Auto-Tuning of PID Controllers for Second Order Unstable Process Having Dead Time

Size: px
Start display at page:

Download "Auto-Tuning of PID Controllers for Second Order Unstable Process Having Dead Time"

Transcription

1 Joural of Chmical Egirig of Jaa, Vol. 3, No. 4, , 1999 Rsarch Par Auo-uig of PID Corollrs for Scod Ordr Usabl Procss Havig Dad im HSIAO-PING HUANG AND CHAN-CHENG CHEN Darm of Chmical Egirig, Naioal aiwa Uivrsiy, aii 1617, aiwa, R.O.C. Kywords: Dadim, Rlay Fdback, Usabl Pol, Sabl Pol, PID A auo-uig rocdur for PID corollrs for a mor gral class of usabl rocss ha has scod-ordr dyamics is rsd. hs scod-ordr dyamics ar rrsd by a modl havig boh sabl ad usabl ols oghr wih a aar dad im. A biasd rlay fdback s is usd o gra a cosa limi cycl for idifyig his modl. Cririo o disiguish a scod-ordr modl from h firs-ordr o is dvisd. Uo fiishig h idificaio, siml uig ruls ar rovidd o u h aramrs of PID corollrs. hs siml uig ruls ar drivd from h auhors rvious work rgardig corollr dsig for o loo usabl rocsss. Iroducio I rc yars, dvloms i auo-uig of idusrial PID corollrs hav focusd o corol of o loo sabl rocsss. For auo-uig, h auouig s of Åsröm ad Hägglad (1984) is usually usd o obai simaios of ulima gai ad ulima frqucy. Afr obaiig such ulima rsuls, ihr Z-N or Z-N rlad uig mhods ar alid o calcula h aramr sigs for idusrial corollrs (Hägglad ad Åsröm, 1991; Åsröm ad Hägglad, 1995). Rcly, aramric modls hav also b usd so ha modl-basd uig mhods ca b alid o dsig corollrs (Huag al., 1996). I coras o h dvlom of auo-uig for sabl rocsss, hr is o as so much liraur (Wag al., 1995; Kavdia ad Chidamaram, 1996) addrssig auo-uig for h corol of o loo usabl rocsss. h dficicy of liraur i his asc is arly du o h fac ha rocsss wih usabl dyamics ar o courd so of as hos wih sabl os. Bu, o loo usabl dyamics idd ar courd i h oraios of may bioracors or xohrmic racors (Ual al., 1974; Ual al., 1976; Hoo ad Kaor, 1985; Agrawal ad Lim, 1986). hus, o hac racicig corol for hs rocsss, auo-uig for a PID corollr would b hlful. Bsids, o accou for h dficicy i dvlom i auo-uig for usabl rocsss, hr ar a fw chical bolcks o b addrssd: Rcivd o Jauary 18, Corrsodc cocrig his aricl should b addrssd o H.-P. Huag ( addrss: huaghc@ccms.u.du.w). 1. h ulima gai ad frqucy obaid from rlay fdback ss ar o dircly rlad o corollr uig such as Z-N ruls for sabl rocsss. As a rsul, a aramric modl bcoms idissibl for uig corollrs. I h rord works of Wag al. (1995) ad of Kavdia ad Chidambaram (1996), h modls usd ar of firs ordr havig dadim. Noic ha, i a o loo sabl rocss, dyamic lags ca b lumd io a firs-ordr lm havig a aar im cosa ad a aar dadim. Bu, for a usabl rocss, a firs-ordr modl is o suffici for dscribig is dyamics. Bcaus, ohr ha h usabl im cosa, hr ar sill sabl dyamic lags i h rocss. hs sabl dyamic lags ca usually b lumd io aohr firs-ordr modl wih dad im. hus, o ak io accou hs wo ars of dyamics, a scod-ordr modl would b br. Bu, modlig his scod-ordr modl for usabl rocss sill sms a o issu.. uig mhods for a gral usabl rocss havig dad im usually rquir dious quaio-solvig ss which ar o fasibl for o-li imlmaio. Bsids, almos all such uig mhods rord i h liraur for a usabl rocss wih dadim ar usually cofid o firs-ordr modls. For scodordr modls, hr ar oly a fw rsuls rord (Shafii ad Sho, 1994; Huag ad Ch, 1996). 3. Ulik h auo-uig s for o loo sabl rocsss, h rlay fdback sysm may fail o rach a limi cycl for a giv o loo usabl rocss. hus, h sabiliy of a rlay fdback sysm is rsriciv. Iformaio rgardig h dyamics of h rocss is hus rquird i riori. Du o h issus addrssd abov, w roos a auo-uig sysm for o loo usabl rocsss. W shall cofi our sco o hos ha hav oly si- 486 Coyrigh 1999 h Sociy of Chmical Egirs, Jaa

2 gl usabl ols firs. For rocsss wih mor usabl ols, h siuaio would b mor comlicad ad is a roblm for fuur sudy. I his roosd auouig sysm, idificaio is coducd usig a rlay fdback s. h ouus of h rlay ar asymmric. Modls of firs ordr or scod ordr ar dvlod wih o-li algorihms. I dvloig a scod-ordr modl, a lad/lag lm which has a vry small lag im ad a adjusabl ladim is aachd o h rlay o chag h rocss dyamics io a firsordr o. Paramr simaio for h firs-ordr modl is h rformd usig h basic rlaios ha hav b drivd from a rlay fdback xrim. Corollr uig is basd o som siml uig formula ha ar drivd from h work of Huag ad Ch (1996). Such ruls ar dvisd for PID corollrs usig ihr a firs-ordr or scod-ordr modl. his aricl is orgaizd as follows. Scio 1 discusss h ky issus i a rlay fdback sysm for o loo usabl rocsss. Scio discusss daild rocdurs i h idificaio has. h corollr uig rul is sablishd i Scio 3. Scio 4 givs xamls o illusra ad s h roosd mhod. A oliar usabl bioracor ad a oliar usabl coiuous sirrd ak racor ar usd o illusra h roosd mhod i Scio 5. Coclusios of his work ar summarizd i Scio Auo-uig Sysm wih Asymmric Rlay Fdback o hac h auo-uig of a PID corollr for a o-loo usabl rocss, h sysm as show i Fig. 1 is cosidrd. h auo-uig sysm is calld o fucio by closig h swich ha cocs h rror sigal o h rlay fdback corollr. h rlay fdback corollr cosiss of a asymmric rlay followd by a lad/lag lm wih a adjusabl lad im. h biasd rlay is dfid as follows: ()= u γ h, h, if if ()> ()< whr () is h rror bw h s-oi, R, ad h ouu, y, as show i Fig. 1. h facor γ is o rovid asymmric rlay ouus. h sysm is xcid ad wais uil h limi cycl occurs. Basd o h rsos daa from hs cosa cycls, aramrs of a modl ar simad. By usig h rsulig modl, aramrs of a PID corollr ar h calculad. As has b miod rviously, h rlay fdback sysm may fail o sabiliz a giv o-loo usabl rocss. hus, i would b ssial o kow udr wha codiios, such a auo-uig sysm wih rlay fdback would b fasibl. Fig. 1 W shall cosidr h followig dyamic modls for h rrsaios of o loo usabl rocsss for auo-uig: s K G()= s s 1 G ()= s Auo-uig sysm for o-loo usabl rocss s K s 1 as 1 ( ) () 1 ( ) Equaio (1) sads for hos rocsss ha hav b discussd i may corol liraur ha dal wih o-loo usabl rocsss. Bu, h usabl ol is o h oly dyamics ha occurs i ral rocsss. o accou for h ohr dyamic lag ha usually occurs i ral rocsss, a sabl firs-ordr-lus-dadim lm is aachd o h o i Eq. (1) o giv h scod-ordr dyamics of Eq. (). 1.1 Sabiliy codiio for rlay fdback I his roosd auo-uig rocdur, a siml rlay fdback s is o b coducd firs. I may h rquir iroducig a lad/lag lm io h loo i subsqu ss durig idificaio. hus, as a sarig s for his roosd auo-u, h sabiliy codiios of a rlay fdback loo ha cosiss of rocss modls such as Eqs. (1) ad () ad a biasd rlay is ssial. Wh a rocss of Eq. (1) or of Eq. () ca b sabilizd wih such a biasd rlay fdback corollr, a fasibl rgio ha would guara loo sabiliy afr aachig a lad/lag lm o h rlay ca b foud. I h followig, h sabiliy of h rlay fdback for a firs-ordr rocss or a scod-ordr rocss will b sudid. h rsul will srv as a guidac for h fasibiliy of rformig a rlay fdback s o a giv rocss Sabiliy codiio for firs-ordr rocsss Cosidr a firs ordr rocss of Eq. (1) ad is rsos o a rlay fdback as show i Fig.. A firs ordr rocss o b sabilizd wih a asymmric rlay fdback has o comly wih h followig codiio (Huag ad Ch, 1997): 1 γ < mil ( 1 γ), l () 3 γ 487

3 Fig. Rlay fdback of a firs-ordr usabl rocss Fig. 4 Fasibl rgio for rlay fdback wih a scodordr usabl rocss Fig. 3 Rlay fdback rsos curvs of a scod-ordr usabl rocss I Eq. (3), dsigas h raio of dadim o h usabl im cosa. his codiio is drivd as a cssary codiio for h occurc of limi cycl i rsos o a shif of rlay ouu. Ay firs-ordr rocss which violas his codiio would o b fasibl for rformig rlay fdback s for auo-uig Sabiliy codiios for scod ordr rocsss Cosidr h scod-ordr rocss of Eq. (). A gral rsos of his rocss o a rlay fdback as show i Fig. 3. o avoid dious mahmaical drivaios, a aroach of h followig is adod. Firs, Eq. () is rwri as h o wih dimsiolss im uis of h followig: h hl of his figur, if a rocss whos aramrs loca i h fasibl rgio, h, cosa cyclig ca b guarad wh coducig such a rlay fdback s Sabiliy codiios for iiial y A h vry bgiig of h rlay fdback s, w hav u = for <. Usually, h s is sard wih y, ad ẏ =. Udr his siuaio, h iiial valus y is also ssial o h sabiliy. h rsos of y a > i his iiial sag is: For y < ay a hk y = a a a γ a y hk a a γ γ hk 5 G ()= s s K ( s 1) as 1 ( 4) or For y > whr, a = ad a = If w cosidr h ouu y big ormalizd wih h rocss cosa K, i is h obvious ha his rlay fdback sysm is characrizd by, a, ad γ oly. By assumig ha h rocss is iiially a a sady sa, h sabiliy rgio for a a diffr ad γ ca b foud by dirc simulaio. h MALAB Simulik is usd as a simulaio ool for his uros. For a giv γ ad, h maximum valu of a which rsuls i sabl rlay fdback s is obaid. By scaig h fasibl a alog usig γ as a aramr, h rsuls ar lod ad giv i Fig. 4. Wih ay ahk y = a a a a y hk a a hk 6 h drivaivs of y bcoms: For y < y hk ẏ = a a a γ a y hk a a γ JOURNAL OF CHEMICAL ENGINEERING OF JAPAN

4 or For y > y hk ẏ = a a a a y hk a a 8 If limi cycl occurs, i is cssary ha h drivaiv of y chags is sig a som im isa, *, (* > ) wh ẏ (*) =. From Eqs. (7) ad (8), h followig cssary codiios ca b cocludd: ad, y < mi hk a γ, γhk 9 y hk a hk < mi, 1 So ha () y hk a hk a hk hk < mi γ,, γ, 11 If a =, h abov iqualiy bcoms: y mi γ, 1 hk 1 < Accordig o h rsul i Eq. (1), i is hus clar ha, i ordr o imlm auo-uig for a usabl rocss, w d o kow h valus of K ad / of h rocss. If such valus ar o availabl i advac, som addiioal ss may b dd. For xaml, w may morarily assum ha all h sabl dyamic lags ca b lumd io h dadim so ha h rocss ca b rrsd as a firs-ordr modl. h, hrough h arly ar of h s rsos, h dlay ca b rad as h im wh ouu chags ca b dcd, ad h aar usabl im cosa ca b simad from his arly ar of y as follows: ˆ y () y ( 1) = l y ( 1) y ( ) which maks us of h dyamic quaio: y ()= y ( 1)K 1 u 1 ad u big a s iu. Hr, ca b ay im largr ha h aar dadim. Noic ha 1 ad do h rvious o ad wo samlig isas a im. hus, rgardig a giv usabl rocss, h fasibiliy for a rlay fdback s ca b simad roughly by usig Eq. (3) I h followig, w shall dic h idificaio ad corollr uig of his auo-uig sysm.. O-li Idificaio for Low Ordr Modl h firs s of his auo-uig rocdur is o idify a suiabl low ordr modl of Eq. (1) or of Eq. () basd o h daa from a rlay fdback s. hus, h rlay fdback loo is xcid from is origial sady sa o rovid cssary daa. Afr a rasi riod, rsis cosa cyclig would aar. From hs cosa cycls, h rocss cosa, K P, ad ohr aramrs i Eq. (1) ca b simad. h usabl rocss cosa, K, ca b simad as follows: K = G( ) ( 13 ) yd () = lim ud () P N y() d = lim P N N u() d P yd () = P ( 14) ud () whr ca b ay im isa afr rsis cyclig aars ad P is h riod of cyclig. h aroximaio of Eq. (14) holds oly if h rlay is asymmric (i.. γ 1). Wih asymmric rlay, h igraios of y ad u ovr h rasi zo ar gligibl comarig wih hos ovr h cosa cyclig zo. As a rsul, h simaio ca bas o h igraio ovr o sigl cyclig riod i his cosa cyclig zo. horically, γ ca b ay osiiv ral umbr. Howvr, as γ icrass or dcrass from uiy, h sabilizabl rgio subjcd o h raio of / would b dwidld. hus, o comromis bw a widr sabilizabl rgio ad h comuaio of K P, a valu aroud uiy is dsirabl. VOL. 3 NO

5

6 Hr, / is comud from h rvious aiv firsordr modl, ad ν is a scalig facor o corol h udaig sd. If w ak a biggr valu of ν, h rlay fdback sysm will rach a rsis cyclig zo mor quickly, which is rfrabl for a o-li xrim. Howvr, if h ruly aarly sabl im cosa is of small valu, a biggr valu of ν will ak mor iraio ss bfor i ca covrg. A valu bw.4 ad.6 is hrfor rcommdd. h w rocd o driv a o-li algorihm for udaig h valu of b. L us dfi a o-gaiv fucio V as follows: Fig. 5 Fasibl rgio of lad im cosa, b V = 1 3 ssial o kow h fasibl rgio for h valu of b. Rgardig a rocss whos dyamic modl ca b rrsd by Eq. (), h fasibl rgios for diffr valus of a/ so as o rsul i a sabl limi cycl for idificaio ar as show i Fig. 5. Wih hs fasibl rgios, iraio ss h ca b rocdd o idify h sabl im cosa. Uo fiishig h iraios, h sabl im cosa will b aroximaly caclld by h lad lm, so ha h comsad rocss bcoms a firs-ordr o. As a rsul, h aramrs i his comsad rocss ca b drmid followig h rocdurs dicd rviously. Huag al. (1996) illusrad a rial ad rror rocdur o drmi h oimal lad im ad h rsulig scod-ordr modl, icludig h dadim,, ad h sabl lag cosa, a. o limia h ds for rsoal irvios i rovidig a w rial valu o udrak h rialad-rror rocdurs, i is dsirabl ha his rial-adrror rocdur ca b udad by h sysm islf. o achiv his, a o-li udaig algorihm for h valu of b is dvisd..1 O-li udaig algorihm h o-li algorihm is iiiad wih a iiial rial valu for h lad im, b. his iiial rial of b should comly wih h fasibl rgio for rlay fdback s. As ca b s from Fig. 4, for a giv /, h sabl im cosa a should b smallr ha (1 /). A rasoabl guss for / is hus adod from h rsuls of a aiv firs-ordr modl i h rvious s, ad is giv as follows: b = ν 1 ν 1 < Obviously, h raio of /δ rsuls from h comsad rocss is a fucio of b. L V(b ) = V(b 1 ) V(b ), h, w hav: Vb ( )= 1 δ = 1 b 4 δ b o mak V(b ) o-osiiv for ay, b is chos as: b = b b 1 1 η 5 whr, φ η = ( 6) φ φ = b ( 7) I ohr words, o hav a vr dcrasig valu of (1 /δ), h rial valu of b is udad accordig o: b w whr, = bold ληˆ 1 8 VOL. 3 NO

7 ˆη b b b1 b ( 9) Accordig o Huag ad Ch (1996), h rsulig uig abl for boh firs-ordr ad scod-ordr rocsss is giv as follows: s k For G()= s : s 1 K( f ) k = 5. ( KM Km), R =, K 1 ad D = b h abov algorihm will guara h covrgc of b o ach udad rial. Rsulig from may simulaio rsuls, i is obsrvd ha /δ dcrass as b icrass, hus h abov algorihm ca b furhr simlifid as followig: bw = bold λb 1 3 whr λ b is a adjusig facor of s siz. A valu bw.3 ad.7 is rcommdd. h slf udad rial-ad-rror rocdur gos as follows. Afr iroducig h iiial rial lad im, b, h rocss ouu is xcid uil limi cycl occurs. A aiv firs-ordr modl is simad usig Eqs. (17) ad (18). Rsuls ar h validad if h w raio of o δ is clos ough o uiy or o. If i is, h aar sabl domia im cosa, a, quals b, ad h usabl im cosa ad dlay i h scod-ordr modl ar adod dircly from h rsuld firs-ordr modl. If h raio of o δ is o wihi h olrac limi aroud uiy, a w valu of b is udad accordig o h algorihm i Eq. (3) ad h s is rad. h rocdur is carrid ou uil saisfacory rsul is obaid. 3. O-li uig for PID Corollrs h corollr uig mhod usd hr is origiad from h work of Huag ad Ch (1996). I hir work, a o-dgr-of-frdom (1-df) corollr i rms of PID algorihm is a simlifid rsul from hir wo-dgr-of-frdom (-df) corol sysm. his -df sysm maks us of hr lms o achiv sabilizaio, disurbac rjcio, ad srvo-rackig saraly. For sabilizaio, h origial o loo usabl rocss is closd wih a P or PD lm (wih a lad im of b) o obai h wids fasibl rgio of gai for corol. As a scod s, his lmary loo is h formulad io a IMC srucur o fid corollrs for ihr disurbac rjcio or srvo-rackig. Fially, h rsulig hr-lm sysm is h rformd io a -df srucur of which h corollr i h fdback loo is of a cascadd PID form. h 1- df PID corollr, ha is h o usd i his auo-uig sysm, is a scial rsul from h -df sysm. s k For G()= s : ( s 1) ( as 1) K( f ) k = 5. ( KM Km), R =, K 1 ad D = a h corollr dsig a h bgiig of his hr-lm aroach is o fid a P or PD lm ha ca rovid h largs K M = K c,max K. o achiv his, w hav o rfr o h followig quaios which dscrib h criical oi: ω = a 1 ω a 1 bω ( 31) Ad, K M is: KM = 1 ω 1 b ω ( 3) If w l: x = ω ad ˆb = b/. Eqs. (31) ad (3) ca b rwri as: ad x = 1 x 1 a a bx ˆ ( 33 ) x KM = 1 1 b x ˆ ( 34) hus, h maximum valu of K M for a giv raio of / ca b drivd by sig h drivaiv of K M wih rsc o / qualig o zro o giv: K M * = K M *[/] his abov rlaio has b foud for diffr valus of / ad is lod as a solid li i Fig. 6(b). A quaio is h foud (< / < 1) for his rlaio: K M = JOURNAL OF CHEMICAL ENGINEERING OF JAPAN

8 Similarly, h valu of b o b ak is giv as h followig quaio. b 4 1 = As show i Figs. 6(a) ad 6(b), good agrm is obaid. h abov quaios ca b alid o a scod ordr sysm by firs caclig h sabl ol o bcom a firs-ordr rocss, of which K M is giv as Eq. (35) ad b =. h rsulig corollr sigs ar h obaid by subsiuig h abov wo quaios o giv: Cas A: Firs-ordr rocss ( < / < 1) KK c = r d f KK c = KK 1 c 4 1 = ( 38) ( 39) Cas B: Scod-ordr rocss ( < / <.8) KK c = r d f KK c = KK 1 c ( 41) a = ( 4) I h abov uig quaios, hr is o aramr lf. h scod s of dsig is h o fid a ror f ha ca giv good srvo-rackig rformac. Du o h rrors i aroximaio, f i Eqs. (38) ad (41) has a lowr boud, ad his lowr bod ca b asily drmid from h Nyquis s. For covic i a auo-uig sysm, such a boud is valuad ad h followig rlaios ar foud for firs-ordr ad scod-ordr rocsss, rscivly. Cas A: Firs-ordr rocss ( < / < 1) f mi 4 = ( 43) Cas B: Scod-ordr rocss ( < / <.8) f Fig. 6 mi = ( 44) hs rlaios for uig f ar also giv i Figs. 6(c) ad (d). I is obvious ha h valu of f should b chos o b largr ha f,mi. A valu of -ims h miimum valu is rcommdd. 4. Simulaio Examl Examl 1 Cosidr h followig scod-ordr rocss: G( s)= Aroximaio of K M, ˆ γ ad ( f /) m. 5s s 1 5. s 1 ( ) ( 45) If h modl is aivly assumd o b of firs ordr, h followig aramrs ar obaid from a rlay fdback s wih h = 1 ad γ = 1.5: K = 1.3; =.844; = 1.63 VOL. 3 NO

9 abl 1 O-li udaig b for Examl 1 b K /δ Fig. 7 O-li xrim for Examl 1 abl Rsulig modls for Examl 1 K a Exac Firs-ordr modl Scod-ordr modl Fig. 8 Corol rsoss of Examl 1: li(1)-(wih dordr modl), li()-(wih 1s-ordr modl) abl 3 O-li udaig b for Examl b K /δ o valida his aiv assumio, h calculad ad xrimal valus of aar dadim ar foud o hav a raio of.9. I is h vid ha his assumio has o b did. hus, idificaio rocdurs ar carrid ou o fid a scod-ordr modl. h ouu y hroughou h xrim is as show i Fig. 7, ad h rocss of o-li udaig h rial valus of b ar summarizd i abl 1. h rsuls of firs-ordr ad scod-ordr modls ar summarizd i abl. Corollr sigs rsulig from ihr modls ar lisd i h followig: For 1s-ordr modl: K c =.71; R = 4.43; D =.317 For d-ordr modl: K c = 3.13; R = 5.77; D =.56 Prformacs of corol usig ihr corollr o rack a s-oi chag ar lod i Fig. 8. his shows ha idificaio for scod ordr rocss usig his roosd mhod ar vry ffciv. Fig. 9 For his xaml, a accura scod ordr modl is rfrrd o a firs-ordr o for corollr dsig. Examl Cosidr h followig highr-ordr rocss: G( s)= Corol rsoss of Examl : li(1)-roosd (wih d-ordr modl), li()-roosd (wih 1sordr modl). 1s s 1. 5s 1. 1s 1 ( )( ) ( 46) Accordig o h idificaio rocdur dicd abov, a aiv firs-ordr modl wih h followig aramrs rsuls: K =.998; = 1.76; =.7 W hav o valida his aiv modl by xamiig h raio of o δ. I is h foud ha h valu of his raio is.741 which is ry far away from uiy. As a rsul, h idificaio rocdur has o b coiud o fid a scod-ordr modl. By usig h o-li adaig algorihm, h rsuls of aramr simaio for his scod-ordr modl ar giv i abl 3. h corollr sigs ar h calculad ad lisd as follow. 494 JOURNAL OF CHEMICAL ENGINEERING OF JAPAN

10 For firs-ordr modl: K c =.3; R = 4.; D =.4 For scod-ordr modl: K c = 4.51; R = 1.67; D =.67 S rsoss o h wo diffr sysms ar giv i Fig. 9. I his figur, i shows h sysm basd o a scod-ordr modl is sigificaly br ha h o which uss a firs-ordr modl. 5. Alicaio o Usabl Noliar Procsss I his scio, wo xamls of usabl oliar rocsss ar usd o illusra h roosd mhod. h firs oliar rocss is a bioracor sysm giv by Agrawal ad Lim (1986). h scod o is a coiuous sirrd ak racor sudid by Ual al. (1974) ad Ual al. (1976). 5.1 Alicaio o a usabl bioracor A oliar coiuous bioracor which xhibis ouu muliliciy ar giv (Agrawal ad Lim, 1986): dx d ds d Whr = ( µ DX ) ( 47) = Sf S D µ X / γ 48 ( 49) µ = µ S/ K S K S m m I h modl aramrs ar: γ =.4% g/g S f = 4.% g/g µ m =.53 h 1 K m =.1% g/g K I =.4545% g/g I cas of D =.3, h sysm of Eqs. (47) o (49) has hr mulil sady-sas: [X, S] 1 = [., 4.] (wash-ou codiio) [X, S] = [.9951, 1.51] (usabl) [X, S] 3 = [1.531,.1746] (sabl) I is assumd ha h diluio ra (D) is cosidrd as h maiulad variabl o corol h cll mass cocraio (X) a h usabl sady-sa, i.. X = A dlay of o hour is addd o h masurm of x o simula h ouu dlay du o h aalyical isrum ad rocdurs. I is obvious ha h rocss gai dds o h magiud of h iu sigal bcaus of h oliar characrisics. o fid h usabl gai a X =.9951, a asymmrical rlay wih h =.1 (abou.33% of h sady-sa valu) ad γ = 1.5 is usd. Wh rsis cyclig occurs, as show i Fig. 1(a), a aiv firs ordr Fig. 1 Auo-uig of usabl oliar bioracor modl of h followig is obaid: K = 6.43; = 6.81; = 1.1 h raio of o δ is foud o b 1.1, hus his aiv firs-ordr modl is accabl. Followig Eqs. (37) o (39), h followig corollr sigs ar suggsd: K c =.93; R =.3871; D =.663 A s chag of X from.9951 o 1.94 is iroducd o h sysm ad is ouu is lod i Fig. 1(b). h rsuls of his xaml shows h ffcivss of idificaio for a firs-ordr modl. h corol rformac hus obaid is a las as good as h o rord by Kavdia ad Chidambaram (1996) as show i h figur. 5. Alicaio o a usabl coiuous sirrd ak racor A coiuous sirrd ak racor (CSR) wih xohrmic racio, which is xlord by Ual al. (1974, 1976) is cosidrd as h ohr xaml for illusraio. A irrvrsibl firs-ordr racio occurs i a racor. h mraur ad cocraio of h raca a h xi of h racor ar h sa variabls, ad h coola mraur is ak o b h maiulad variabl. Afr iroducig dimsiolss grous io h govrig quaios, h sysm is dscribd as: dx d 1 dx d = x D 1 x 1 a 1 x x 1 x co d 1 d 5 / ν x = x BDa ( 1 x1) x 1 x / ν β( x x ) βu( ) d ( 51) VOL. 3 NO

11 abl 4 Dimsiolss variabls ad grous of CSR sysm B D a β ν d x co x 1 x u d 1 u dimsiolss ha of racio Damkohlr umbr dimsiolss ha rasfr coffici dimsiolss acivaio rgy dimsiolss im dimsiolss im dlay omial dimsiolss coola mraur dimsiolss comosiio dimsiolss mraur dimsiolss coola mraur dimsiolss fd mraur disurbac dimsiolss fd comosiio disurbac Fig. 11 Auo-uig of usabl oliar CSR abl 5 O-li udaig b for CSR sysm b K /δ whr x 1 ad x ar dimsiolss cocraio ad mraur of h raca, rscivly. h dimsiolss disurbacs d 1 ad d ar usd o rrs h flucuaios of h mraur ad cocraio i h fd sram. A lis of dimsiolss variabls or grous is giv i abl 4. I is assumd ha h mraur ad cocraio of fd sram ar cosa (i.. d 1 = d = ). A dimsiolss im dlay d of. i h maiulaio variabl u is also icludd. As a summary, h dimsiolss aramrs of his sysm ar lisd as follows. D a =.7 ν = B = 8. β =.3 x co = I h cas of u =, h sady-sa soluio of Eqs. (5) ad (51) givs h followig hr mulil sadysa soluios: [x 1, x ] 1 = [.144,.866] (sabl) [x 1, x ] = [.447,.7517] (usabl) [x 1, x ] 3 = [.7646, 4.755] (sabl) o idify h rasfr fucio modl a x 1 =.447 ad x =.7517, a asymmrical rlay wih γ = 1.5 ad h =.5 is iroducd. A aiv firsordr modl wih h followig aramrs rsuls, i..: K =.31; = 4.; = 1.45 Uo xamiig his firs-ordr modl, i is foud ha h raio of o δ is.811. As has b xlaid bfor, his aiv modl will o b usd. As show i abl 5, h iraiv rocdur will lad o h followig scod-ordr modl: K =.31; = 1.78; a = 1.389; =.9 Figur 11(a) shows h ouu of h sysm durig h idificaio has. G( s)=. s s 1. 3s 1 ( ) ( 5) Comard wih a liarizd modl, h rsulig scod-ordr modl is a rasoabl simaio a a usabl oi. Followig Eqs. (4) o (4), h followig corollr aramrs ar suggsd: K c = 7.86; R = 1.7; D = 1.39 o show ha a scod-ordr modl is surior, corollr aramrs basd o h rvious aiv firsordr modl ar: K c = 13.67; R = 4.48; D =.36 A soi chag of x 1 form.447 o.497 is iroducd o h sysm. As Fig. 11(b) shows, h rsos rsuld from a scod-ordr modl is much br ha ha from a firs-ordr modl. Coclusio I his work, a mhod o auou a PID corollr for o loo usabl rocsss havig a sigl usabl ol ad dadim is roosd. A asymmric rlay fdback s is usd o gra a cosa limi cycl. From his cosa limi cycl, a aiv firs-ordr modl is idifid. his modl is h vali- 496 JOURNAL OF CHEMICAL ENGINEERING OF JAPAN

12 dad by xamiig h raio of calculad ad masurd dadim. If h aiv modl is o saisfacory, a idificaio rocdur is carrid ou o fid a scod-ordr modl. his scod-ordr modl is obaid by raig h rlay fdback s wih a oli udaig algorihm. Corollr aramrs of a PID corollr ar h calculad from a s of siml uig ruls. wo usabl oliar chmical rocsss ar usd o illusra his roosd auo-uig mhod. Nomclaur a = sabl im cosa b = lad cosa D = Diluio ra G (s) = rocss rasfr fucio h = rlay magiud K M = maximum loo gai K m = miimum loo gai K P = rocss cosa K = usabl gai P = riod of limi cycl i rlay fdback sysm S = subsra cocraio = usabl im cosa u = rocss iu V = rformac fucio X = cll mass cocraio x = ulima loo gai y = rocss ouu β = ulima gai δ = simad dadim = Diffrc = dadim γ = biasd mulil Λ = s siz ω = frqucy <Subscri> d = drivaiv f = IMC filr = rocss r = rs Liraur Cid Agrawal, P. ad H. C. Lim; Aalysis of Various Corol Schms for Coiuous Bioracors, Adv. Biochm. Bioch., 3, 61 9 (1986) Åsröm, K. J. ad. Hägglad; Auomaic uig of Siml Rgulaors wih Scificaios o Phas ad Amliud Margis, Auomaica,, (1984) Åsröm, K. J. ad. Hägglad; PID Corollrs, d Ediio, ISA (1995) Hägglad,. ad K. J. Åsröm; Idusrial Adaiv Corollrs Bas o Frqucy Rsos chiqus, Auomaica, 7, (1991) Hoo, K. A. ad J. C. Kaor; A Exohrmic Coiuous Sirrd ak Racor is Fdback Equival o a Liar Sysm, Chm. Eg. Commu., 37, 1 1 (1985) Hoo, K. A. ad J. C. Kaor; Liar Fdback Equivalc ad Corol of a Usabl Biological Racor, Chm. Eg. Commu., 46, (1986) Huag, H. P. ad C. C. Ch; Corol Sysm Syhsis for O Loo Usabl Procss Havig im Dlay, IEE Procdigs Corol ad Alicaios, 144, (1996) Huag, H. P. ad C. C. Ch; A Nw Aroach o Idify Low Ordr Modl for Procss Havig Sigl Usabl Pol, Sysm Aalysis-Modlig-Simulaio, 9, (1997) Huag, H. P., C. L. Ch, C. W. Lai ad G. B. Wag; Auouig for Modl-Basd PID Corollrs, AIChE J., 4, (1996) Kavdia, M. ad M. Chidambaram; O-li Corollr uig for Usabl Sysms, Comurs Chm. Egg,, (1996) Shafii, Z. ad. Sho; uig of PID-y Corollr for Sabl ad Usabl Sysms wih im Dlay, Auomaica, 3, (1994) Ual, A., W. H. Ray ad A. B. Poor; O h Dyamic Bhavior of Coious Sirrd ak Racors, Chm. Eg. Sci., 9, (1974) Ual, A., W. H. Ray ad A. B. Poor; h Classificaio of h Dyamic Bhavior of Coious Sirrd ak Racors, Chm. Eg. Sci., 31, 5 14 (1976) Wag, Q. G.,. H. L ad K. K. a; Rlay-ud FSA Corol for Usabl Procsss Wih Dadim, Procdigs of h ACC, , Sal, USA (1995) Yuwaa, M. ad D. E. Sborg; A Nw Mhod for O-Li Corollr uig, AIChE J., 8, (198) Zhao, Y. ad S. Jayasuriya; Sabilizabiliy of Usabl Liar Plas Udr Boudd Corol, J. of Dyamic Sysms, Masurm, ad Corol, 117, (1995) VOL. 3 NO

Numerical Simulation for the 2-D Heat Equation with Derivative Boundary Conditions

Numerical Simulation for the 2-D Heat Equation with Derivative Boundary Conditions IOSR Joural of Applid Chmisr IOSR-JAC -ISSN: 78-576.Volum 9 Issu 8 Vr. I Aug. 6 PP 4-8 www.iosrjourals.org Numrical Simulaio for h - Ha Equaio wih rivaiv Boudar Codiios Ima. I. Gorial parm of Mahmaics

More information

Chapter 3 Linear Equations of Higher Order (Page # 144)

Chapter 3 Linear Equations of Higher Order (Page # 144) Ma Modr Dirial Equaios Lcur wk 4 Jul 4-8 Dr Firozzama Darm o Mahmaics ad Saisics Arizoa Sa Uivrsi This wk s lcur will covr har ad har 4 Scios 4 har Liar Equaios o Highr Ordr Pag # 44 Scio Iroducio: Scod

More information

Continous system: differential equations

Continous system: differential equations /6/008 Coious sysm: diffrial quaios Drmiisic modls drivaivs isad of (+)-( r( compar ( + ) R( + r ( (0) ( R ( 0 ) ( Dcid wha hav a ffc o h sysm Drmi whhr h paramrs ar posiiv or gaiv, i.. giv growh or rducio

More information

Control Systems. Transient and Steady State Response.

Control Systems. Transient and Steady State Response. Corol Sym Trai a Say Sa Ro chibum@oulch.ac.kr Ouli Tim Domai Aalyi orr ym Ui ro Ui ram ro Ui imul ro Chibum L -Soulch Corol Sym Tim Domai Aalyi Afr h mahmaical mol of h ym i obai, aalyi of ym rformac i.

More information

Response of LTI Systems to Complex Exponentials

Response of LTI Systems to Complex Exponentials 3 Fourir sris coiuous-im Rspos of LI Sysms o Complx Expoials Ouli Cosidr a LI sysm wih h ui impuls rspos Suppos h ipu sigal is a complx xpoial s x s is a complx umbr, xz zis a complx umbr h or h h w will

More information

1973 AP Calculus BC: Section I

1973 AP Calculus BC: Section I 97 AP Calculus BC: Scio I 9 Mius No Calculaor No: I his amiaio, l dos h aural logarihm of (ha is, logarihm o h bas ).. If f ( ) =, h f ( ) = ( ). ( ) + d = 7 6. If f( ) = +, h h s of valus for which f

More information

Fourier Series: main points

Fourier Series: main points BIOEN 3 Lcur 6 Fourir rasforms Novmbr 9, Fourir Sris: mai pois Ifii sum of sis, cosis, or boh + a a cos( + b si( All frqucis ar igr mulipls of a fudamal frqucy, o F.S. ca rprs ay priodic fucio ha w ca

More information

Part B: Transform Methods. Professor E. Ambikairajah UNSW, Australia

Part B: Transform Methods. Professor E. Ambikairajah UNSW, Australia Par B: rasform Mhods Profssor E. Ambikairaah UNSW, Ausralia Chapr : Fourir Rprsaio of Sigal. Fourir Sris. Fourir rasform.3 Ivrs Fourir rasform.4 Propris.4. Frqucy Shif.4. im Shif.4.3 Scalig.4.4 Diffriaio

More information

The Development of Suitable and Well-founded Numerical Methods to Solve Systems of Integro- Differential Equations,

The Development of Suitable and Well-founded Numerical Methods to Solve Systems of Integro- Differential Equations, Shiraz Uivrsiy of Tchology From h SlcdWorks of Habibolla Laifizadh Th Dvlopm of Suiabl ad Wll-foudd Numrical Mhods o Solv Sysms of Igro- Diffrial Equaios, Habibolla Laifizadh, Shiraz Uivrsiy of Tchology

More information

( A) ( B) ( C) ( D) ( E)

( A) ( B) ( C) ( D) ( E) d Smsr Fial Exam Worksh x 5x.( NC)If f ( ) d + 7, h 4 f ( ) d is 9x + x 5 6 ( B) ( C) 0 7 ( E) divrg +. (NC) Th ifii sris ak has h parial sum S ( ) for. k Wha is h sum of h sris a? ( B) 0 ( C) ( E) divrgs

More information

Poisson Arrival Process

Poisson Arrival Process 1 Poisso Arrival Procss Arrivals occur i) i a mmorylss mar ii) [ o arrival durig Δ ] = λδ + ( Δ ) P o [ o arrival durig Δ ] = 1 λδ + ( Δ ) P o P j arrivals durig Δ = o Δ for j = 2,3, ( ) o Δ whr lim =

More information

Poisson Arrival Process

Poisson Arrival Process Poisso Arrival Procss Arrivals occur i) i a mmylss mar ii) [ o arrival durig Δ ] = λδ + ( Δ ) P o [ o arrival durig Δ ] = λδ + ( Δ ) P o P j arrivals durig Δ = o Δ f j = 2,3, o Δ whr lim =. Δ Δ C C 2 C

More information

Web-appendix 1: macro to calculate the range of ( ρ, for which R is positive definite

Web-appendix 1: macro to calculate the range of ( ρ, for which R is positive definite Wb-basd Supplmary Marials for Sampl siz cosidraios for GEE aalyss of hr-lvl clusr radomizd rials by Sv Trsra, Big Lu, oh S. Prissr, Tho va Achrbrg, ad Gorg F. Borm Wb-appdix : macro o calcula h rag of

More information

Note 6 Frequency Response

Note 6 Frequency Response No 6 Frqucy Rpo Dparm of Mchaical Egirig, Uivriy Of Sakachwa, 57 Campu Driv, Sakaoo, S S7N 59, Caada Dparm of Mchaical Egirig, Uivriy Of Sakachwa, 57 Campu Driv, Sakaoo, S S7N 59, Caada. alyical Exprio

More information

What Is the Difference between Gamma and Gaussian Distributions?

What Is the Difference between Gamma and Gaussian Distributions? Applid Mahmaics,,, 85-89 hp://ddoiorg/6/am Publishd Oli Fbruary (hp://wwwscirporg/joural/am) Wha Is h Diffrc bw Gamma ad Gaussia Disribuios? iao-li Hu chool of Elcrical Egirig ad Compur cic, Uivrsiy of

More information

Modeling of the CML FD noise-to-jitter conversion as an LPTV process

Modeling of the CML FD noise-to-jitter conversion as an LPTV process Modlig of h CML FD ois-o-ir covrsio as a LPV procss Marko Alksic. Rvisio hisory Vrsio Da Comms. //4 Firs vrsio mrgd wo docums. Cyclosaioary Nois ad Applicaio o CML Frqucy Dividr Jir/Phas Nois Aalysis fil

More information

MAT3700. Tutorial Letter 201/2/2016. Mathematics III (Engineering) Semester 2. Department of Mathematical sciences MAT3700/201/2/2016

MAT3700. Tutorial Letter 201/2/2016. Mathematics III (Engineering) Semester 2. Department of Mathematical sciences MAT3700/201/2/2016 MAT3700/0//06 Tuorial Lr 0//06 Mahmaics III (Egirig) MAT3700 Smsr Dparm of Mahmaical scics This uorial lr coais soluios ad aswrs o assigms. BARCODE CONTENTS Pag SOLUTIONS ASSIGNMENT... 3 SOLUTIONS ASSIGNMENT...

More information

MEM 355 Performance Enhancement of Dynamical Systems A First Control Problem - Cruise Control

MEM 355 Performance Enhancement of Dynamical Systems A First Control Problem - Cruise Control MEM 355 Prformanc Enhancmn of Dynamical Sysms A Firs Conrol Problm - Cruis Conrol Harry G. Kwany Darmn of Mchanical Enginring & Mchanics Drxl Univrsiy Cruis Conrol ( ) mv = F mg sinθ cv v +.2v= u 9.8θ

More information

Mathematical Preliminaries for Transforms, Subbands, and Wavelets

Mathematical Preliminaries for Transforms, Subbands, and Wavelets Mahmaical Prlimiaris for rasforms, Subbads, ad Wavls C.M. Liu Prcpual Sigal Procssig Lab Collg of Compur Scic Naioal Chiao-ug Uivrsiy hp://www.csi.cu.du.w/~cmliu/courss/comprssio/ Offic: EC538 (03)5731877

More information

ECEN620: Network Theory Broadband Circuit Design Fall 2014

ECEN620: Network Theory Broadband Circuit Design Fall 2014 ECE60: work Thory Broadbad Circui Dig Fall 04 Lcur 6: PLL Trai Bhavior Sam Palrmo Aalog & Mixd-Sigal Cr Txa A&M Uivriy Aoucm, Agda, & Rfrc HW i du oday by 5PM PLL Trackig Rpo Pha Dcor Modl PLL Hold Rag

More information

Mixing time with Coupling

Mixing time with Coupling Mixig im wih Couplig Jihui Li Mig Zhg Saisics Dparm May 7 Goal Iroducio o boudig h mixig im for MCMC wih couplig ad pah couplig Prsig a simpl xampl o illusra h basic ida Noaio M is a Markov chai o fii

More information

UNIT III STANDARD DISTRIBUTIONS

UNIT III STANDARD DISTRIBUTIONS UNIT III STANDARD DISTRIBUTIONS Biomial, Poisso, Normal, Gomric, Uiform, Eoial, Gamma disribuios ad hir roris. Prard by Dr. V. Valliammal Ngaiv biomial disribuios Prard by Dr.A.R.VIJAYALAKSHMI Sadard Disribuios

More information

15. Numerical Methods

15. Numerical Methods S K Modal' 5. Numrical Mhod. Th quaio + 4 4 i o b olvd uig h Nwo-Rapho mhod. If i ak a h iiial approimaio of h oluio, h h approimaio uig hi mhod will b [EC: GATE-7].(a (a (b 4 Nwo-Rapho iraio chm i f(

More information

Advanced Engineering Mathematics, K.A. Stroud, Dexter J. Booth Engineering Mathematics, H.K. Dass Higher Engineering Mathematics, Dr. B.S.

Advanced Engineering Mathematics, K.A. Stroud, Dexter J. Booth Engineering Mathematics, H.K. Dass Higher Engineering Mathematics, Dr. B.S. Rfrc: (i) (ii) (iii) Advcd Egirig Mhmic, K.A. Sroud, Dxr J. Booh Egirig Mhmic, H.K. D Highr Egirig Mhmic, Dr. B.S. Grwl Th mhod of m Thi coi of h followig xm wih h giv coribuio o h ol. () Mid-rm xm : 3%

More information

ON H-TRICHOTOMY IN BANACH SPACES

ON H-TRICHOTOMY IN BANACH SPACES CODRUTA STOICA IHAIL EGA O H-TRICHOTOY I BAACH SPACES Absrac: I his papr w mphasiz h oio of skw-oluio smiflows cosidrd a gralizaio of smigroups oluio opraors ad skw-produc smiflows which aris i h sabiliy

More information

ELECTROMAGNETIC COMPATIBILITY HANDBOOK 1. Chapter 12: Spectra of Periodic and Aperiodic Signals

ELECTROMAGNETIC COMPATIBILITY HANDBOOK 1. Chapter 12: Spectra of Periodic and Aperiodic Signals ELECTOMAGNETIC COMPATIBILITY HANDBOOK Chapr : Spcra of Priodic ad Apriodic Sigals. Drmi whhr ach of h followig fucios ar priodic. If hy ar priodic, provid hir fudamal frqucy ad priod. a) x 4cos( 5 ) si(

More information

Ring of Large Number Mutually Coupled Oscillators Periodic Solutions

Ring of Large Number Mutually Coupled Oscillators Periodic Solutions Iraioal Joural of horical ad Mahmaical Physics 4, 4(6: 5-9 DOI: 59/jijmp446 Rig of arg Numbr Muually Coupld Oscillaors Priodic Soluios Vasil G Aglov,*, Dafika z Aglova Dparm Nam of Mahmaics, Uivrsiy of

More information

Modeling of Reductive Biodegradation of TCE to ETH. Adam Worsztynowicz, Dorota Rzychon, Sebastian Iwaszenko, Tomasz Siobowicz

Modeling of Reductive Biodegradation of TCE to ETH. Adam Worsztynowicz, Dorota Rzychon, Sebastian Iwaszenko, Tomasz Siobowicz Modlig of Rduciv Biodgradaio of o ETH Adam Worszyowicz, Doroa Rzycho, Sbasia Iwaszo, Tomasz Siobowicz Isiu for Ecology of Idusrial Aras Kossuha S., Kaowic, Polad l. (+-) 5, fax: (+-) 5 7 7 -mail: iu@iu.aowic.pl

More information

a dt a dt a dt dt If 1, then the poles in the transfer function are complex conjugates. Let s look at f t H t f s / s. So, for a 2 nd order system:

a dt a dt a dt dt If 1, then the poles in the transfer function are complex conjugates. Let s look at f t H t f s / s. So, for a 2 nd order system: Undrdamd Sysms Undrdamd Sysms nd Ordr Sysms Ouu modld wih a nd ordr ODE: d y dy a a1 a0 y b f If a 0 0, hn: whr: a d y a1 dy b d y dy y f y f a a a 0 0 0 is h naural riod of oscillaion. is h daming facor.

More information

MA6451-PROBABILITY AND RANDOM PROCESSES

MA6451-PROBABILITY AND RANDOM PROCESSES MA645-PROBABILITY AND RANDOM PROCESSES UNIT I RANDOM VARIABLES Dr. V. Valliammal Darm of Alid Mahmaics Sri Vkaswara Collg of Egirig Radom variabl Radom Variabls A ral variabl whos valu is drmid by h oucom

More information

Linear Systems Analysis in the Time Domain

Linear Systems Analysis in the Time Domain Liar Sysms Aalysis i h Tim Domai Firs Ordr Sysms di vl = L, vr = Ri, d di L + Ri = () d R x= i, x& = x+ ( ) L L X() s I() s = = = U() s E() s Ls+ R R L s + R u () = () =, i() = L i () = R R Firs Ordr Sysms

More information

Software Development Cost Model based on NHPP Gompertz Distribution

Software Development Cost Model based on NHPP Gompertz Distribution Idia Joural of Scic ad Tchology, Vol 8(12), DOI: 10.17485/ijs/2015/v8i12/68332, Ju 2015 ISSN (Pri) : 0974-6846 ISSN (Oli) : 0974-5645 Sofwar Dvlopm Cos Modl basd o NHPP Gomprz Disribuio H-Chul Kim 1* ad

More information

2 Dirac delta function, modeling of impulse processes. 3 Sine integral function. Exponential integral function

2 Dirac delta function, modeling of impulse processes. 3 Sine integral function. Exponential integral function Chapr VII Spcial Fucios Ocobr 7, 7 479 CHAPTER VII SPECIAL FUNCTIONS Cos: Havisid sp fucio, filr fucio Dirac dla fucio, modlig of impuls procsss 3 Si igral fucio 4 Error fucio 5 Gamma fucio E Epoial igral

More information

ECE351: Signals and Systems I. Thinh Nguyen

ECE351: Signals and Systems I. Thinh Nguyen ECE35: Sigals ad Sysms I Thih Nguy FudamalsofSigalsadSysms x Fudamals of Sigals ad Sysms co. Fudamals of Sigals ad Sysms co. x x] Classificaio of sigals Classificaio of sigals co. x] x x] =xt s =x

More information

1.7 Vector Calculus 2 - Integration

1.7 Vector Calculus 2 - Integration cio.7.7 cor alculus - Igraio.7. Ordiary Igrals o a cor A vcor ca b igrad i h ordiary way o roduc aohr vcor or aml 5 5 d 6.7. Li Igrals Discussd hr is h oio o a dii igral ivolvig a vcor ucio ha gras a scalar.

More information

Fourier Techniques Chapters 2 & 3, Part I

Fourier Techniques Chapters 2 & 3, Part I Fourir chiqus Chaprs & 3, Par I Dr. Yu Q. Shi Dp o Elcrical & Compur Egirig Nw Jrsy Isiu o chology Email: shi@i.du usd or h cours: , 4 h Ediio, Lahi ad Dog, Oord

More information

CS 688 Pattern Recognition. Linear Models for Classification

CS 688 Pattern Recognition. Linear Models for Classification //6 S 688 Pr Rcogiio Lir Modls for lssificio Ø Probbilisic griv modls Ø Probbilisic discrimiiv modls Probbilisic Griv Modls Ø W o ur o robbilisic roch o clssificio Ø W ll s ho modls ih lir dcisio boudris

More information

, then the old equilibrium biomass was greater than the new B e. and we want to determine how long it takes for B(t) to reach the value B e.

, then the old equilibrium biomass was greater than the new B e. and we want to determine how long it takes for B(t) to reach the value B e. SURPLUS PRODUCTION (coiud) Trasiio o a Nw Equilibrium Th followig marials ar adapd from lchr (978), o h Rcommdd Radig lis caus () approachs h w quilibrium valu asympoically, i aks a ifii amou of im o acually

More information

NON-LINEAR PARAMETER ESTIMATION USING VOLTERRA SERIES WITH MULTI-TONE EXCITATION

NON-LINEAR PARAMETER ESTIMATION USING VOLTERRA SERIES WITH MULTI-TONE EXCITATION NON-LINER PRMETER ESTIMTION USING VOLTERR SERIES WIT MULTI-TONE ECITTION imsh Char Dparm of Mchaical Egirig Visvsvaraya Rgioal Collg of Egirig Nagpur INDI-00 Naliash Vyas Dparm of Mchaical Egirig Iia Isiu

More information

Larry Mianzo Laboratory Simulation Department Ford Motor Company Dearborn, MI

Larry Mianzo Laboratory Simulation Department Ford Motor Company Dearborn, MI 78338359/97/$. (c) 997 AACC LQ a H Prviw Corol or a Durailiy Simuor Larry Miazo Laoraory Simuio Darm For Moor Comay Daror, MI 48 lmiazo@or.com Hui Pg Darm o Mchaical Egirig a Ali Mchaics Uivrsiy o Michiga

More information

Nonlinear PID-based analog neural network control for a two link rigid robot manipulator and determining the maximum load carrying capacity

Nonlinear PID-based analog neural network control for a two link rigid robot manipulator and determining the maximum load carrying capacity Noliar PID-basd aalog ural work corol for a wo lik rigid robo maipulaor ad drmiig h maximum load carryig capaciy Hadi Razmi Aabak Mashhadi Kashiba Absrac A adapiv corollr of oliar PID-basd aalog ural works

More information

Log-periodogram regression with odd Fourier frequencies

Log-periodogram regression with odd Fourier frequencies Log-priodogram rgrssio wih odd Fourir frqucis Erhard Rschhofr Dparm of Saisics ad Opraios Rsarch, Uivrsiy of Via, Ausria Uivrsiässr. 5, Via, Ausria E-mail: rhard.rschhofr@uivi.ac.a Absrac I his papr, a

More information

3.2. Derivation of Laplace Transforms of Simple Functions

3.2. Derivation of Laplace Transforms of Simple Functions 3. aplac Tarform 3. PE TRNSFORM wid rag of girig ym ar modld mahmaically by uig diffrial quaio. I gral, h diffrial quaio of h ordr ym i wri: d y( a d d d y( dy( a a y( f( (3. d Which i alo ow a a liar

More information

Chapter4 Time Domain Analysis of Control System

Chapter4 Time Domain Analysis of Control System Chpr4 im Domi Alyi of Corol Sym Rouh biliy cririo Sdy rror ri rpo of h fir-ordr ym ri rpo of h cod-ordr ym im domi prformc pcificio h rliohip bw h prformc pcificio d ym prmr ri rpo of highr-ordr ym Dfiiio

More information

EEE 303: Signals and Linear Systems

EEE 303: Signals and Linear Systems 33: Sigls d Lir Sysms Orhogoliy bw wo sigls L us pproim fucio f () by fucio () ovr irvl : f ( ) = c( ); h rror i pproimio is, () = f() c () h rgy of rror sigl ovr h irvl [, ] is, { }{ } = f () c () d =

More information

Boyce/DiPrima 9 th ed, Ch 7.9: Nonhomogeneous Linear Systems

Boyce/DiPrima 9 th ed, Ch 7.9: Nonhomogeneous Linear Systems BoDiPrima 9 h d Ch 7.9: Nohomogou Liar Sm Elmar Diffrial Equaio ad Boudar Valu Prolm 9 h diio William E. Bo ad Rihard C. DiPrima 9 Joh Wil & So I. Th gral hor of a ohomogou m of quaio g g aralll ha of

More information

PFC Predictive Functional Control

PFC Predictive Functional Control PFC Prdiciv Funcional Conrol Prof. Car d Prada D. of Sm Enginring and Auomaic Conrol Univri of Valladolid, Sain rada@auom.uva. Oulin A iml a oibl Moivaion PFC main ida An inroducor xaml Moivaion Prdiciv

More information

Adomian Decomposition Method for Dispersion. Phenomena Arising in Longitudinal Dispersion of. Miscible Fluid Flow through Porous Media

Adomian Decomposition Method for Dispersion. Phenomena Arising in Longitudinal Dispersion of. Miscible Fluid Flow through Porous Media dv. Thor. ppl. Mch. Vol. 3 o. 5 - domia Dcomposiio Mhod for Disprsio Phoma risig i ogiudial Disprsio of Miscibl Fluid Flow hrough Porous Mdia Ramakaa Mhr ad M.N. Mha Dparm of Mahmaics S.V. Naioal Isiu

More information

8. Queueing systems. Contents. Simple teletraffic model. Pure queueing system

8. Queueing systems. Contents. Simple teletraffic model. Pure queueing system 8. Quug sysms Cos 8. Quug sysms Rfrshr: Sml lraffc modl Quug dscl M/M/ srvr wag lacs Alcao o ack lvl modllg of daa raffc M/M/ srvrs wag lacs lc8. S-38.45 Iroduco o Tlraffc Thory Srg 5 8. Quug sysms 8.

More information

Improved estimation of population variance using information on auxiliary attribute in simple random sampling. Rajesh Singh and Sachin Malik

Improved estimation of population variance using information on auxiliary attribute in simple random sampling. Rajesh Singh and Sachin Malik Imrovd imaio of oulaio variac uig iformaio o auxiliar ariu i iml radom amlig Rajh igh ad achi alik Darm of aiic, Baara Hidu Uivri Varaai-5, Idia (righa@gmail.com, achikurava999@gmail.com) Arac igh ad Kumar

More information

Practice papers A and B, produced by Edexcel in 2009, with mark schemes. Practice Paper A. 5 cosh x 2 sinh x = 11,

Practice papers A and B, produced by Edexcel in 2009, with mark schemes. Practice Paper A. 5 cosh x 2 sinh x = 11, Prai paprs A ad B, produd by Edl i 9, wih mark shms Prai Papr A. Fid h valus of for whih 5 osh sih =, givig your aswrs as aural logarihms. (Toal 6 marks) k. A = k, whr k is a ral osa. 9 (a) Fid valus of

More information

Recovery of Valuable Incompletely-Recorded Return- Stroke Current Derivative Signals

Recovery of Valuable Incompletely-Recorded Return- Stroke Current Derivative Signals Rcovry of Valuabl Icomplly-Rcordd Rur- Srok Curr Drivaiv Sigals Lakmii Prra Elcrical ad Compur Egirig Dparm Ryrso Uivrsiy Toroo, Caada lakmii.prra@ryrso.ca Ali M. Hussi Elcrical ad Compur Egirig Dparm

More information

Ideal Amplifier/Attenuator. Memoryless. where k is some real constant. Integrator. System with memory

Ideal Amplifier/Attenuator. Memoryless. where k is some real constant. Integrator. System with memory Liear Time-Ivaria Sysems (LTI Sysems) Oulie Basic Sysem Properies Memoryless ad sysems wih memory (saic or dyamic) Causal ad o-causal sysems (Causaliy) Liear ad o-liear sysems (Lieariy) Sable ad o-sable

More information

Testing Goodness-of-Fit in Autoregressive Fractionally Integrated Moving- Average Models with Conditional Hetroscedastic Errors of Unknown form

Testing Goodness-of-Fit in Autoregressive Fractionally Integrated Moving- Average Models with Conditional Hetroscedastic Errors of Unknown form Rsarch Joural of Rc Scics ISSN 77-5 Vol. (5, 9-4, May ( Rs.J.Rc Sci. Tsig Goodss-of-Fi i Auorgrssiv Fracioally Igrad Movig- Avrag Modls wih Codiioal roscdasic Errors of Uow form Absrac Ali Amad, Salahuddi

More information

Page 1. Before-After Control-Impact (BACI) Power Analysis For Several Related Populations (With Unknown Variance Matrix) Richard A.

Page 1. Before-After Control-Impact (BACI) Power Analysis For Several Related Populations (With Unknown Variance Matrix) Richard A. Pag Bfor-Afr Corol-Impac (BACI) Powr Aalysis For Svral Rlad Populaios (Wih Ukow Variac Marix) Richard A. Hirichs Spmbr 0, 00 Cava: This xprimal dsig ool is a idalizd powr aalysis buil upo svral simplifyig

More information

DEFLECTIONS OF THIN PLATES: INFLUENCE OF THE SLOPE OF THE PLATE IN THE APLICATION OF LINEAR AND NONLINEAR THEORIES

DEFLECTIONS OF THIN PLATES: INFLUENCE OF THE SLOPE OF THE PLATE IN THE APLICATION OF LINEAR AND NONLINEAR THEORIES Procdigs of COBEM 5 Coprigh 5 b BCM 8h Iraioal Cogrss of Mchaical Egirig Novmbr 6-, 5, Ouro Pro, MG DEFLECIONS OF HIN PLES: INFLUENCE OF HE SLOPE OF HE PLE IN HE PLICION OF LINER ND NONLINER HEORIES C..

More information

(A) 1 (B) 1 + (sin 1) (C) 1 (sin 1) (D) (sin 1) 1 (C) and g be the inverse of f. Then the value of g'(0) is. (C) a. dx (a > 0) is

(A) 1 (B) 1 + (sin 1) (C) 1 (sin 1) (D) (sin 1) 1 (C) and g be the inverse of f. Then the value of g'(0) is. (C) a. dx (a > 0) is [STRAIGHT OBJECTIVE TYPE] l Q. Th vlu of h dfii igrl, cos d is + (si ) (si ) (si ) Q. Th vlu of h dfii igrl si d whr [, ] cos cos Q. Vlu of h dfii igrl ( si Q. L f () = d ( ) cos 7 ( ) )d d g b h ivrs

More information

Outline. Overlook. Controllability measures. Observability measures. Infinite Gramians. MOR: Balanced truncation based on infinite Gramians

Outline. Overlook. Controllability measures. Observability measures. Infinite Gramians. MOR: Balanced truncation based on infinite Gramians Ouli Ovrlook Corollabiliy masurs Obsrvabiliy masurs Ifii Gramias MOR: alacd rucaio basd o ifii Gramias Ovrlook alacd rucaio: firs balacig h ruca. Giv a I sysm: / y u d d For covic of discussio w do h sysm

More information

A THREE COMPARTMENT MATHEMATICAL MODEL OF LIVER

A THREE COMPARTMENT MATHEMATICAL MODEL OF LIVER A THREE COPARTENT ATHEATICAL ODEL OF LIVER V. An N. Ch. Paabhi Ramacharyulu Faculy of ahmaics, R D collgs, Hanamonda, Warangal, India Dparmn of ahmaics, Naional Insiu of Tchnology, Warangal, India E-ail:

More information

Some Applications of the Poisson Process

Some Applications of the Poisson Process Applid Maaics, 24, 5, 3-37 Publishd Oli Novbr 24 i SciRs. hp://www.scirp.org/oural/a hp://dx.doi.org/.4236/a.24.59288 So Applicaios of Poisso Procss Kug-Ku s Dpar of Maaics, Ka Uivrsiy, Uio, USA Eail:

More information

Chapter 7 INTEGRAL EQUATIONS

Chapter 7 INTEGRAL EQUATIONS hapr 7 INTERAL EQUATIONS hapr 7 INTERAL EUATIONS hapr 7 Igral Eqaios 7. Normd Vcor Spacs. Eclidia vcor spac. Vcor spac o coios cios ( ). Vcor Spac L ( ) 4. ach-baowsi iqali 5. iowsi iqali 7. Liar Opraors

More information

ANALYTICAL EXPRESSION FOR THE NON-ISOTHERMAL EFFECTIVENESS FACTOR: The n th -order reaction in a slab geometry

ANALYTICAL EXPRESSION FOR THE NON-ISOTHERMAL EFFECTIVENESS FACTOR: The n th -order reaction in a slab geometry ANALYTICAL XPRSSION FOR T NON-ISOTRMAL FFCTIVNSS FACTOR: Th h -ordr racio i a slab gomry riqu Muñoz Tavra Dparm o Biogirig, Ric Uivrsiy, ouso, TX 775-89 USA muoz@ric.du Absrac Th problm o calculaig h civss

More information

Institute of Actuaries of India

Institute of Actuaries of India Insiu of Acuaris of India ubjc CT3 Probabiliy and Mahmaical aisics Novmbr Examinaions INDICATIVE OLUTION Pag of IAI CT3 Novmbr ol. a sampl man = 35 sampl sandard dviaion = 36.6 b for = uppr bound = 35+*36.6

More information

Assessing Reliable Software using SPRT based on LPETM

Assessing Reliable Software using SPRT based on LPETM Iraioal Joural of Compur Applicaios (75 888) Volum 47 No., Ju Assssig Rliabl Sofwar usig SRT basd o LETM R. Saya rasad hd, Associa rofssor Dp. of CS &Egg. AcharyaNagarjua Uivrsiy D. Hariha Assisa rofssor

More information

BMM3553 Mechanical Vibrations

BMM3553 Mechanical Vibrations BMM3553 Mhaial Vibraio Chapr 3: Damp Vibraio of Sigl Dgr of From Sym (Par ) by Ch Ku Ey Nizwa Bi Ch Ku Hui Fauly of Mhaial Egirig mail: y@ump.u.my Chapr Dripio Ep Ouom Su will b abl o: Drmi h aural frquy

More information

Chapter 11 INTEGRAL EQUATIONS

Chapter 11 INTEGRAL EQUATIONS hapr INTERAL EQUATIONS hapr INTERAL EUATIONS Dcmbr 4, 8 hapr Igral Eqaios. Normd Vcor Spacs. Eclidia vcor spac. Vcor spac o coios cios ( ). Vcor Spac L ( ) 4. achy-byaowsi iqaliy 5. iowsi iqaliy. Liar

More information

From Fourier Series towards Fourier Transform

From Fourier Series towards Fourier Transform From Fourir Sris owards Fourir rasform D D d D, d wh lim Dparm of Elcrical ad Compur Eiri D, d wh lim L s Cosidr a fucio G d W ca xprss D i rms of Gw D G Dparm of Elcrical ad Compur Eiri D G G 3 Dparm

More information

(Reference: sections in Silberberg 5 th ed.)

(Reference: sections in Silberberg 5 th ed.) ALE. Atomic Structur Nam HEM K. Marr Tam No. Sctio What is a atom? What is th structur of a atom? Th Modl th structur of a atom (Rfrc: sctios.4 -. i Silbrbrg 5 th d.) Th subatomic articls that chmists

More information

82A Engineering Mathematics

82A Engineering Mathematics Class Nos 5: Sod Ordr Diffrial Eqaio No Homoos 8A Eiri Mahmais Sod Ordr Liar Diffrial Eqaios Homoos & No Homoos v q Homoos No-homoos q ar iv oios fios o h o irval I Sod Ordr Liar Diffrial Eqaios Homoos

More information

EE415/515 Fundamentals of Semiconductor Devices Fall 2012

EE415/515 Fundamentals of Semiconductor Devices Fall 2012 3 EE4555 Fudmls of Smicoducor vics Fll cur 8: PN ucio iod hr 8 Forwrd & rvrs bis Moriy crrir diffusio Brrir lowrd blcd by iffusio rducd iffusio icrsd mioriy crrir drif rif hcd 3 EE 4555. E. Morris 3 3

More information

Review Topics from Chapter 3&4. Fourier Series Fourier Transform Linear Time Invariant (LTI) Systems Energy-Type Signals Power-Type Signals

Review Topics from Chapter 3&4. Fourier Series Fourier Transform Linear Time Invariant (LTI) Systems Energy-Type Signals Power-Type Signals Rviw opics from Chapr 3&4 Fourir Sris Fourir rasform Liar im Ivaria (LI) Sysms Ergy-yp Sigals Powr-yp Sigals Fourir Sris Rprsaio for Priodic Sigals Dfiiio: L h sigal () b a priodic sigal wih priod. ()

More information

Option 3. b) xe dx = and therefore the series is convergent. 12 a) Divergent b) Convergent Proof 15 For. p = 1 1so the series diverges.

Option 3. b) xe dx = and therefore the series is convergent. 12 a) Divergent b) Convergent Proof 15 For. p = 1 1so the series diverges. Optio Chaptr Ercis. Covrgs to Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Divrgs 8 Divrgs Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Covrgs to Covrgs to 8 Proof Covrgs to π l 8 l a b Divrgt π Divrgt

More information

The geometry of surfaces contact

The geometry of surfaces contact Applid ad ompuaioal Mchaics (007 647-656 h gomry of surfacs coac J. Sigl a * J. Švíglr a a Faculy of Applid Scics UWB i Pils Uivrzií 0 00 Pils zch public civd 0 Spmbr 007; rcivd i rvisd form 0 Ocobr 007

More information

Chapter 2 Infinite Series Page 1 of 11. Chapter 2 : Infinite Series

Chapter 2 Infinite Series Page 1 of 11. Chapter 2 : Infinite Series Chatr Ifiit Sris Pag of Sctio F Itgral Tst Chatr : Ifiit Sris By th d of this sctio you will b abl to valuat imror itgrals tst a sris for covrgc by alyig th itgral tst aly th itgral tst to rov th -sris

More information

Lecture 4: Laplace Transforms

Lecture 4: Laplace Transforms Lur 4: Lapla Transforms Lapla and rlad ransformaions an b usd o solv diffrnial quaion and o rdu priodi nois in signals and imags. Basially, hy onvr h drivaiv opraions ino mulipliaion, diffrnial quaions

More information

Pricing and Hedging of Long-term Futures and Forward Contracts by a Three-Factor Model

Pricing and Hedging of Long-term Futures and Forward Contracts by a Three-Factor Model CIRJE-F-68 Pricig ad Hdgig of Log-rm Fuurs ad Forward Coracs by a hr-facor Modl Kichiro Shiraya Mizuho-DL Fiacial chology Co. Ld. Akihiko akahashi Uivrsiy of okyo April 009 CIRJE Discussio Paprs ca b dowloadd

More information

Spring 2006 Process Dynamics, Operations, and Control Lesson 2: Mathematics Review

Spring 2006 Process Dynamics, Operations, and Control Lesson 2: Mathematics Review Spring 6 Procss Dynamics, Opraions, and Conrol.45 Lsson : Mahmaics Rviw. conx and dircion Imagin a sysm ha varis in im; w migh plo is oupu vs. im. A plo migh imply an quaion, and h quaion is usually an

More information

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS

UNIT #5 EXPONENTIAL AND LOGARITHMIC FUNCTIONS Answr Ky Nam: Da: UNIT # EXPONENTIAL AND LOGARITHMIC FUNCTIONS Par I Qusions. Th prssion is quivaln o () () 6 6 6. Th ponnial funcion y 6 could rwrin as y () y y 6 () y y (). Th prssion a is quivaln o

More information

Transfer function and the Laplace transformation

Transfer function and the Laplace transformation Lab No PH-35 Porland Sa Univriy A. La Roa Tranfr funcion and h Laplac ranformaion. INTRODUTION. THE LAPLAE TRANSFORMATION L 3. TRANSFER FUNTIONS 4. ELETRIAL SYSTEMS Analyi of h hr baic paiv lmn R, and

More information

z 1+ 3 z = Π n =1 z f() z = n e - z = ( 1-z) e z e n z z 1- n = ( 1-z/2) 1+ 2n z e 2n e n -1 ( 1-z )/2 e 2n-1 1-2n -1 1 () z

z 1+ 3 z = Π n =1 z f() z = n e - z = ( 1-z) e z e n z z 1- n = ( 1-z/2) 1+ 2n z e 2n e n -1 ( 1-z )/2 e 2n-1 1-2n -1 1 () z Sris Expasio of Rciprocal of Gamma Fuctio. Fuctios with Itgrs as Roots Fuctio f with gativ itgrs as roots ca b dscribd as follows. f() Howvr, this ifiit product divrgs. That is, such a fuctio caot xist

More information

Lecture 2: Current in RC circuit D.K.Pandey

Lecture 2: Current in RC circuit D.K.Pandey Lcur 2: urrn in circui harging of apacior hrough Rsisr L us considr a capacior of capacianc is conncd o a D sourc of.m.f. E hrough a rsisr of rsisanc R and a ky K in sris. Whn h ky K is swichd on, h charging

More information

) and furthermore all X. The definition of the term stationary requires that the distribution fulfills the condition:

) and furthermore all X. The definition of the term stationary requires that the distribution fulfills the condition: Assigm Thomas Aam, Spha Brumm, Haik Lor May 6 h, 3 8 h smsr, 357, 7544, 757 oblm For R b X a raom variabl havig ormal isribuio wih ma µ a variac σ (his is wri as ~ (,) X. by: R a. Is X ) a urhrmor all

More information

LINEAR 2 nd ORDER DIFFERENTIAL EQUATIONS WITH CONSTANT COEFFICIENTS

LINEAR 2 nd ORDER DIFFERENTIAL EQUATIONS WITH CONSTANT COEFFICIENTS Diol Bgyoko (0) I.INTRODUCTION LINEAR d ORDER DIFFERENTIAL EQUATIONS WITH CONSTANT COEFFICIENTS I. Dfiiio All suh diffril quios s i h sdrd or oil form: y + y + y Q( x) dy d y wih y d y d dx dx whr,, d

More information

On the Derivatives of Bessel and Modified Bessel Functions with Respect to the Order and the Argument

On the Derivatives of Bessel and Modified Bessel Functions with Respect to the Order and the Argument Inrnaional Rsarch Journal of Applid Basic Scincs 03 Aailabl onlin a wwwirjabscom ISSN 5-838X / Vol 4 (): 47-433 Scinc Eplorr Publicaions On h Driais of Bssl Modifid Bssl Funcions wih Rspc o h Ordr h Argumn

More information

DYNAMICS and CONTROL

DYNAMICS and CONTROL DYNAMICS an CONTROL Mol IV(I) IV(II) Conrol Sysms Dsign Conrol sysm aramrs Prsn by Pro Albros Profssor of Sysms Enginring an Conrol - UPV Mols: Examls of sysms an signals Mols of sysms an signals Conroll

More information

Worksheet: Taylor Series, Lagrange Error Bound ilearnmath.net

Worksheet: Taylor Series, Lagrange Error Bound ilearnmath.net Taylor s Thorm & Lagrag Error Bouds Actual Error This is th ral amout o rror, ot th rror boud (worst cas scario). It is th dirc btw th actual () ad th polyomial. Stps:. Plug -valu ito () to gt a valu.

More information

AR(1) Process. The first-order autoregressive process, AR(1) is. where e t is WN(0, σ 2 )

AR(1) Process. The first-order autoregressive process, AR(1) is. where e t is WN(0, σ 2 ) AR() Procss Th firs-ordr auorgrssiv procss, AR() is whr is WN(0, σ ) Condiional Man and Varianc of AR() Condiional man: Condiional varianc: ) ( ) ( Ω Ω E E ) var( ) ) ( var( ) var( σ Ω Ω Ω Ω E Auocovarianc

More information

1985 AP Calculus BC: Section I

1985 AP Calculus BC: Section I 985 AP Calculus BC: Sctio I 9 Miuts No Calculator Nots: () I this amiatio, l dots th atural logarithm of (that is, logarithm to th bas ). () Ulss othrwis spcifid, th domai of a fuctio f is assumd to b

More information

Lecture 12: Introduction to nonlinear optics II.

Lecture 12: Introduction to nonlinear optics II. Lcur : Iroduco o olar opcs II r Kužl ropagao of srog opc sgals propr olar ffcs Scod ordr ffcs! Thr-wav mxg has machg codo! Scod harmoc grao! Sum frqucy grao! aramrc grao Thrd ordr ffcs! Four-wav mxg! Opcal

More information

Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem

Mathematical Statistics. Chapter VIII Sampling Distributions and the Central Limit Theorem Mahmacal ascs 8 Chapr VIII amplg Dsrbos ad h Cral Lm Thorm Fcos of radom arabls ar sall of rs sascal applcao Cosdr a s of obsrabl radom arabls L For ampl sppos h arabls ar a radom sampl of s from a poplao

More information

Gauge Theories. Elementary Particle Physics Strong Interaction Fenomenology. Diego Bettoni Academic year

Gauge Theories. Elementary Particle Physics Strong Interaction Fenomenology. Diego Bettoni Academic year Gau Thors Elmary Parcl Physcs Sro Iraco Fomoloy o Bo cadmc yar - Gau Ivarac Gau Ivarac Whr do Laraas or Hamloas com from? How do w kow ha a cra raco should dscrb a acual hyscal sysm? Why s h lcromac raco

More information

Reliability analysis of time - dependent stress - strength system when the number of cycles follows binomial distribution

Reliability analysis of time - dependent stress - strength system when the number of cycles follows binomial distribution raoal Joural of Sascs ad Ssms SSN 97-675 Volum, Numbr 7,. 575-58 sarch da Publcaos h://www.rublcao.com labl aalss of m - dd srss - srgh ssm wh h umbr of ccls follows bomal dsrbuo T.Sumah Umamahswar, N.Swah,

More information

ISSN: [Bellale* et al., 6(1): January, 2017] Impact Factor: 4.116

ISSN: [Bellale* et al., 6(1): January, 2017] Impact Factor: 4.116 IESRT INTERNTIONL OURNL OF ENGINEERING SCIENCES & RESERCH TECHNOLOGY HYBRID FIED POINT THEOREM FOR NONLINER DIFFERENTIL EQUTIONS Sidhshwar Sagram Bllal*, Gash Babrwa Dapk * Dparm o Mahmaics, Daaad Scic

More information

Boyce/DiPrima/Meade 11 th ed, Ch 4.1: Higher Order Linear ODEs: General Theory

Boyce/DiPrima/Meade 11 th ed, Ch 4.1: Higher Order Linear ODEs: General Theory Bo/DiPima/Mad h d Ch.: High Od Lia ODEs: Gal Tho Elma Diffial Eqaios ad Boda Val Poblms h diio b William E. Bo Rihad C. DiPima ad Dog Mad 7 b Joh Wil & Sos I. A h od ODE has h gal fom d d P P P d d W assm

More information

Solution to 1223 The Evil Warden.

Solution to 1223 The Evil Warden. Solutio to 1 Th Evil Ward. This is o of thos vry rar PoWs (I caot thik of aothr cas) that o o solvd. About 10 of you submittd th basic approach, which givs a probability of 47%. I was shockd wh I foud

More information

Trigonometric Formula

Trigonometric Formula MhScop g of 9 FORMULAE SHEET If h lik blow r o-fucioig ihr Sv hi fil o your hrd driv (o h rm lf of h br bov hi pg for viwig off li or ju coll dow h pg. [] Trigoomry formul. [] Tbl of uful rigoomric vlu.

More information

Chapter (8) Estimation and Confedence Intervals Examples

Chapter (8) Estimation and Confedence Intervals Examples Chaptr (8) Estimatio ad Cofdc Itrvals Exampls Typs of stimatio: i. Poit stimatio: Exampl (1): Cosidr th sampl obsrvatios, 17,3,5,1,18,6,16,10 8 X i i1 17 3 5 118 6 16 10 116 X 14.5 8 8 8 14.5 is a poit

More information

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule

Lecture 1: Numerical Integration The Trapezoidal and Simpson s Rule Lcur : Numrical ngraion Th Trapzoidal and Simpson s Rul A problm Th probabiliy of a normally disribud (man µ and sandard dviaion σ ) vn occurring bwn h valus a and b is B A P( a x b) d () π whr a µ b -

More information

A MATHEMATICAL MODEL FOR NATURAL COOLING OF A CUP OF TEA

A MATHEMATICAL MODEL FOR NATURAL COOLING OF A CUP OF TEA MTHEMTICL MODEL FOR NTURL COOLING OF CUP OF TE 1 Mrs.D.Kalpana, 2 Mr.S.Dhvarajan 1 Snior Lcurr, Dparmn of Chmisry, PSB Polychnic Collg, Chnnai, India. 2 ssisan Profssor, Dparmn of Mahmaics, Dr.M.G.R Educaional

More information