CHAPTER HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG. 7.1 SECOND-ORDER SYSTEM Transfer Function

Size: px
Start display at page:

Download "CHAPTER HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG. 7.1 SECOND-ORDER SYSTEM Transfer Function"

Transcription

1 CHAPTER 7 HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG 7. SECOND-ORDER SYSTEM Tranfer Funcion Thi ecion inroduce a baic yem called a econd-order yem or a quadraic lag. Second-order yem are decribed by a econd-order differenial equaion ha relae he oupu variable y o he inpu variable x (he forcing funcion) wih ime a he independen variable. A d y B dy Cy x() (7.) d d A econd-order yem can arie from wo fir-order yem in erie, a we aw in Chap. 6. Some yem are inherenly econd-order, and hey do no reul from a erie combinaion of wo fir-order yem. Inherenly econd-order yem are no exremely common in chemical engineering applicaion. Mo econd-order yem ha we encouner will reul from he addiion of a conroller o a fir-order proce. Le examine an inherenly econd-order yem and develop ome erminology ha will be ueful in our analyi of he conrol of chemical procee. Conider a imple manomeer a hown in Fig. 7. The preure on boh leg of he manomeer i iniially he ame. The lengh of he fluid column in he manomeer i L. A ime, a preure difference i impoed acro he leg of he manomeer. Auming he reuling flow in he manomeer o be laminar and he eady-ae fricion law for drag force in laminar flow o apply a each inan, we will deermine he ranfer funcion beween he applied preure difference P and he manomeer reading h. If we perform a momenum balance on he fluid in he manomeer, we arrive a he following erm: ( Sum of force cauing fluid omove) ( Raeof change of momenum of fluid) (7.) 37

2 38 PART LINEAR OPEN-LOOP SYSTEMS P = P = P P D Reference level = h h/ h/ L Before (Iniial) Afer (Final) FIGURE 7 Manomeer. where Sum of force Un cauing fluid o move balanced preure force cauing moion Fricional force oppoing moion Unbalanced preure force p D p cauing moion ( P P ) gh D r 4 4 Fricional force Skin oppoing moion fricion Shear re a wall a wall Area in conac wih wall Fricional force Wal oppoing moion l p DL 8mV 8m dh p DL p DL D D d ( ) ( ) ( ) The erm for he kin fricion a he wall i obained from he Hagen-Poieuille relaionhip for laminar flow (McCabe, Smih and Harrio, 4). Noe ha V i he average velociy of he fluid in he ube, which i alo he velociy of he inerface, which i equal o dh/ d (ee Fig. 7 ).

3 CHAPTER 7 HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG 39 P P V V h h/ h/ Reference level = FIGURE 7 Average velociy of he fluid in he manomeer. The rae of change of momenum of he fluid [he righ ide of Eq. (7.)] may be expreed a d ( Rae of change of momenum) ( ma velociy momenum correcion facor) d r p D 4 L ( b ) dv d ( ) r p D d h L b 4 d The momenum correcion facor b accoun for he fac ha he fluid ha a parabolic velociy profile in he ube, and he momenum mu be expreed a b m V for laminar flow (ee McCabe, Smih and Harrio, 4). The value of b for laminar flow i 4/3. Subiuing he appropriae erm ino Eq. (7.) produce he deired force balance equaion for he manomeer. r pd 4 4 d h L P P p 3 D p d ( ) gh D 8m dh r p DL 4 4 D d ( (7.3) Rearranging Eq. (7.3), we obain r pd 4 4 d h 8 L m 3 d + D dh p ( DL) gh D pd p r ( P P) d 4 4 and finally, dividing boh ide by r g ( p D /4), we arrive a he andard form for a econd-order yem.

4 4 PART LINEAR OPEN-LOOP SYSTEMS L d h 6mL dh P P P h 3g d rdgd rg rg (7.4) (A more deailed verion of he analyi of he manomeer can be found in Bird e al., 96). Noe ha a wih fir-order yem, andard form ha a coefficien of on he dependen variable erm, h in hi cae. Second-order yem are decribed by a econdorder differenial equaion. We may rewrie hi Eq. (7.4) in general erm a where dy dy z Y X() (7.5) d d L (7.6) 3g z 6mL rdg (7.7) X () P rg Solving for and z from Eq. (7.6) and (7.7) give and Y h (7.8) L 3g (7.9) z m 8 3 L rd g dimenionle (7.) By definiion, boh and z mu be poiive. The reaon for inroducing and z in he paricular form hown in Eq. (7.5) will become clear when we dicu he oluion of Eq. (7.5) for paricular forcing funcion X ( ). Equaion (7.5) i wrien in a andard form ha i widely ued in conrol heory. If he fluid column i moionle ( dy / d ) and locaed a i re poiion ( Y ) before he forcing funcion i applied, he Laplace ranform of Eq. (7.4) become From hi, he ranfer funcion follow: Y () zy () Y () X () (7.) Y () X () z (7.) The ranfer funcion given by Eq. (7.) i wrien in andard form, and we will how laer ha oher phyical yem can be repreened by a ranfer funcion having he

5 CHAPTER 7 HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG 4 denominaor of z. All uch yem are defined a econd-order. Noe ha i require wo parameer, and z, o characerize he dynamic of a econd-order yem in conra o only one parameer for a fir-order yem. We now dicu he repone of a econd-order yem o ome of he common forcing funcion, namely, ep, impule, and inuoidal. Sep Repone If he forcing funcion i a uni-ep funcion, we have X () (7.3) In erm of he manomeer hown in Fig. 7, hi i equivalen o uddenly applying a preure difference [uch ha X ( ) P / r g ] acro he leg of he manomeer a ime. Superpoiion will enable u o deermine eaily he repone o a ep funcion of any oher magniude. Combining Eq. (7.3) wih he ranfer funcion of Eq. (7.) give Y () z (7.4) The quadraic erm in hi equaion may be facored ino wo linear erm ha conain he roo z a z b z z (7.5) (7.6) Equaion (7.4) can now be wrien / Y () ( a)( b) (7.7) The repone of he yem Y ( ) can be found by invering Eq. (7.7). The roo a and b will be real or complex depending on value of he parameer z. The naure of he roo will, in urn, affec he form of Y ( ). The problem may be divided ino he hree cae hown in Table 7.. Each cae will now be dicued. TABLE 7 Sep repone of a econd-order yem Cae y Naure of roo Decripion of repone I < Complex Underdamped or ocillaory II Real and equal Criically damped III > Real Overdamped or nonocillaory

6 4 PART LINEAR OPEN-LOOP SYSTEMS CASE I STEP RESPONSE FOR y <. For hi cae, he inverion of Eq. (7.7) yield he reul z / z Y () e in z an z z (7.8) To derive Eq. (7.8), ue i made of he echnique of Chap. 3. Since z <, Eq. (7.5) o (7.7) indicae a pair of complex conjugae roo in he lef half-plane and a roo a he origin. In erm of he ymbol of Fig. 3, he complex roo correpond o and * and he roo a he origin o 6. The reader hould realize ha in Eq. (7.8), he argumen of he ine funcion i in radian, a i he value of he invere angen erm. By referring o Table 3., we ee ha Y ( ) ha he form z / Y () C e C co z C3 in z (7.9) The conan C, C, and C 3 are found by parial fracion. The reuling equaion i hen pu in he form of Eq. (7.8) by applying he rigonomeric ideniy ued in Chap. 4, Eq. (4.6). The deail are lef a an exercie for he reader. I i eviden from Eq. (7.8) ha Y ( ) a. The naure of he repone can be underood mo clearly by ploing he oluion o Eq. (7.7) a hown in Fig. 7 3, where Y ( ) i ploed again he dimenionle variable / for everal value of z, including hoe above uniy, which will be conidered in he nex ecion. Noe ha for z < all he repone curve are ocillaory in naure and become le ocillaory a z i increaed. The lope a he origin in Fig. 7 3 i zero for all value of z. The repone of a econd-order yem for z < i aid o be underdamped. Wha i he phyical ignificance of an underdamped repone? Uing he manomeer a an example, if we ep-change he preure difference acro an underdamped manomeer, he liquid level in he wo leg will ocillae before abilizing. The ocillaion are characeriic of an underdamped repone. CASE II STEP RESPONSE FOR y. For hi cae, he repone i given by he expreion Y () e / (7.) Thi i derived a follow: Equaion (7.5) and (7.6) how ha he roo and are real and equal. By referring o Fig. 3 and Table 3., i i een ha Eq. (7.) i he correc form. The conan are obained, a uual, by parial fracion. The repone, which i ploed in Fig. 7 3, i nonocillaory. Thi condiion, z, i called criical damping and allow he mo rapid approach of he repone o Y wihou ocillaion.

7 CHAPTER 7 HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG Y()..8.6 ζ = ζ = FIGURE 7 3 Repone of a econd-order yem o a uni-ep forcing funcion. / CASE III STEP RESPONSE FOR z >. For hi cae, he inverion of Eq. (7.7) give he reul Y () z / z e coh z inh z z (7.) where he hyperbolic funcion are defined a e inh a e e e coh a The procedure for obaining Eq. (7.) i parallel o ha ued in he previou cae. The repone ha been ploed in Fig. 7 3 for everal value of z. Noice ha he repone i nonocillaory and become more luggih a z increae. Thi i known a an overdamped repone. A in previou cae, all curve evenually approach he line Y. a a a a

8 44 PART LINEAR OPEN-LOOP SYSTEMS Acually, he repone for z > i no new. We aw i previouly in he dicuion of he ep repone of a yem conaining wo fir-order yem in erie, for which he ranfer funcion i Y () X () ( )( ) (7.) Thi i rue for z > becaue he roo and are real, and he denominaor of Eq. (7.) may be facored ino wo real linear facor. Therefore, Eq. (7.) i equivalen o Eq. (7.) in hi cae. By comparing he linear facor of he denominaor of Eq. (7.) wih hoe of Eq. (7.), i follow ha z z ( ) (7.3) z z ( ) (7.4) Noe ha if, hen and z. The reader hould verify hee reul. Uing MATLAB/Simulink o Deermine he Sep Repone of he Manomeer Conider a manomeer a illuraed in Fig. 7. The manomeer i being ued o deermine he preure difference beween wo inrumen ap on an air line. The working fluid in he manomeer i waer. Deermine he repone of he manomeer o a ep change in preure acro he leg of he manomeer. Daa L cm g 98 cm/ m cp. g/ ( cm ) 3 r. g/cm P rg for cm for D. cm,. cm,.3 cm (Three Cae) for h eworking fluid, waer Soluion. From Eq. (7.4), we have he governing differenial equaion for he manomeer: L 3g d h 6mL dh P P P h d rdgd rg rg

9 CHAPTER 7 HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG 45 In erm of ranformed deviaion variable, hi become Y () zy () Y () X () P P where Y h h and X rg rg 3L 8m and z g rd 3L g Le calculae he ime conan for he manomeer. L ( cm) g 3( 98 cm /) and he damping coefficien for he hree differen ube diameer z 8m 3L 8 [. g/ ( cm )] r 3 D g (. g/cm )( D ) 3( cm) ( 98 cm/ ). 443 D Diameer (cm) Clearly we have one underdamped yem ( z < ), one criically damped yem ( z ), and one overdamped yem ( z > ). One mehod of obaining he repone i o ubiue he value of and z ino Eq. (7.8), (7.), and (7.) and plo he reuling equaion, realizing ha he forcing funcion i ime a uni ep. Anoher way o obain he repone i o ue MATLAB and Simulink o obain he repone of he ranfer funcion Y/X o he forcing funcion inpu X. Y () X () z and X The hree neceary ranfer funcion are a follow: Diameer (cm) z z Tranfer funcion (coninued)

10 46 PART LINEAR OPEN-LOOP SYSTEMS The Simulink model for imulaing he ranfer funcion i hown in Fig. 7 4, and he repone i hown in Fig Overdamped manomeer Preure forcing funcion / Criically damped manomeer Scope Underdamped manomeer FIGURE 7 4 Simulink diagram for manomeer imulaion. Underdamped 8 Criically damped Overdamped Heigh Time FIGURE 7 5 Manomeer repone o ep inpu.

11 CHAPTER 7 HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG 47 Subiuing he value for and z ino Eq. (7.8), (7.), and (7.), we ge Y () z z / e in z z an z 5..3e in 4. an.93.9 rad Y () e / Y () z e / coh z underdamped manomeer 369 e /. criical. 369 ly damped manomeer z inh z 99. { [ ]} e coh(9.54 ).4 inh(9.54 ) z overdamped manomeer Ploing hee repone give he ame reul a he Simulink model. On a pracical noe, noice ha increae wih he oal lengh of he fluid column and ha z increae wih he vicoiy of he fluid. If he damping coefficien z i mall (< <.), he repone of he manomeer o a change in preure can be very ocillaory, and i become difficul o obain accurae reading of he preure. To dampen he ocillaion, i i common pracice o place a rericion on he bend of he ube. Thi increae he drag force of he fluid and i equivalen o increaing m in he equaion for z. Such a rericion (a parially open valve) i called a nubber. Term Ued o Decribe an Underdamped Syem Of hee hree cae, he underdamped repone occur mo frequenly in conrol yem. Hence a number of erm are ued o decribe he underdamped repone quaniaively. Equaion for ome of hee erm are lied below for fuure reference. In general, he erm depend on z and/or. All hee equaion can be derived from he ime repone a given by Eq. (7.8); however, he mahemaical derivaion are lef o he reader a exercie.. Overhoo. Overhoo i a meaure of how much he repone exceed he ulimae value following a ep change and i expreed a he raio A/B in Fig The overhoo for a uni ep i relaed o z by he expreion Overhoo exp pz z (7.5) Thi relaion i ploed in Fig The overhoo increae for decreaing z.

12 48 PART LINEAR OPEN-LOOP SYSTEMS Period T. A C Repone ime limi Y() B T r Rie ime Repone ime FIGURE 7 6 Term ued o decribe an underdamped econd-order repone...8 f n f.6.4 Overhoo. Decay raio ζ FIGURE 7 7 Characeriic of a ep repone of an underdamped econd-order yem. Why are we concerned abou overhoo? Perhap he emperaure in our chemical reacor canno be allowed o exceed a pecified emperaure o proec he caaly from deacivaion, or if i a level conrol yem, we don wan he ank o overflow. If we know hee phyical limiaion, we can deermine allowable value of z and chooe our conrol yem parameer o be ure o ay wihin hoe limi.. Decay raio. The decay raio i defined a he raio of he ize of ucceive peak and i given by C/A in Fig The decay raio i relaed o z by he expreion pz Decay raio exp ( overhoo) z (7.6) which i ploed in Fig Noice ha larger z mean greaer damping, hence greaer decay.

13 CHAPTER 7 HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG Rie ime. Thi i he ime required for he repone o fir reach i ulimae value and i labeled r in Fig The reader can verify from Fig. 7 3 ha r increae wih increaing z. 4. Repone ime. Thi i he ime required for he repone o come wihin 5 percen of i ulimae value and remain here. The repone ime i indicaed in Fig The limi 5 percen are arbirary, and oher limi can be ued for defining a repone ime. 5. Period of ocillaion. From Eq. (7.8), he radian frequency (radian/ime) i he coefficien of in he ine erm; hu, radian frequency w z (7.7) Since he radian frequency w i relaed o he cyclical frequency f by w p f, i follow ha f T p z (7.8) where T i he period of ocillaion (ime/cycle). In erm of Fig. 7 6, T i he ime elaped beween peak. I i alo he ime elaped beween alernae croing of he line Y. 6. Naural period of ocillaion. If he damping i eliminaed [ B in Eq. (7.), or z ], he yem ocillae coninuouly wihou aenuaion in ampliude. Under hee naural or undamped condiion, he radian frequency i /, a hown by Eq. (7.7) when z. Thi frequency i referred o a he naural frequency w n : wn (7.9) The correponding naural cyclical frequency f n and period T n are relaed by he expreion fn T p (7.3) n Thu, ha he ignificance of he undamped period. From Eq. (7.8) and (7.3), he naural frequency i relaed o he acual frequency by he expreion f z f n which i ploed in Fig Noice ha for z <.5 he naural frequency i nearly he ame a he acual frequency. In ummary, i i eviden ha z i a meaure of he degree of damping, or he ocillaory characer, and i a meaure of he period, or peed, of he repone of a econd-order yem.

14 5 PART LINEAR OPEN-LOOP SYSTEMS Impule Repone If a uni impule d ( ) i applied o he econd-order yem, hen from Eq. (7.) and (3A.) he ranform of he repone i Y () z (7.3) A in he cae of he ep inpu, he naure of he repone o a uni impule will depend on wheher he roo of he denominaor of Eq. (7.3) are real or complex. The problem i again divided ino he hree cae hown in Table 7., and each i dicued below. CASE I IMPULSE RESPONSE FOR y <. The inverion of Eq. (7.3) for z < yield he reul Y () z z / e in z (7.3) which i ploed in Fig The lope a he origin in Fig. 7 8 i. for all value of z. A imple way o obain Eq. (7.3) from he ep repone of Eq. (7.8) i o ake he derivaive of Eq. (7.8) wih repec o (remember from App. 3A ha he derivaive of he uni-ep funcion i he impule funcion). Comparion of Eq. (7.4) and (7.3) how ha Y () Y () (7.33) impule ep ζ = τy(). = / FIGURE 7 8 Repone of a econd-order yem o a uni-impule forcing funcion.

15 CHAPTER 7 HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG 5 The preence of on he righ ide of Eq. (7.33) implie differeniaion wih repec o in he ime repone. In oher word, he invere ranform of Eq. (7.3) i d Y () impule Y () d ( ) (7.34) Applicaion of Eq. (7.34) o Eq. (7.8) yield Eq. (7.3). Thi principle alo yield he reul for he nex wo cae. CASE II IMPULSE RESPONSE FOR y. For he criically damped cae, he repone i given by ep which i ploed in Fig Y () e / (7.35) CASE III IMPULSE RESPONSE FOR y >. For he overdamped cae, he repone i given by Y () z e z / inh z (7.36) which i alo ploed in Fig To ummarize, he impule repone curve of Fig. 7 8 how he ame general behavior a he ep repone curve of Fig However, he impule repone alway reurn o zero. Term uch a decay raio, period of ocillaion, ec., may alo be ued o decribe he impule repone. Many conrol yem exhibi ranien repone uch a hoe of Fig Sinuoidal Repone If he forcing funcion applied o he econd-order yem i inuoidal X ()Ainw hen i follow from Eq. (7.) and (4.3) ha Y () Aw ( w )( z ) (7.37) The inverion of Eq. (7.37) may be accomplihed by fir facoring he wo quadraic erm o give Aw / Y () ( jw )( jw)( a)( b) (7.38)

16 5 PART LINEAR OPEN-LOOP SYSTEMS ( Here a and b are he roo of he denominaor of he ranfer funcion and are given by Eq. (7.5) and (7.6). For he cae of an underdamped yem ( z < ), he roo of he denominaor of Eq. (7.38) are a pair of pure imaginary roo ( j w, j w ) conribued by he forcing funcion and a pair of complex roo z / j z /, z / j z / We may wrie he form of he repone Y ( ) by referring o Fig. 3 and Table 3.; hu z / Y () C C e cow inw C3 co z C4 in z (7.39) The conan are evaluaed by parial fracion. Noice in Eq. (7.39) ha a, only he fir wo erm do no become zero. Thee remaining erm are he ulimae periodic oluion; hu Y () Ccow Cinw (7.4) The reader hould verify ha Eq. (7.4) i alo rue for z. From hi lile effor, we ee already ha he repone of he econd-order yem o a inuoidal driving funcion i ulimaely inuoidal and ha he ame frequency a he driving funcion. If he conan C and C are evaluaed, we ge from Eq. (4.6) and (7.4) Y () A ( w) zw ( ) in ( w f) (7.4) where f zw an ( w ) By comparing Eq. (7.4) wih he forcing funcion i i een ha X () Ainw. The raio of he oupu ampliude o he inpu ampliude i oupu ampliude Ampliude raio inpu ampliude ( w ) zw ( ) I will be hown in Chap. 5 ha hi may be greaer or le han, depending upon he value of z and w. Thi i in direc conra o he inuoidal repone of he fir-order yem, where he raio of he oupu ampliude o he inpu ampliude i alway le han.. The oupu lag he inpu by phae angle f. f phae angle an zw ( w )

17 CHAPTER 7 HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG 53 I can be een from Eq. (7.4), and will be hown in Chap. 5, ha f approache 8 aympoically a w increae. The phae lag of he fir-order yem, on he oher hand, can never exceed 9. Dicuion of oher characeriic of he inuoidal repone will be deferred unil Chap. 5. We now have a our dipoal coniderable informaion abou he dynamic behavior of he econd-order yem. I happen ha many conrol yem ha are no ruly econd-order exhibi ep repone very imilar o hoe of Fig Such yem are ofen characerized by econd-order equaion for approximae mahemaical analyi. Hence, he econd-order yem i quie imporan in conrol heory, and frequen ue will be made of he maerial in hi chaper. 7. TRANSPORTATION LAG A phenomenon ha i ofen preen in flow yem i he ranporaion lag. Synonym for hi erm are dead ime and diance velociy lag. A an example, conider he yem hown in Fig. 7 9, in which a liquid flow hrough an inulaed ube of uniform cro-ecional area A and lengh L a a x() q Cro-ecional area = A L FIGURE 7 9 Syem wih ranporaion lag. y() q conan volumeric flow rae q. The deniy r and he hea capaciy C are conan. The ube wall ha negligible hea capaciy, and he velociy profile i fla (plug flow). The emperaure x of he enering fluid varie wih ime, and i i deired o find he repone of he oule emperaure y ( ) in erm of a ranfer funcion. A uual, i i aumed ha he yem i iniially a eady ae; for hi yem, i i obviou ha he inle emperaure equal he oule emperaure; i.e., x y (7.4) If a ep change were made in x ( ) a, he change would no be deeced a he end of he ube unil laer, where i he ime required for he enering fluid o pa hrough he ube. Thi imple ep repone i hown in Fig. 7. If he variaion in x ( ) were ome arbirary funcion, a hown in Fig. 7, he repone y ( ) a he end of he pipe would be idenical wih x ( ) bu again delayed by x() x() y() τ y() τ τ (a) (b) FIGURE 7 Repone of ranporaion lag o variou inpu.

18 54 PART LINEAR OPEN-LOOP SYSTEMS uni of ime. The ranporaion lag parameer i imply he ime needed for a paricle of fluid o flow from he enrance of he ube o he exi, and i can be calculaed from he expreion volume of ube volumeric flow rae or AL q I can be een from Fig. 7 ha he relaionhip beween y ( ) and x ( ) i (7.43) y () x( ) (7.44) Subracing Eq. (7.4) from Eq. (7.44) and inroducing he deviaion variable X x x and Y y y give Y () X ( ) (7.45) If he Laplace ranform of X ( ) i X ( ), hen he Laplace ranform of X ( ) i e X ( ). Thi reul follow from he heorem on ranlaion of a funcion, which wa dicued in App. 3A. Equaion (7.45) become Y () e X () or Y () e X () (7.46) Therefore, he ranfer funcion of a ranporaion lag i e. The ranporaion lag i quie common in he chemical proce indurie where a fluid i ranpored hrough a pipe. We hall ee in a laer chaper ha he preence of a ranporaion lag in a conrol yem can make i much more difficul o conrol. In general, uch lag hould be avoided if poible by placing equipmen cloe ogeher. They can eldom be enirely eliminaed. APPROXIMATION OF TRANSPORT LAG. The ranpor lag i quie differen from he oher ranfer funcion (fir-order, econd-order, ec.) ha we have dicued in ha i i no a raional funcion (i.e., a raio of polynomial.) A hown in Chap. 3, a yem conaining a ranpor lag canno be analyzed for abiliy by he Rouh e. The ranpor lag can alo be difficul o imulae by compuer. For hee reaon, everal approximaion of ranpor lag ha are ueful in conrol calculaion are preened here. One approach o approximaing he ranpor lag i o wrie e a / e and o expre he denominaor a a Taylor erie; he reul i e e 3 3 / / 3!

19 CHAPTER 7 HIGHER-ORDER SYSTEMS: SECOND-ORDER AND TRANSPORTATION LAG 55 Keeping only he fir wo erm in he denominaor give e (7.47) Thi approximaion, which i imply a fir-order lag, i a crude approximaion of a ranpor lag. An improvemen can be made by expreing he ranpor lag a / e e / e Expanding numeraor and denominaor in a Taylor erie and keeping only erm of fir-order give e / / fir-order Padé (7.48) Thi expreion i alo known a a fir-order Padé approximaion. Anoher well-known approximaion for a ranpor lag i he econd-order Padé approximaion: e / / / / econd-order Padé (7.49) Equaion (7.48) i no merely he raio of wo Taylor erie; i ha been opimized o give a beer approximaion. Y () () (3) FIGURE 7 Sep repone o approximaion of he ranpor lag e : () ; () fir-order Padé; (3) econd-order Padé ; (4) e. (4) /τ The ep repone of he hree approximaion of ranpor lag preened here are hown in Fig. 7. The ep repone of e i alo hown for comparion. Noice ha he repone for he fir-order Padé approximaion drop o before riing exponenially oward. The repone for he econdorder Padé approximaion jump o and hen decend o below before reurning gradually back o. Alhough none of he approximaion for e i very accurae, he approximaion for e i more ueful when i i muliplied by everal fir-order or econd-order ranfer funcion. In hi cae, he oher ranfer funcion filer ou he high-frequency conen of he ignal paing hrough he ranpor lag, wih he reul ha he ranpor lag approximaion, when combined wih oher ranfer funcion, provide a aifacory reul in many cae. The accuracy of a ranpor lag can be evaluaed mo clearly in erm of frequency repone, a opic covered laer in hi book.

Chapter 7: Inverse-Response Systems

Chapter 7: Inverse-Response Systems Chaper 7: Invere-Repone Syem Normal Syem Invere-Repone Syem Baic Sar ou in he wrong direcion End up in he original eady-ae gain value Two or more yem wih differen magniude and cale in parallel Main yem

More information

CHAPTER 7: SECOND-ORDER CIRCUITS

CHAPTER 7: SECOND-ORDER CIRCUITS EEE5: CI RCUI T THEORY CHAPTER 7: SECOND-ORDER CIRCUITS 7. Inroducion Thi chaper conider circui wih wo orage elemen. Known a econd-order circui becaue heir repone are decribed by differenial equaion ha

More information

u(t) Figure 1. Open loop control system

u(t) Figure 1. Open loop control system Open loop conrol v cloed loop feedbac conrol The nex wo figure preen he rucure of open loop and feedbac conrol yem Figure how an open loop conrol yem whoe funcion i o caue he oupu y o follow he reference

More information

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship Laplace Tranform (Lin & DeCarlo: Ch 3) ENSC30 Elecric Circui II The Laplace ranform i an inegral ranformaion. I ranform: f ( ) F( ) ime variable complex variable From Euler > Lagrange > Laplace. Hence,

More information

6.8 Laplace Transform: General Formulas

6.8 Laplace Transform: General Formulas 48 HAP. 6 Laplace Tranform 6.8 Laplace Tranform: General Formula Formula Name, ommen Sec. F() l{ f ()} e f () d f () l {F()} Definiion of Tranform Invere Tranform 6. l{af () bg()} al{f ()} bl{g()} Lineariy

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signal & Syem Prof. Mark Fowler Noe Se #27 C-T Syem: Laplace Tranform Power Tool for yem analyi Reading Aignmen: Secion 6.1 6.3 of Kamen and Heck 1/18 Coure Flow Diagram The arrow here how concepual

More information

Sample Final Exam (finals03) Covering Chapters 1-9 of Fundamentals of Signals & Systems

Sample Final Exam (finals03) Covering Chapters 1-9 of Fundamentals of Signals & Systems Sample Final Exam Covering Chaper 9 (final04) Sample Final Exam (final03) Covering Chaper 9 of Fundamenal of Signal & Syem Problem (0 mar) Conider he caual opamp circui iniially a re depiced below. I LI

More information

6.302 Feedback Systems Recitation : Phase-locked Loops Prof. Joel L. Dawson

6.302 Feedback Systems Recitation : Phase-locked Loops Prof. Joel L. Dawson 6.32 Feedback Syem Phae-locked loop are a foundaional building block for analog circui deign, paricularly for communicaion circui. They provide a good example yem for hi cla becaue hey are an excellen

More information

6 December 2013 H. T. Hoang - www4.hcmut.edu.vn/~hthoang/ 1

6 December 2013 H. T. Hoang - www4.hcmut.edu.vn/~hthoang/ 1 Lecure Noe Fundamenal of Conrol Syem Inrucor: Aoc. Prof. Dr. Huynh Thai Hoang Deparmen of Auomaic Conrol Faculy of Elecrical & Elecronic Engineering Ho Chi Minh Ciy Univeriy of Technology Email: hhoang@hcmu.edu.vn

More information

13.1 Circuit Elements in the s Domain Circuit Analysis in the s Domain The Transfer Function and Natural Response 13.

13.1 Circuit Elements in the s Domain Circuit Analysis in the s Domain The Transfer Function and Natural Response 13. Chaper 3 The Laplace Tranform in Circui Analyi 3. Circui Elemen in he Domain 3.-3 Circui Analyi in he Domain 3.4-5 The Tranfer Funcion and Naural Repone 3.6 The Tranfer Funcion and he Convoluion Inegral

More information

EE Control Systems LECTURE 2

EE Control Systems LECTURE 2 Copyrigh F.L. Lewi 999 All righ reerved EE 434 - Conrol Syem LECTURE REVIEW OF LAPLACE TRANSFORM LAPLACE TRANSFORM The Laplace ranform i very ueful in analyi and deign for yem ha are linear and ime-invarian

More information

Chapter 6. Laplace Transforms

Chapter 6. Laplace Transforms 6- Chaper 6. Laplace Tranform 6.4 Shor Impule. Dirac Dela Funcion. Parial Fracion 6.5 Convoluion. Inegral Equaion 6.6 Differeniaion and Inegraion of Tranform 6.7 Syem of ODE 6.4 Shor Impule. Dirac Dela

More information

CONTROL SYSTEMS. Chapter 10 : State Space Response

CONTROL SYSTEMS. Chapter 10 : State Space Response CONTROL SYSTEMS Chaper : Sae Space Repone GATE Objecive & Numerical Type Soluion Queion 5 [GATE EE 99 IIT-Bombay : Mark] Conider a econd order yem whoe ae pace repreenaion i of he form A Bu. If () (),

More information

Some Basic Information about M-S-D Systems

Some Basic Information about M-S-D Systems Some Basic Informaion abou M-S-D Sysems 1 Inroducion We wan o give some summary of he facs concerning unforced (homogeneous) and forced (non-homogeneous) models for linear oscillaors governed by second-order,

More information

CHAPTER. Forced Equations and Systems { } ( ) ( ) 8.1 The Laplace Transform and Its Inverse. Transforms from the Definition.

CHAPTER. Forced Equations and Systems { } ( ) ( ) 8.1 The Laplace Transform and Its Inverse. Transforms from the Definition. CHAPTER 8 Forced Equaion and Syem 8 The aplace Tranform and I Invere Tranform from he Definiion 5 5 = b b {} 5 = 5e d = lim5 e = ( ) b {} = e d = lim e + e d b = (inegraion by par) = = = = b b ( ) ( )

More information

Chapter 6. Laplace Transforms

Chapter 6. Laplace Transforms Chaper 6. Laplace Tranform Kreyzig by YHLee;45; 6- An ODE i reduced o an algebraic problem by operaional calculu. The equaion i olved by algebraic manipulaion. The reul i ranformed back for he oluion of

More information

18.03SC Unit 3 Practice Exam and Solutions

18.03SC Unit 3 Practice Exam and Solutions Sudy Guide on Sep, Dela, Convoluion, Laplace You can hink of he ep funcion u() a any nice mooh funcion which i for < a and for > a, where a i a poiive number which i much maller han any ime cale we care

More information

Chapter 2. First Order Scalar Equations

Chapter 2. First Order Scalar Equations Chaper. Firs Order Scalar Equaions We sar our sudy of differenial equaions in he same way he pioneers in his field did. We show paricular echniques o solve paricular ypes of firs order differenial equaions.

More information

Algorithmic Discrete Mathematics 6. Exercise Sheet

Algorithmic Discrete Mathematics 6. Exercise Sheet Algorihmic Dicree Mahemaic. Exercie Shee Deparmen of Mahemaic SS 0 PD Dr. Ulf Lorenz 7. and 8. Juni 0 Dipl.-Mah. David Meffer Verion of June, 0 Groupwork Exercie G (Heap-Sor) Ue Heap-Sor wih a min-heap

More information

Discussion Session 2 Constant Acceleration/Relative Motion Week 03

Discussion Session 2 Constant Acceleration/Relative Motion Week 03 PHYS 100 Dicuion Seion Conan Acceleraion/Relaive Moion Week 03 The Plan Today you will work wih your group explore he idea of reference frame (i.e. relaive moion) and moion wih conan acceleraion. You ll

More information

Mon Apr 2: Laplace transform and initial value problems like we studied in Chapter 5

Mon Apr 2: Laplace transform and initial value problems like we studied in Chapter 5 Mah 225-4 Week 2 April 2-6 coninue.-.3; alo cover par of.4-.5, EP 7.6 Mon Apr 2:.-.3 Laplace ranform and iniial value problem like we udied in Chaper 5 Announcemen: Warm-up Exercie: Recall, The Laplace

More information

EE202 Circuit Theory II

EE202 Circuit Theory II EE202 Circui Theory II 2017-2018, Spring Dr. Yılmaz KALKAN I. Inroducion & eview of Fir Order Circui (Chaper 7 of Nilon - 3 Hr. Inroducion, C and L Circui, Naural and Sep epone of Serie and Parallel L/C

More information

CONTROL SYSTEMS. Chapter 3 Mathematical Modelling of Physical Systems-Laplace Transforms. Prof.Dr. Fatih Mehmet Botsalı

CONTROL SYSTEMS. Chapter 3 Mathematical Modelling of Physical Systems-Laplace Transforms. Prof.Dr. Fatih Mehmet Botsalı CONTROL SYSTEMS Chaper Mahemaical Modelling of Phyical Syem-Laplace Tranform Prof.Dr. Faih Mehme Boalı Definiion Tranform -- a mahemaical converion from one way of hinking o anoher o make a problem eaier

More information

Randomized Perfect Bipartite Matching

Randomized Perfect Bipartite Matching Inenive Algorihm Lecure 24 Randomized Perfec Biparie Maching Lecurer: Daniel A. Spielman April 9, 208 24. Inroducion We explain a randomized algorihm by Ahih Goel, Michael Kapralov and Sanjeev Khanna for

More information

Instrumentation & Process Control

Instrumentation & Process Control Chemical Engineering (GTE & PSU) Poal Correpondence GTE & Public Secor Inrumenaion & Proce Conrol To Buy Poal Correpondence Package call a -999657855 Poal Coure ( GTE & PSU) 5 ENGINEERS INSTITUTE OF INDI.

More information

LAPLACE TRANSFORM AND TRANSFER FUNCTION

LAPLACE TRANSFORM AND TRANSFER FUNCTION CHBE320 LECTURE V LAPLACE TRANSFORM AND TRANSFER FUNCTION Professor Dae Ryook Yang Spring 2018 Dep. of Chemical and Biological Engineering 5-1 Road Map of he Lecure V Laplace Transform and Transfer funcions

More information

Chapter 9 - The Laplace Transform

Chapter 9 - The Laplace Transform Chaper 9 - The Laplace Tranform Selece Soluion. Skech he pole-zero plo an region of convergence (if i exi) for hee ignal. ω [] () 8 (a) x e u = 8 ROC σ ( ) 3 (b) x e co π u ω [] ( ) () (c) x e u e u ROC

More information

1 Motivation and Basic Definitions

1 Motivation and Basic Definitions CSCE : Deign and Analyi of Algorihm Noe on Max Flow Fall 20 (Baed on he preenaion in Chaper 26 of Inroducion o Algorihm, 3rd Ed. by Cormen, Leieron, Rive and Sein.) Moivaion and Baic Definiion Conider

More information

Let. x y. denote a bivariate time series with zero mean.

Let. x y. denote a bivariate time series with zero mean. Linear Filer Le x y : T denoe a bivariae ime erie wih zero mean. Suppoe ha he ime erie {y : T} i conruced a follow: y a x The ime erie {y : T} i aid o be conruced from {x : T} by mean of a Linear Filer.

More information

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2)

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2) Laplace Tranform Maoud Malek The Laplace ranform i an inegral ranform named in honor of mahemaician and aronomer Pierre-Simon Laplace, who ued he ranform in hi work on probabiliy heory. I i a powerful

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 30 Signal & Syem Prof. ark Fowler oe Se #34 C-T Tranfer Funcion and Frequency Repone /4 Finding he Tranfer Funcion from Differenial Eq. Recall: we found a DT yem Tranfer Funcion Hz y aking he ZT of

More information

, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max

, the. L and the L. x x. max. i n. It is easy to show that these two norms satisfy the following relation: x x n x = (17.3) max ecure 8 7. Sabiliy Analyi For an n dimenional vecor R n, he and he vecor norm are defined a: = T = i n i (7.) I i eay o how ha hee wo norm aify he following relaion: n (7.) If a vecor i ime-dependen, hen

More information

Design of Controller for Robot Position Control

Design of Controller for Robot Position Control eign of Conroller for Robo oiion Conrol Two imporan goal of conrol: 1. Reference inpu racking: The oupu mu follow he reference inpu rajecory a quickly a poible. Se-poin racking: Tracking when he reference

More information

13.1 Accelerating Objects

13.1 Accelerating Objects 13.1 Acceleraing Objec A you learned in Chaper 12, when you are ravelling a a conan peed in a raigh line, you have uniform moion. However, mo objec do no ravel a conan peed in a raigh line o hey do no

More information

Exponential Sawtooth

Exponential Sawtooth ECPE 36 HOMEWORK 3: PROPERTIES OF THE FOURIER TRANSFORM SOLUTION. Exponenial Sawooh: The eaie way o do hi problem i o look a he Fourier ranform of a ingle exponenial funcion, () = exp( )u(). From he able

More information

Physics 240: Worksheet 16 Name

Physics 240: Worksheet 16 Name Phyic 4: Workhee 16 Nae Non-unifor circular oion Each of hee proble involve non-unifor circular oion wih a conan α. (1) Obain each of he equaion of oion for non-unifor circular oion under a conan acceleraion,

More information

10. State Space Methods

10. State Space Methods . Sae Space Mehods. Inroducion Sae space modelling was briefly inroduced in chaper. Here more coverage is provided of sae space mehods before some of heir uses in conrol sysem design are covered in he

More information

Curvature. Institute of Lifelong Learning, University of Delhi pg. 1

Curvature. Institute of Lifelong Learning, University of Delhi pg. 1 Dicipline Coure-I Semeer-I Paper: Calculu-I Leon: Leon Developer: Chaianya Kumar College/Deparmen: Deparmen of Mahemaic, Delhi College of r and Commerce, Univeriy of Delhi Iniue of Lifelong Learning, Univeriy

More information

8.1. a) For step response, M input is u ( t) Taking inverse Laplace transform. as α 0. Ideal response, K c. = Kc Mτ D + For ramp response, 8-1

8.1. a) For step response, M input is u ( t) Taking inverse Laplace transform. as α 0. Ideal response, K c. = Kc Mτ D + For ramp response, 8-1 8. a For ep repone, inpu i u, U Y a U α α Y a α α Taking invere Laplae ranform a α e e / α / α A α 0 a δ 0 e / α a δ deal repone, α d Y i Gi U i δ Hene a α 0 a i For ramp repone, inpu i u, U Soluion anual

More information

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is UNIT IMPULSE RESPONSE, UNIT STEP RESPONSE, STABILITY. Uni impulse funcion (Dirac dela funcion, dela funcion) rigorously defined is no sricly a funcion, bu disribuion (or measure), precise reamen requires

More information

NEUTRON DIFFUSION THEORY

NEUTRON DIFFUSION THEORY NEUTRON DIFFUSION THEORY M. Ragheb 4//7. INTRODUCTION The diffuion heory model of neuron ranpor play a crucial role in reacor heory ince i i imple enough o allow cienific inigh, and i i ufficienly realiic

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients Secion 3.5 Nonhomogeneous Equaions; Mehod of Undeermined Coefficiens Key Terms/Ideas: Linear Differenial operaor Nonlinear operaor Second order homogeneous DE Second order nonhomogeneous DE Soluion o homogeneous

More information

Vehicle Arrival Models : Headway

Vehicle Arrival Models : Headway Chaper 12 Vehicle Arrival Models : Headway 12.1 Inroducion Modelling arrival of vehicle a secion of road is an imporan sep in raffic flow modelling. I has imporan applicaion in raffic flow simulaion where

More information

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3 and d = c b - b c c d = c b - b c c This process is coninued unil he nh row has been compleed. The complee array of coefficiens is riangular. Noe ha in developing he array an enire row may be divided or

More information

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow.

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow. CSE 202: Deign and Analyi of Algorihm Winer 2013 Problem Se 3 Inrucor: Kamalika Chaudhuri Due on: Tue. Feb 26, 2013 Inrucion For your proof, you may ue any lower bound, algorihm or daa rucure from he ex

More information

Introduction to SLE Lecture Notes

Introduction to SLE Lecture Notes Inroducion o SLE Lecure Noe May 13, 16 - The goal of hi ecion i o find a ufficien condiion of λ for he hull K o be generaed by a imple cure. I urn ou if λ 1 < 4 hen K i generaed by a imple curve. We will

More information

1 CHAPTER 14 LAPLACE TRANSFORMS

1 CHAPTER 14 LAPLACE TRANSFORMS CHAPTER 4 LAPLACE TRANSFORMS 4 nroducion f x) i a funcion of x, where x lie in he range o, hen he funcion p), defined by p) px e x) dx, 4 i called he Laplace ranform of x) However, in hi chaper, where

More information

Notes on cointegration of real interest rates and real exchange rates. ρ (2)

Notes on cointegration of real interest rates and real exchange rates. ρ (2) Noe on coinegraion of real inere rae and real exchange rae Charle ngel, Univeriy of Wiconin Le me ar wih he obervaion ha while he lieraure (mo prominenly Meee and Rogoff (988) and dion and Paul (993))

More information

TP B.2 Rolling resistance, spin resistance, and "ball turn"

TP B.2 Rolling resistance, spin resistance, and ball turn echnical proof TP B. olling reiance, pin reiance, and "ball urn" upporing: The Illuraed Principle of Pool and Billiard hp://billiard.coloae.edu by Daid G. Alciaore, PhD, PE ("Dr. Dae") echnical proof originally

More information

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes Some common engineering funcions 2.7 Inroducion This secion provides a caalogue of some common funcions ofen used in Science and Engineering. These include polynomials, raional funcions, he modulus funcion

More information

Piecewise-Defined Functions and Periodic Functions

Piecewise-Defined Functions and Periodic Functions 28 Piecewie-Defined Funcion and Periodic Funcion A he ar of our udy of he Laplace ranform, i wa claimed ha he Laplace ranform i paricularly ueful when dealing wih nonhomogeneou equaion in which he forcing

More information

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V ME 352 VETS 2. VETS Vecor algebra form he mahemaical foundaion for kinemaic and dnamic. Geomer of moion i a he hear of boh he kinemaic and dnamic of mechanical em. Vecor anali i he imehonored ool for decribing

More information

Math 333 Problem Set #2 Solution 14 February 2003

Math 333 Problem Set #2 Solution 14 February 2003 Mah 333 Problem Se #2 Soluion 14 February 2003 A1. Solve he iniial value problem dy dx = x2 + e 3x ; 2y 4 y(0) = 1. Soluion: This is separable; we wrie 2y 4 dy = x 2 + e x dx and inegrae o ge The iniial

More information

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t...

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t... Mah 228- Fri Mar 24 5.6 Marix exponenials and linear sysems: The analogy beween firs order sysems of linear differenial equaions (Chaper 5) and scalar linear differenial equaions (Chaper ) is much sronger

More information

t )? How would you have tried to solve this problem in Chapter 3?

t )? How would you have tried to solve this problem in Chapter 3? Exercie 9) Ue Laplace ranform o wrie down he oluion o 2 x x = F in x = x x = v. wha phenomena do oluion o hi DE illurae (even hough we're forcing wih in co )? How would you have ried o olve hi problem

More information

Final Spring 2007

Final Spring 2007 .615 Final Spring 7 Overview The purpose of he final exam is o calculae he MHD β limi in a high-bea oroidal okamak agains he dangerous n = 1 exernal ballooning-kink mode. Effecively, his corresponds o

More information

Numerical Dispersion

Numerical Dispersion eview of Linear Numerical Sabiliy Numerical Dispersion n he previous lecure, we considered he linear numerical sabiliy of boh advecion and diffusion erms when approimaed wih several spaial and emporal

More information

Control Systems. Lecture 9 Frequency Response. Frequency Response

Control Systems. Lecture 9 Frequency Response. Frequency Response Conrol Syem Lecure 9 Frequency eone Frequency eone We now know how o analyze and deign yem via -domain mehod which yield dynamical informaion The reone are decribed by he exonenial mode The mode are deermined

More information

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method ME 352 GRHICL VELCITY NLYSIS 52 GRHICL VELCITY NLYSIS olygon Mehod Velociy analyi form he hear of kinemaic and dynamic of mechanical yem Velociy analyi i uually performed following a poiion analyi; ie,

More information

s-domain Circuit Analysis

s-domain Circuit Analysis Domain ircui Analyi Operae direcly in he domain wih capacior, inducor and reior Key feaure lineariy i preerved c decribed by ODE and heir I Order equal number of plu number of Elemenbyelemen and ource

More information

Buckling of a structure means failure due to excessive displacements (loss of structural stiffness), and/or

Buckling of a structure means failure due to excessive displacements (loss of structural stiffness), and/or Buckling Buckling of a rucure mean failure due o exceive diplacemen (lo of rucural iffne), and/or lo of abiliy of an equilibrium configuraion of he rucure The rule of humb i ha buckling i conidered a mode

More information

Sub Module 2.6. Measurement of transient temperature

Sub Module 2.6. Measurement of transient temperature Mechanical Measuremens Prof. S.P.Venkaeshan Sub Module 2.6 Measuremen of ransien emperaure Many processes of engineering relevance involve variaions wih respec o ime. The sysem properies like emperaure,

More information

Chapter 7 Response of First-order RL and RC Circuits

Chapter 7 Response of First-order RL and RC Circuits Chaper 7 Response of Firs-order RL and RC Circuis 7.- The Naural Response of RL and RC Circuis 7.3 The Sep Response of RL and RC Circuis 7.4 A General Soluion for Sep and Naural Responses 7.5 Sequenial

More information

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws

Chapter 15: Phenomena. Chapter 15 Chemical Kinetics. Reaction Rates. Reaction Rates R P. Reaction Rates. Rate Laws Chaper 5: Phenomena Phenomena: The reacion (aq) + B(aq) C(aq) was sudied a wo differen emperaures (98 K and 35 K). For each emperaure he reacion was sared by puing differen concenraions of he 3 species

More information

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3.

dt = C exp (3 ln t 4 ). t 4 W = C exp ( ln(4 t) 3) = C(4 t) 3. Mah Rahman Exam Review Soluions () Consider he IVP: ( 4)y 3y + 4y = ; y(3) = 0, y (3) =. (a) Please deermine he longes inerval for which he IVP is guaraneed o have a unique soluion. Soluion: The disconinuiies

More information

PHYSICS 151 Notes for Online Lecture #4

PHYSICS 151 Notes for Online Lecture #4 PHYSICS 5 Noe for Online Lecure #4 Acceleraion The ga pedal in a car i alo called an acceleraor becaue preing i allow you o change your elociy. Acceleraion i how fa he elociy change. So if you ar fro re

More information

Frequency Response. We now know how to analyze and design ccts via s- domain methods which yield dynamical information

Frequency Response. We now know how to analyze and design ccts via s- domain methods which yield dynamical information Frequency Repone We now now how o analyze and deign cc via - domain mehod which yield dynamical informaion Zero-ae repone Zero-inpu repone Naural repone Forced repone The repone are decribed by he exponenial

More information

Module 2 F c i k c s la l w a s o s f dif di fusi s o i n

Module 2 F c i k c s la l w a s o s f dif di fusi s o i n Module Fick s laws of diffusion Fick s laws of diffusion and hin film soluion Adolf Fick (1855) proposed: d J α d d d J (mole/m s) flu (m /s) diffusion coefficien and (mole/m 3 ) concenraion of ions, aoms

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Linear Response Theory: The connecion beween QFT and experimens 3.1. Basic conceps and ideas Q: How do we measure he conduciviy of a meal? A: we firs inroduce a weak elecric field E, and

More information

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles Diebold, Chaper 7 Francis X. Diebold, Elemens of Forecasing, 4h Ediion (Mason, Ohio: Cengage Learning, 006). Chaper 7. Characerizing Cycles Afer compleing his reading you should be able o: Define covariance

More information

KINEMATICS IN ONE DIMENSION

KINEMATICS IN ONE DIMENSION KINEMATICS IN ONE DIMENSION PREVIEW Kinemaics is he sudy of how hings move how far (disance and displacemen), how fas (speed and velociy), and how fas ha how fas changes (acceleraion). We say ha an objec

More information

More on ODEs by Laplace Transforms October 30, 2017

More on ODEs by Laplace Transforms October 30, 2017 More on OE b Laplace Tranfor Ocober, 7 More on Ordinar ifferenial Equaion wih Laplace Tranfor Larr areo Mechanical Engineering 5 Seinar in Engineering nali Ocober, 7 Ouline Review la cla efiniion of Laplace

More information

Two Coupled Oscillators / Normal Modes

Two Coupled Oscillators / Normal Modes Lecure 3 Phys 3750 Two Coupled Oscillaors / Normal Modes Overview and Moivaion: Today we ake a small, bu significan, sep owards wave moion. We will no ye observe waves, bu his sep is imporan in is own

More information

Module 3: The Damped Oscillator-II Lecture 3: The Damped Oscillator-II

Module 3: The Damped Oscillator-II Lecture 3: The Damped Oscillator-II Module 3: The Damped Oscillaor-II Lecure 3: The Damped Oscillaor-II 3. Over-damped Oscillaions. This refers o he siuaion where β > ω (3.) The wo roos are and α = β + α 2 = β β 2 ω 2 = (3.2) β 2 ω 2 = 2

More information

!!"#"$%&#'()!"#&'(*%)+,&',-)./0)1-*23)

!!#$%&#'()!#&'(*%)+,&',-)./0)1-*23) "#"$%&#'()"#&'(*%)+,&',-)./)1-*) #$%&'()*+,&',-.%,/)*+,-&1*#$)()5*6$+$%*,7&*-'-&1*(,-&*6&,7.$%$+*&%'(*8$&',-,%'-&1*(,-&*6&,79*(&,%: ;..,*&1$&$.$%&'()*1$$.,'&',-9*(&,%)?%*,('&5

More information

STATE-SPACE MODELLING. A mass balance across the tank gives:

STATE-SPACE MODELLING. A mass balance across the tank gives: B. Lennox and N.F. Thornhill, 9, Sae Space Modelling, IChemE Process Managemen and Conrol Subjec Group Newsleer STE-SPACE MODELLING Inroducion: Over he pas decade or so here has been an ever increasing

More information

18 Extensions of Maximum Flow

18 Extensions of Maximum Flow Who are you?" aid Lunkwill, riing angrily from hi ea. Wha do you wan?" I am Majikhie!" announced he older one. And I demand ha I am Vroomfondel!" houed he younger one. Majikhie urned on Vroomfondel. I

More information

Network Flows: Introduction & Maximum Flow

Network Flows: Introduction & Maximum Flow CSC 373 - lgorihm Deign, nalyi, and Complexiy Summer 2016 Lalla Mouaadid Nework Flow: Inroducion & Maximum Flow We now urn our aenion o anoher powerful algorihmic echnique: Local Search. In a local earch

More information

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities:

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities: Mah 4 Eam Review Problems Problem. Calculae he 3rd Taylor polynomial for arcsin a =. Soluion. Le f() = arcsin. For his problem, we use he formula f() + f () + f ()! + f () 3! for he 3rd Taylor polynomial

More information

The Residual Graph. 11 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm

The Residual Graph. 11 Augmenting Path Algorithms. Augmenting Path Algorithm. Augmenting Path Algorithm Augmening Pah Algorihm Greedy-algorihm: ar wih f (e) = everywhere find an - pah wih f (e) < c(e) on every edge augmen flow along he pah repea a long a poible The Reidual Graph From he graph G = (V, E,

More information

20. Applications of the Genetic-Drift Model

20. Applications of the Genetic-Drift Model 0. Applicaions of he Geneic-Drif Model 1) Deermining he probabiliy of forming any paricular combinaion of genoypes in he nex generaion: Example: If he parenal allele frequencies are p 0 = 0.35 and q 0

More information

KEY. Math 334 Midterm I Fall 2008 sections 001 and 003 Instructor: Scott Glasgow

KEY. Math 334 Midterm I Fall 2008 sections 001 and 003 Instructor: Scott Glasgow 1 KEY Mah 4 Miderm I Fall 8 secions 1 and Insrucor: Sco Glasgow Please do NOT wrie on his eam. No credi will be given for such work. Raher wrie in a blue book, or on our own paper, preferabl engineering

More information

MATH 31B: MIDTERM 2 REVIEW. x 2 e x2 2x dx = 1. ue u du 2. x 2 e x2 e x2] + C 2. dx = x ln(x) 2 2. ln x dx = x ln x x + C. 2, or dx = 2u du.

MATH 31B: MIDTERM 2 REVIEW. x 2 e x2 2x dx = 1. ue u du 2. x 2 e x2 e x2] + C 2. dx = x ln(x) 2 2. ln x dx = x ln x x + C. 2, or dx = 2u du. MATH 3B: MIDTERM REVIEW JOE HUGHES. Inegraion by Pars. Evaluae 3 e. Soluion: Firs make he subsiuion u =. Then =, hence 3 e = e = ue u Now inegrae by pars o ge ue u = ue u e u + C and subsiue he definiion

More information

Linear Motion, Speed & Velocity

Linear Motion, Speed & Velocity Add Iporan Linear Moion, Speed & Velociy Page: 136 Linear Moion, Speed & Velociy NGSS Sandard: N/A MA Curriculu Fraework (2006): 1.1, 1.2 AP Phyic 1 Learning Objecive: 3.A.1.1, 3.A.1.3 Knowledge/Underanding

More information

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes Represening Periodic Funcions by Fourier Series 3. Inroducion In his Secion we show how a periodic funcion can be expressed as a series of sines and cosines. We begin by obaining some sandard inegrals

More information

Angular Motion, Speed and Velocity

Angular Motion, Speed and Velocity Add Imporan Angular Moion, Speed and Velociy Page: 163 Noe/Cue Here Angular Moion, Speed and Velociy NGSS Sandard: N/A MA Curriculum Framework (006): 1.1, 1. AP Phyic 1 Learning Objecive: 3.A.1.1, 3.A.1.3

More information

Solutions to Assignment 1

Solutions to Assignment 1 MA 2326 Differenial Equaions Insrucor: Peronela Radu Friday, February 8, 203 Soluions o Assignmen. Find he general soluions of he following ODEs: (a) 2 x = an x Soluion: I is a separable equaion as we

More information

Mathcad Lecture #8 In-class Worksheet Curve Fitting and Interpolation

Mathcad Lecture #8 In-class Worksheet Curve Fitting and Interpolation Mahcad Lecure #8 In-class Workshee Curve Fiing and Inerpolaion A he end of his lecure, you will be able o: explain he difference beween curve fiing and inerpolaion decide wheher curve fiing or inerpolaion

More information

u(x) = e x 2 y + 2 ) Integrate and solve for x (1 + x)y + y = cos x Answer: Divide both sides by 1 + x and solve for y. y = x y + cos x

u(x) = e x 2 y + 2 ) Integrate and solve for x (1 + x)y + y = cos x Answer: Divide both sides by 1 + x and solve for y. y = x y + cos x . 1 Mah 211 Homework #3 February 2, 2001 2.4.3. y + (2/x)y = (cos x)/x 2 Answer: Compare y + (2/x) y = (cos x)/x 2 wih y = a(x)x + f(x)and noe ha a(x) = 2/x. Consequenly, an inegraing facor is found wih

More information

INDEX. Transient analysis 1 Initial Conditions 1

INDEX. Transient analysis 1 Initial Conditions 1 INDEX Secion Page Transien analysis 1 Iniial Condiions 1 Please inform me of your opinion of he relaive emphasis of he review maerial by simply making commens on his page and sending i o me a: Frank Mera

More information

Laplace transfom: t-translation rule , Haynes Miller and Jeremy Orloff

Laplace transfom: t-translation rule , Haynes Miller and Jeremy Orloff Laplace ransfom: -ranslaion rule 8.03, Haynes Miller and Jeremy Orloff Inroducory example Consider he sysem ẋ + 3x = f(, where f is he inpu and x he response. We know is uni impulse response is 0 for

More information

Wall. x(t) f(t) x(t = 0) = x 0, t=0. which describes the motion of the mass in absence of any external forcing.

Wall. x(t) f(t) x(t = 0) = x 0, t=0. which describes the motion of the mass in absence of any external forcing. MECHANICS APPLICATIONS OF SECOND-ORDER ODES 7 Mechanics applicaions of second-order ODEs Second-order linear ODEs wih consan coefficiens arise in many physical applicaions. One physical sysems whose behaviour

More information

The fundamental mass balance equation is ( 1 ) where: I = inputs P = production O = outputs L = losses A = accumulation

The fundamental mass balance equation is ( 1 ) where: I = inputs P = production O = outputs L = losses A = accumulation Hea (iffusion) Equaion erivaion of iffusion Equaion The fundamenal mass balance equaion is I P O L A ( 1 ) where: I inpus P producion O oupus L losses A accumulaion Assume ha no chemical is produced or

More information

Chapter 8 The Complete Response of RL and RC Circuits

Chapter 8 The Complete Response of RL and RC Circuits Chaper 8 The Complee Response of RL and RC Circuis Seoul Naional Universiy Deparmen of Elecrical and Compuer Engineering Wha is Firs Order Circuis? Circuis ha conain only one inducor or only one capacior

More information

Section 7.4 Modeling Changing Amplitude and Midline

Section 7.4 Modeling Changing Amplitude and Midline 488 Chaper 7 Secion 7.4 Modeling Changing Ampliude and Midline While sinusoidal funcions can model a variey of behaviors, i is ofen necessary o combine sinusoidal funcions wih linear and exponenial curves

More information

Notes on Kalman Filtering

Notes on Kalman Filtering Noes on Kalman Filering Brian Borchers and Rick Aser November 7, Inroducion Daa Assimilaion is he problem of merging model predicions wih acual measuremens of a sysem o produce an opimal esimae of he curren

More information

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution Physics 7b: Saisical Mechanics Fokker-Planck Equaion The Langevin equaion approach o he evoluion of he velociy disribuion for he Brownian paricle migh leave you uncomforable. A more formal reamen of his

More information

RC, RL and RLC circuits

RC, RL and RLC circuits Name Dae Time o Complee h m Parner Course/ Secion / Grade RC, RL and RLC circuis Inroducion In his experimen we will invesigae he behavior of circuis conaining combinaions of resisors, capaciors, and inducors.

More information

Introduction to Congestion Games

Introduction to Congestion Games Algorihmic Game Theory, Summer 2017 Inroducion o Congeion Game Lecure 1 (5 page) Inrucor: Thoma Keelheim In hi lecure, we ge o know congeion game, which will be our running example for many concep in game

More information