of Mathematics Rutgers University New Brunswick, NJ 08903, U.S.A. ABSTRACT We present various comments on a question about systems over rings posed in a rec...
Rutgers >> 640 >> 252 (Fall, 2008)
Proceedings of the 46th IEEE Conference on Decision and Control New Orleans, LA, USA, Dec. 12-14, 2007 FrB14.1 Towards ISS Disturbance Attenuation for Randomly Switched Systems Debasish Chatterjee and Daniel Liberzon Abstract We are concerned with...
Rutgers >> 640 >> 252 (Fall, 2008)
Proceedings of the 45th IEEE Conference on Decision & Control Manchester Grand Hyatt Hotel San Diego, CA, USA, December 13-15, 2006 ThB12.5 A Model Reduction Algorithm for Hidden Markov Models Georgios Kotsalis, Alexandre Megretski, Munther A. Dahl...
Rutgers >> 640 >> 252 (Fall, 2008)
Proceedings of the 46th IEEE Conference on Decision and Control New Orleans, LA, USA, Dec. 12-14, 2007 ThB17.2 iISS gain of dissipative systems Bayu Jayawardhana , Andrew R. Teel, Eugene P. Ryan Abstract For a class of dissipative nonlinear syste...
Rutgers >> 640 >> 252 (Fall, 2008)
...
Rutgers >> 640 >> 252 (Fall, 2008)
Proceedings of the 42nd IEEE Conference on Decision and Control Maui, Hawaii USA, December 2003 TuP05-4 Observability for Hybrid Systems Andrea Balluchi PARADES Via S. Pantaleo, 66, 00186 Roma, Italy balluchi@parades.rm.cnr.it Luca Benvenuti DIS, ...
Rutgers >> 640 >> 252 (Fall, 2008)
Proceedings of the 45th IEEE Conference on Decision & Control Manchester Grand Hyatt Hotel San Diego, CA, USA, December 13-15, 2006 ThIP9.11 Summability criteria for stability of sets for sampled-data nonlinear inclusions Dragan Nei sc Antonio Lora...
Rutgers >> 640 >> 252 (Fall, 2008)
Stabilization of Linear Systems with Input Constraints1 Li Qiu Department of Electrical and Electronic Engineering Hong Kong University of Science and Technology Clear Water Bay, Kowloon, Hong Kong eeqiu@ee.ust.hk Daniel E. Miller Department of Elec...
Rutgers >> 640 >> 252 (Fall, 2008)
...
Rutgers >> 640 >> 252 (Fall, 2008)
Proceedings of the 46th IEEE Conference on Decision and Control New Orleans, LA, USA, Dec. 12-14, 2007 FrC09.2 Sensorless PBC of induction motors: A separation principle from ISS properties e Jaime A. Moreno and Gerardo EspinosaP rez Abstract In th...
Rutgers >> 640 >> 300 (Fall, 2008)
MATH 300. INTRODUCTION TO MATHEMATICAL REASONING. FALL 2006. HOME ASSIGNMENT 8 (LECTURES 17,18) 1. Reading: Sect.3.3, 3.4,3.5. Preparation for Quiz 3 (Tue, November 7). 2. Home assignment (Due Tue, November 7; to submit). Sect.3.3. 1,2(b,c), 3(a,d),...
Rutgers >> 640 >> 524 (Fall, 2008)
MATH 300. INTRODUCTION TO MATHEMATICAL REASONING. FALL 2006. HOME ASSIGNMENT 8 (LECTURES 17,18) 1. Reading: Sect.3.3, 3.4,3.5. Preparation for Quiz 3 (Tue, November 7). 2. Home assignment (Due Tue, November 7; to submit). Sect.3.3. 1,2(b,c), 3(a,d),...
Rutgers >> 640 >> 300 (Fall, 2008)
MATH 300. INTRODUCTION TO MATHEMATICAL REASONING. FALL 2006. HOME ASSIGNMENT 10 (LECTURES 21,22). 1. Reading: Sect.4.3,4.4. 2. Preparation for Midterm 2 (Thursday, November 16) 2. Home assignment (Due Tue, November 21; to submit). Sect.4.3. 1(b,d,e,...
Rutgers >> 640 >> 524 (Fall, 2008)
MATH 300. INTRODUCTION TO MATHEMATICAL REASONING. FALL 2006. HOME ASSIGNMENT 10 (LECTURES 21,22). 1. Reading: Sect.4.3,4.4. 2. Preparation for Midterm 2 (Thursday, November 16) 2. Home assignment (Due Tue, November 21; to submit). Sect.4.3. 1(b,d,e,...
Rutgers >> 640 >> 321 (Fall, 2008)
Math 321 Assignment 10 Solutions 61.1 At 0 mph, = 5280/16 = 330 cars/mile. At 10 mph, = 330/2 cars/mile. At 20 mph, = 330/3 cars/mile. The general formula is = 330/(1 + u/10), where u is the velocity of a car. Now q = u. To get q as a function of...
Rutgers >> 640 >> 321 (Fall, 2008)
Math 321 Assignment 5 Solutions 32.3 (a) N (t + t) N (t) = RtN (t) + 1000, where R = b d. (b) Using the equation Nm+1 = (1 + Rt)Nm + 1000, we have N1 = (1 + Rt)N0 + 1000 N2 = (1 + Rt)N1 + 1000 = (1 + Rt)2 N0 + 1000(1 + Rt) + 1000 N3 = (1 + Rt)N2 +...
Rutgers >> 640 >> 321 (Fall, 2008)
Math 321 Assignment 8 Solutions 50.3 The phase plane equation is F (a bF cS) dF = . dS S(k + F ) dF/dS = 0 along F = 0 and bF + cS = a. dF/dS = along S = 0 and F = k/. dF/dt = F (a bF cS) > 0 if bF + cS < a and < 0 if bF + cS > a. dS/dt = S(k +...
Rutgers >> 640 >> 321 (Fall, 2008)
Math 321 Assignment 11 Solutions 71.1 Using the method of characteristics, = max /2 along the curve dened by dx/dt = (dq/d)(max /2). Integrating, this curve is the line x(t) = (dq/d)(max /2)t + c. Now (x, 0) = max /2 at x = x0 /2. Hence, x(0) = c = ...
Rutgers >> 640 >> 321 (Fall, 2008)
Math 321 Exam 1 Solutions 1 a) (1/2)d2 x/dt2 = 8x 5dx/dt. b) The above equation is equivalent to: d2 x/dt2 + 10dx/dt + 16x = 0. Looking for solutions of the form ert , we nd that r must satisfy r2 + 10r + 16 = (r + 8)(r + 2) = 0. Hence r = 8 and r ...
Rutgers >> 640 >> 321 (Fall, 2008)
Math 321 Assignment 2 Solutions 13.2. (a) When c2 = 4mk, the solution has the form x(t) = ect/(2m) (At + B). We rst note that x(t) can equal zero only for t = B/A. Hence there can be at most one time when the mass passes through its equilibrium posit...
Rutgers >> 640 >> 321 (Fall, 2008)
Math 321 Assignment 1 Solutions 4.2 Using Newtons law to describe the motion in the horizontal and vertical directions, we have d2 y d2 x = 0, = g. dt2 dt2 Assuming that at time t = 0 the mass is at the end of the table (we denote this position by x ...
Rutgers >> 640 >> 321 (Fall, 2008)
Math 321 Assignment 12 Solutions 77.1 [q] 1 u(1 ) 0 u(0 ) 1 (1 1 /max ) 0 (1 0 /max ) dxs = = = umax dt [] 1 0 1 0 2 2 (1 0 ) (1 0 )/max = umax [1 (1 + 0 )/max ]. = umax 1 0 The density wave velocities are (dq/d)(0 ) and (dq/d)(1 ) and th...
Rutgers >> 640 >> 321 (Fall, 2008)
Math 321 Assignment 9 Solutions 57.2a) dx/dt = u(x, t) = (30x + 30L)/(15t + L), x(0) = L/2. Then dt 1 1 dx = . Hence ln |30x + 30L| = ln |15t + L| + C. 30x + 30L 15t + L 30 15 Now x(0) = L/2 implies 1 1 ln |45L| = ln |L| + C, 30 15 so C = (1/30) ln(4...
Rutgers >> 640 >> 336 (Fall, 2008)
INPUT-TO-STATE STABILITY FOR DISCRETE-TIME NONLINEAR SYSTEMS Zhong-Ping Jiang Eduardo Sontag ,1 Yuan Wang ,2 Department of Electrical Engineering, Polytechnic University, Six Metrotech Center, Brooklyn, NY 11201. Department of Mathematics, Rutger...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005 Seville, Spain, December 12-15, 2005 1 TuB16.2 Stability of Nonlinear Switched Systems on the Plane Ugo Boscain, SISSA-ISAS, via Beirut 2-4, 3...
Rutgers >> 640 >> 336 (Fall, 2008)
Constr. Approx. CONSTRUCTIVE APPROXIMATION c 1994 Springer-Verlag NewYork Inc. Rates of Convex Approximation in Non-Hilbert Spaces Michael J. Donahue, Leonid Gurvits, Christian Darken, and Eduardo Sontag Abstract. This paper deals with sparse appro...
Rutgers >> 640 >> 336 (Fall, 2008)
Separating Bi-Chromatic Points by Parallel Lines Tetsuo Asano John Hershberger Diane Souvaine Jnos Pach a Eduardo Sontag Subhash Suri March 24, 2001 Abstract Given a 2-coloring of the vertices of a regular n-gon P , how many parallel lines are neede...
Rutgers >> 640 >> 336 (Fall, 2008)
Measurement to Error Stability: a Notion of Partial Detectability for Nonlinear Systems Brian P. Ingalls Control and Dynamical Systems, California Institute of Technology, CA ingalls@cds.caltech.edu Eduardo D. Sontag Dept. of Mathematics, Rutgers Uni...
Rutgers >> 640 >> 336 (Fall, 2008)
FOR NEURAL NETWORKS, FUNCTION DETERMINES FORM Francesca Albertini(*) Eduardo D. Sontag Department of Mathematics Rutgers University, New Brunswick, NJ 08903 E-mail: albertin@pdmat1.unipd.it, sontag@hilbert.rutgers.edu (*)Also: Universita degli Studi ...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 40th IEEE Conference on Decision and Control Orlando, Florida USA, December 2001 ThA09-1 Output Feedback Disturbance Attenuation with Robustness to Nonlinear Uncertain Dynamics via State-Dependent Scaling Hiroshi Ito and Zhong-Pi...
Rutgers >> 640 >> 336 (Fall, 2008)
Attractors under perturbation and discretization Lars Grune Fachbereich Mathematik J.W. Goethe-Universitat Postfach 11 19 32 60054 Frankfurt a.M., Germany gruene@math.uni-frankfurt.de essary and su cient condition for the convergence of attractors ...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005 Seville, Spain, December 12-15, 2005 ThC12.2 Performance analysis of saturated systems via two forms of differential inclusions Tingshu Hu, An...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 46th IEEE Conference on Decision and Control New Orleans, LA, USA, Dec. 12-14, 2007 ThPI23.16 Stability, Stabilization and Observers of Linear Control Systems on Time Scales Zbigniew Bartosiewicz, Ewa Piotrowska and Magorzata Wyr...
Rutgers >> 640 >> 336 (Fall, 2008)
SOME CONNECTIONS BETWEEN CHAOTIC DYNAMICAL SYSTEMS AND CONTROL SYSTEMS Francesca ALBERTINI, Eduardo D. SONTAG SYCON- Rutgers Center for Systems and Control Department of Mathematics, Rutgers University, New Brunswick, NJ 08903 Abstract. This paper sh...
Rutgers >> 640 >> 336 (Fall, 2008)
FEEDBACK STABILIZATION OF NONLINEAR SYSTEMS Eduardo D. Sontag Abstract This paper surveys some well-known facts as well as some recent developments on the topic of stabilization of nonlinear systems. 1 Introduction In this paper we consider probl...
Rutgers >> 640 >> 336 (Fall, 2008)
k xh y u, xf x . l la rof ) kd ( = kd dna ) kd kd ( = 1+kd taht hcus ,ylevitcepser ,secneuqes tupni dna etats derised eht sa ot derrefer ,RI kd dna X kd secneuqes dednuob tsixe ereht fi stuptuo derised fo ecneuqes u x y >r r< x x C .h . ,....
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 42nd IEEE Conference on Decision and Control Maui, Hawaii USA, December 2003 FrP11-1 Results on Discrete-Time Control-Lyapunov Functions Christopher M. Kelletta a 1 and Andrew R. Teelb 2 Department of Electrical and Electronic...
Rutgers >> 640 >> 336 (Fall, 2008)
J. Math. Biol. 49: 627634 (2004) Digital Object Identier (DOI): 10.1007/s00285-004-0291-5 Mathematical Biology German Enciso Eduardo D. Sontag On the stability of a model of testosterone dynamics Received: 11 April 2004 / Published online: 7 Octo...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005 Seville, Spain, December 12-15, 2005 WeB02.1 Transverse Feedback Linearization of Multi-Input Systems Christopher Nielsen and Manfredi Maggior...
Rutgers >> 640 >> 336 (Fall, 2008)
CONTROLLABILITY AND LINEARIZED REGULATION Eduardo D. Sontag* Department of Mathematics Rutgers University New Brunswick, NJ 08903 ABSTRACT A nonlinear controllable plant, under mild technical conditions, admits a precompensator with the following ...
Rutgers >> 640 >> 336 (Fall, 2008)
...
Rutgers >> 640 >> 336 (Fall, 2008)
...
Rutgers >> 640 >> 336 (Fall, 2008)
JOURNAL OF COMPUTATIONAL BIOLOGY Volume 14, Number 7, 2007 Mary Ann Liebert, Inc. Pp. 927949 DOI: 10.1089/cmb.2007.0015 A Novel Method for Signal Transduction Network Inference from Indirect Experimental Evidence RKA ALBERT,1 BHASKAR DASGUPTA,2 RIC...
Rutgers >> 640 >> 336 (Fall, 2008)
SOME CONNECTIONS BETWEEN STABILIZATION AND FACTORIZATION Eduardo D. Sontag SYCON - Rutgers Center for Systems and Control Department of Mathematics, Rutgers University, New Brunswick, NJ 08903 e-mail: sontag@fermat.rutgers.edu Appeared as Proc. IEEE...
Rutgers >> 640 >> 336 (Fall, 2008)
Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics Thomas Natschl ger & Wolfgang Maass a Institute for Theoretical Computer Science Technische Universit t Graz, Austria a tnatschl,maass @igi.tu-graz.ac.at Edu...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005 Seville, Spain, December 12-15, 2005 ThA10.4 The Realization Problem for Hidden Markov Models: The Complete Realization Problem M. Vidyasagar ...
Rutgers >> 640 >> 336 (Fall, 2008)
Journal of Dynamical and Control Systems, Vol. 10, No. 3, July 2004, 391412 ( c 2004) UNIFORM GLOBAL ASYMPTOTIC STABILITY OF DIFFERENTIAL INCLUSIONS D. ANGELI, B. INGALLS, E. D. SONTAG, and Y. WANG Abstract. Stability of dierential inclusions dened ...
Rutgers >> 640 >> 336 (Fall, 2008)
...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 40th IEEE Conference on Decision and Control Orlando, Florida USA, December 2001 FrP03-4 ...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 46th IEEE Conference on Decision and Control New Orleans, LA, USA, Dec. 12-14, 2007 FrA05.3 Adaptive NN Control of Strict-feedback Systems Using ISS-modular Approach Beibei Ren, Shuzhi Sam Ge , and Tong Heng Lee Abstract In this ...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005 Seville, Spain, December 12-15, 2005 TuB17.4 Tracking and disturbance rejection for passive nonlinear systems Bayu Jayawardhana Abstract In t...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 46th IEEE Conference on Decision and Control New Orleans, LA, USA, Dec. 12-14, 2007 ThC18.1 Robust MIMO Control of a Parallel Kinematics Nano-Positioner for High Resolution High Bandwidth Tracking and Repetitive Tasks Jingyan Don...
Rutgers >> 640 >> 336 (Fall, 2008)
A Notion of Input to Output Stability Eduardo Sontag Dept. of Mathematics, Rutgers University New Brunswick, NJ 08903 sontag@control.rutgers.edu and Yuan Wang Dept. of Mathematics, Florida Atlantic University Boca Raton, FL 33431 ywang@math.fau.edu ...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005 Seville, Spain, December 12-15, 2005 WeB02.5 Exogenous feedback linearization of discrete-time systems E. Aranda-Bricaire and C.H. Moog Abstr...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 2005 Seville, Spain, December 12-15, 2005 TuC16.5 On Input-to-State Stability of Impulsive Systems Jo o P. Hespanha a Electrical and Comp. Eng. Dep...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 42nd IEEE Conference on Decision and Control Maui, Hawaii USA, December 2003 FrA14-2 Scaling Supply Rates of ISS Systems for Stability of Feedback Interconnected Nonlinear Systems Hiroshi Ito Department of Control Engineering and...
Rutgers >> 640 >> 336 (Fall, 2008)
Shattering all sets of k points in general position requires (k 1)/2 parameters Eduardo D. Sontag Department of Mathematics Rutgers University, New Brunswick, NJ 08903 Abstract For classes of concepts dened by certain classes of analytic functions ...
Rutgers >> 640 >> 336 (Fall, 2008)
Input-Output-to-State Stability Mikhail Krichmanand Eduardo D. Sontag Dep. of Mathematics, Rutgers University, NJ {krichman,sontag}@math.rutgers.edu Yuan Wang Dept. of Mathematics, Florida Atlantic University, FL ywang@control.math.fau.edu Abstract ...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 45th IEEE Conference on Decision & Control Manchester Grand Hyatt Hotel San Diego, CA, USA, December 13-15, 2006 ThIP10.1 Real-Time Control of an Autonomous Control System Based on Feasibility Analysis D.H.A. Maithripala, Suhada ...
Rutgers >> 640 >> 336 (Fall, 2008)
Proceedings of the 42nd IEEE Conference on Decision and Control Maui, Hawaii USA, December 2003 FrA07-3 Moving Horizon Monte Carlo State Estimation for Linear Systems with Output Quantization Hernan Haimovich, Graham C. Goodwin and Daniel E. Queved...
Rutgers >> 640 >> 336 (Fall, 2008)
Nonlinear observability and an invariance principle for switched systems Joo P. Hespanha a Dept. of Electr. & Comp. Eng. Univ. of California, Santa Barbara hespanha@ece.ucsb.edu Daniel Liberzon Coordinated Science Lab. Univ. of Illinois, Urbana-Cham...
Rutgers >> 640 >> 336 (Fall, 2008)
BILINEAR REALIZABILITY IS EQUIVALENT TO EXISTENCE OF A SINGULAR AFFINE DIFFERENTIAL I/O EQUATION Eduardo D. Sontag* Department of Mathematics Rutgers University New Brunswick, NJ 08903 (201)932-3072 sontag@fermat.rutgers.edu ABSTRACT For continuous ...
Rutgers >> 640 >> 336 (Fall, 2008)
ANAlysIs Transcriptional control of human p53-regulated genes Todd Riley*, Eduardo Sontag, Patricia Chen* and Arnold Levine* Abstract | The p53 protein regulates the transcription of many different genes in response to a wide variety of stress signa...
Rutgers >> 640 >> 336 (Fall, 2008)
TIME-OPTIMAL CONTROL OF MANIPULATORS Eduardo D. Sontag* and Hector J. Sussmann* Department of Mathematics Rutgers, The State University New Brunswick, NJ 09803 ABSTRACT This paper studies time-optimal control questions for a certain class of nonlin...
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