The following Content. Objective. Introduction to Process Control. What have we talked in MM1-MM5? MM5? Software: Control Tutorials for Matlab
|
|
- Dominic Cobb
- 5 years ago
- Views:
Transcription
1 Objecive Iroucio o Proce Corol Zheyu Yag Aalborg Uiveriy Ebjerg Semeer 5 of Fall 4, h://caueauck/~yag/cour e/4fall/roce4hml /8/4 Proce Corol To uera a gra he fuameal kowlege abou feeback corol heory: claical corol heory Moer corol heory To be able o aalyze, yheize a imulae corol yem uig iffere meho To be able o uera iurial corol yem /8/4 Proce Corol Wha have we alke i MM-MM5? MM5? Hiory of feeback corol Block iagram for yem moelig Time-omai ecificaio Traie erformace, eay-ae error, yem ye PID coroller Frequecy reoe aalyi a eig Boe lo, gai a hae margi, bawih, Deig of yamic comeaio Lea, lag comeaor BIBO Sabiliy (Rouh crierio) Nyqui abiliy /8/4 Proce Corol 3 /8/4 Proce Corol 4 The followig Coe Par oe: Ehace he Claical corol heory MM6: Moellig Iue a Corol Secificaio MM7: PID Corol a Examle MM8: Frequecy Reoe Meho - I MM9: Frequecy Reoe Meho - II MM:Roo locu meho Par wo: Moer corol heory MM: Iroucio o ae ace meho MM: Corol Deig for Full Sae Feeback MM3: Corol eig uig eimaor MM4: Iroucio of Referece Iu MM5: Iegral Corol a LQR corol /8/4 Proce Corol 5 Sofware: Corol Tuorial for Malab h://wwwegiumicheu/grou/ cm/homeexhml /8/4 Proce Corol 6
2 MM6 Moelig Iue & Corol Secificaio ) Iroucio ) Moelig iue 3) Secificaio 6 Iroucio The fuameal goal of CE i o fi echically, eviromeally, a ecoomically feaible way of acig o yem o corol heir ouu o eire level of erformace i he face of uceraiy of he roce a i he reece of ucorolable exeral iurbace acig o he roce - Graham C Goowi /8/4 Proce Corol 7 /8/4 Proce Corol 8 6 Wa fly-ball goveror Hiorical Perio of Corol Theory The iurial revoluio (86) The Seco Worl War (94-945) The uh io ace (6, 7) Ecoomic globalizaio (8) Shareholer-value hikig /8/4 Proce Corol 9 /8/4 Proce Corol 6 CE Alicaio Domai /8/4 Proce Corol 63 Baic Corol Syem Referece - iu Feeforwar comeaor Feeback comeaor Alicaio: Regulaor yem Servo or oiio yem Trackig yem acuaor Meaure oie eor iurbace Pla Targe: Cloe-loo abiliy Diurbace aeuaio Goo comma reoe Robue /8/4 Proce Corol
3 MM6 Moelig Iue & Corol Secificaio ) Iroucio ) Moelig iue LTI moelmalab Block iagrammalab 3 Digial corol yem 3) Secificaio /8/4 Proce Corol 3 6 Moelig Iue Moel Aribue mahemaical Coiuou-ime Iu-ouu Dyamic SISO Liear Parameric Time-ivaria Coraig aribue No-mahemaical Dicree-ime Sae ace aic MIMO oliear Noarameric Time-varyig /8/4 Proce Corol 4 6 Moelig Iue Moellig 6 Examle: Trai Syem Theoreical (hyical law) Whie-box ieificaio Srucure eermiaio Time-omai Recurive Direc Exerimeal Black-box ieificaio Parameer eimaio Frequecy-omai No-recurive Iirec Moelig Tuorial Problem: coier a oy rai coiig of a egie a a car Aumig ha he rai oly ravel i oe irecio, we wa o aly corol o he rai o ha i ha a mooh ar-u a o, alog wih a coa-ee rie The ma of he egie a he car will be rereee by M a M, reecively The wo are hel ogeher by a rig, which ha he iffe coefficie of k F reree he force alie by he egie, a he Greek leer, mu, reree he coefficie of rollig fricio Semeer /8/4 6: Moellig a Proce imulaio Corol 5 /8/4 Proce Corol 6 6 Examle: Trai Syem (co ) 6 Examle: Trai Syem (co ) M kg M 5 kg k N/ec F N u ec/m g 98 m/^ M; M5; k; F; u; g98; um[m M*u*g ]; e[m*m *M*M*u*g M*kM*M*u*u*g*gM*k M*k*u*gM*k*u*g]; yf(um,e) Liview(y) /8/4 Proce Corol 7 /8/4 Proce Corol 8 3
4 6 Coiuou C LTI Syem Moel Differeial equaio y ζ y y u Trafer fucio Num-e form m Y ( ) b b G ( ) U ( ) a a Zero-ole form m X FX Y HX GU JU m ( z ) Y ( ) i i G ( ) e g, G ( ) U ( ) ( )( ) ( i ) i, ζ ± ζ /8/4 Proce Corol 9 L b L b m, e g, G ( ) ζ 63 Moel Exreio i Malab Sae-ace form y(f,g,h,j) Num-e rafer fucio form yf(um,e) Zero-ole rafer fucio form yzk(z,p,) Mole exchage y(f(um,e)) or [F,G,H,J] (f(um,e)) [um,e] f(a,b,c,d,iu) [A,B,C,D]f(um,e) /8/4 Proce Corol 64 Coecio Block Diagram Referece iu - Forwar comeaor Feeback comeaor acuaor eor iurbace Pla 65 Coecio i Malab - I Serie coecio of wo LTI y erie(y,y) y erie(y,y,ouu,iu) w r - D() A(S) P() y y F() S() /8/4 Proce Corol /8/4 Proce Corol 65 Coecio i Malab - II 65 Coecio i Malab - III Parrallel coecio of wo LTI y arallel(y,y) y arallel(y,y,i,i,ou,ou) y y Feeback coecio of wo LTI y feeback(y,y) y feeback(y,y,ig) y feeback(y,y,feei,feeou,ig) /8/4 Proce Corol 3 /8/4 Proce Corol 4 4
5 r() 66 Digial Corol Syem - D/A a D (z) A(S) P() hol clock F (z) A/D a amler S() /8/4 Proce Corol 5 w 66 Zero-Orer Hol Equivale H h ( z) ( z D( ) ) Ζ{ } Malab imlemeaio y c(y,t,meho) 'zoh : Zero-orer hol The corol iu are aume iecewie coa over he amlig erio T 'foh : Triagle aroximaio (moifie fir-orer hol) The corol iu are aume iecewie liear over he amlig erio T 'ui : Biliear (Tui) aroximaio 'rewar : Tui aroximaio wih frequecy rewarig 'mache : Mache ole-zero meho /8/4 Proce Corol 6 Demom file ca be owloa from coure web Pla: G()/(), lea comeaor: D()7()/() NumG[]; DeG[ ]; NumD[7 4]; DeD[ ]; ygf(numg,deg); ydf(numd,ded); ycfeeback(yg*yd,); T5; ydlf([/t],[ /T]); yclfeeback(yg*yd*ydl,); Sublo(,,); imule(yc); hol; imule(ycl,'r'); Sublo(,,); zma(yc); gri; hol;zma(ycl,'r'); hol off figure boe(yc,'b',ycl,'r'); hol off yzohc(yc,t,'zoh'); ytusinc(yc,t,'ui'); yzpc(yc,t,'mache'); boe(yc,'b',yzoh,'r',ytusin,'g',yzp,'b') /8/4 Proce Corol 7 MM6 Moelig Iue & Corol Secificaio ) Iroucio ) Moelig iue 3) Corol Secificaio /8/4 Proce Corol 8 63 Corol Secificaio 3 Syem Sabiliy 63 Cloe-loo abiliy Defiiio: BIBO abiliy 63 Goo comma reoe 33 Diurbace aeuaio 34 Robue /8/4 Proce Corol 9 Deermiaio meho: o Imule reoe fucio/equece o Roo of characeriic equaio o Rouh abiliy crierio o Gai a hae margi o Nyqui abiliy crierio /8/4 Proce Corol 3 5
6 Sabiliy Imule Reoe BIBO abiliy (FC 3-4) The coiuou yem wih imue reoe h() i BIBO able if a oly if h() i aboluely iegrallable The icree yem wih imue reoe h[] i BIBO able if a oly if h[] i aboluely ummable Sabiliy Characeriic Roo Aymoic ieral abiliy Occur whe all ole (roo of he chraceriic equaio) of he coiuou yem are ricly i he LHP of he -lae Occur whe all ole (roo of he chraceriic equaio) of he icree yem are ricly iie he ui circle of he z-lae (Malab: roo(e)) /8/4 Proce Corol 3 /8/4 Proce Corol 3 Sabiliy Rouh Crierio Rouh abiliy crierio (FC 5-) For a able yem all he eleme i he fir colum of he Rouh array mu be oiive Examle (ee exbook) 3 Corol Secificaio 3 Cloe-loo abiliy 3 Goo comma reoe 33 Diurbace aeuaio 34 Robue /8/4 Proce Corol 33 /8/4 Proce Corol Syem Performace Syem ye: Coiuou corol yem Digial corol yem Aalyi omai: Time omai ecificaio Frequecy ecificaio Differe erio: Dyamic raie reoe Seay-ae reoe /8/4 Proce Corol 35 Coiuou Syem Time Domai (I) Dyamic reoe (raie reoe) Imule reoe: imule(y) H ( ) ζ ζ : amig raio Se reoe: e(y) EXAMPLE: y: Sy: h ( ) e : auralfre quecy i( )( ) σ ζ, ζ um[]; um[ ]; e[ ]; e[ 3]; imule(f(um,e),'r',f(um,e),'b') e(f(um,e),'r',f(um,e),'b') /8/4 Proce Corol 36 σ 6
7 Coiuou Syem Time Domai (II) goo raie reoe (See FC 6-3) Rie ime r Selig ime Overhoo M 8 r 4 6 ζ 4 6 σ πζ / ζ Peak ime M e, ζ π, ζ H( ) ζ ζ : amigraio : auralfrequecy /8/4 Proce Corol 37 Coiuou Syem Time Domai (III) goo eay-ae reoe (See FC -6) Lalace raform Fial value heorem Seay-ae error a yem ye (ye, ye I, ye II, ) uiy feeback y T ( ) e lim k lim G o ( ) e v lim G o ( ) e v Velociy coa Acceleraio coa a lim G o ( ) e a /8/4 Proce Corol 38 Poiio-error coa F ( ) f ( ) e lim f ( ) lim F ( ) Seay-ae error a yem ye Coiuou Syem Frequecy Domai Frequecy reoe (See FC ) u ( ) U y ( ) U A G ( ) θ < G ( ) i( ) A i( θ ) j j {Re[ G ( j )]} a Im[ G ( j )] Re[ G ( j )] {Im[ G ( j )]} /8/4 Proce Corol 39 /8/4 Proce Corol 4 Coiuou Syem Frequecy Domai Bawih a reoa eak Bawih:meaure he ee of reoe ( 3B frequecy) Boe lo echique (See FC 35) /8/4 Proce Corol 4 Coiuou Syem Frequecy Domai Boe lo boe(y); boe(y,w) boe(y,'plosyle',,yn,'plosylen') Comue gai a hae margi a aociae croover frequecie [Gm,Pm,Wcg,Wc] margi(y) margi(y) EXAMPLE: um[ ]; e[ 3 4] margi(um,e) /8/4 Proce Corol 4 7
8 Effec of Pole a Zero SGRID geerae a gri over a exiig coiuou -lae roo locu or ole-zero ma Lie of coa amig raio (zea) a aural frequecy (W) are raw H ( ) ζ : amig raio ζ h ( ) : auralfre quecy e ζ σ i( )( ) σ ζ, ζ zma(sy); /8/4 Proce Corol 43 ZGRID geerae a gri over a exiig icree z-lae roo locu or ole-zero ma Lie of coa amig facor (zea) a aural frequecy (W) are raw i wihi he ui Z-lae circle /8/4 Proce Corol 44 Effec of Aiioal Pole A aiioal ole i he LHP will icreae he riig ime igificaly if he exra ole i wihi a facor of 4 of he real ar of he comlex ole Examle: um[36] e[ 6 36] yf(um,e) roo(e) yy*f(,[ ]) yy*f(65,[ 65]) y3y*f(5,[ 5]) e(y,'b',y,'g',y,'r', y3,'--') lege('orig', 'y', 'y', 'y3') figure, boe(y,'b',y,'g',y,'r', y3,'--') lege('orig', 'y', 'y', 'y3') Dowloa aiioalolezerom /8/4 Proce Corol 45 Effec of Aiioal Zero A aiioal zero i he LHP will icreae he overhoo if he zero i wihi a facor of 4 of he real ar of he comlex ole A aiioal zero i he RHP will ere he overhoo (a may caue he e reoe o ar ou i he wrog irecio omiimum-hae yem Examle : um[36]; e[ 6 36]; yf(um,e); yy*f([ 3],3) yy*f([ 9],9) y3y*f([ 5],5) e(y,'b',y,'g',y,'r', y3,'--') figure, boe(y,'b',y,'g',y,'r', y3,'--') Dowloa aiioalolezerom Examle : um[36]; e[ 6 36]; yf(um,e); umz[-36 36] ez[ 6 36]; yzf(umz,ez) e(y,'b',yz,'r') /8/4 Proce Corol 46 Exercie Oe See he iribue aer /8/4 Proce Corol 47 8
Stability. Outline Stability Sab Stability of Digital Systems. Stability for Continuous-time Systems. system is its stability:
Oulie Sabiliy Sab Sabiliy of Digial Syem Ieral Sabiliy Exeral Sabiliy Example Roo Locu v ime Repoe Fir Orer Seco Orer Sabiliy e Jury e Rouh Crierio Example Sabiliy A very impora propery of a yamic yem
More informationLecture 25 Outline: LTI Systems: Causality, Stability, Feedback
Lecure 5 Oulie: LTI Sye: Caualiy, Sabiliy, Feebac oucee: Reaig: 6: Lalace Trafor. 37-49.5, 53-63.5, 73; 7: 7: Feebac. -4.5, 8-7. W 8 oe, ue oay. Free -ay eeio W 9 will be oe oay, ue e Friay (o lae W) Fial
More informationAnalysis of Dynamic Systems
ME 43 Syem Dyamic & Corol Chaper 8: Time Domai Aalyi of Dyamic Syem Syem Chaper 8 Time-Domai Aalyi of Dyamic Syem 8. INTRODUCTION Pole a Zero of a Trafer Fucio A. Bazoue Pole: The pole of a rafer fucio
More informationTIME RESPONSE Introduction
TIME RESPONSE Iroducio Time repoe of a corol yem i a udy o how he oupu variable chage whe a ypical e ipu igal i give o he yem. The commoly e ipu igal are hoe of ep fucio, impule fucio, ramp fucio ad iuoidal
More informationMODERN CONTROL SYSTEMS
MODERN CONTROL SYSTEMS Lecure 9, Sae Space Repreeaio Emam Fahy Deparme of Elecrical ad Corol Egieerig email: emfmz@aa.edu hp://www.aa.edu/cv.php?dip_ui=346&er=6855 Trafer Fucio Limiaio TF = O/P I/P ZIC
More informationState-Space Model. In general, the dynamic equations of a lumped-parameter continuous system may be represented by
Sae-Space Model I geeral, he dyaic equaio of a luped-paraeer coiuou ye ay be repreeed by x & f x, u, y g x, u, ae equaio oupu equaio where f ad g are oliear vecor-valued fucio Uig a liearized echique,
More informationROBUST CONTROL OF HYDRAULIC ACTUATOR USING BACK-STEPPING SLIDING MODE CONTROLLER
P-0 ROBUST CONTRO OF HYDRAUIC ACTUATOR USING BACK-STEPPING SIDING ODE CONTROER Jeogju Choi* Techical Ceer for High Performace alve, Dog-A Uiveriy, Bua, Korea * Correodig auhor (jchoi7@dau.ac.kr ABSTRACT:
More informationDesign 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 informationControl 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 informationTwo Implicit Runge-Kutta Methods for Stochastic Differential Equation
Alied Mahemaic, 0, 3, 03-08 h://dx.doi.org/0.436/am.0.306 Publihed Olie Ocober 0 (h://www.scirp.org/oural/am) wo mlici Ruge-Kua Mehod for Sochaic Differeial quaio Fuwe Lu, Zhiyog Wag * Dearme of Mahemaic,
More informationControl 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 informationM. Rafeeyan. Keywords: MIMO, QFT, non-diagonal, control, uncertain
IUST Ieraioal Joural of Eieeri Sciece, Vol. 9, No.5-, 008, Pae 37-4 QUANTITATIVE NON-IAGONAL REGULATOR ESIGN FOR UNCERTAIN MULTIVARIABLE SYSTEM WITH HAR TIME-OMAIN CONSTRAINTS owloae from ijiepr.iu.ac.ir
More informationChapter 2: Time-Domain Representations of Linear Time-Invariant Systems. Chih-Wei Liu
Caper : Time-Domai Represeaios of Liear Time-Ivaria Sysems Ci-Wei Liu Oulie Iroucio Te Covoluio Sum Covoluio Sum Evaluaio Proceure Te Covoluio Iegral Covoluio Iegral Evaluaio Proceure Iercoecios of LTI
More informationK3 p K2 p Kp 0 p 2 p 3 p
Mah 80-00 Mo Ar 0 Chaer 9 Fourier Series ad alicaios o differeial equaios (ad arial differeial equaios) 9.-9. Fourier series defiiio ad covergece. The idea of Fourier series is relaed o he liear algebra
More informationu(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 informationME 3210 Mechatronics II Laboratory Lab 6: Second-Order Dynamic Response
Iroucio ME 30 Mecharoics II Laboraory Lab 6: Seco-Orer Dyamic Respose Seco orer iffereial equaios approimae he yamic respose of may sysems. I his lab you will moel a alumium bar as a seco orer Mass-Sprig-Damper
More informationTime-Scale Modification Basic approaches
AN IMPROVED HYBRID TIME-FREQUENCY ALORITHM FOR TIME-SCALE MODIFICATION OF SPEECH/AUDIO SINALS Criia NERESCU, Amelia CIOBANU, Draoş BURILEANU, Dumiru STANOMIR Uiveriaea Poliehica Bucureşi Time-Scale Moificaio
More informationNotes 03 largely plagiarized by %khc
1 1 Discree-Time Covoluio Noes 03 largely plagiarized by %khc Le s begi our discussio of covoluio i discree-ime, sice life is somewha easier i ha domai. We sar wih a sigal x[] ha will be he ipu io our
More informationIdeal 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 informationSHOCK AND VIBRATION RESPONSE SPECTRA COURSE Unit 21 Base Excitation Shock: Classical Pulse
SHOCK AND VIBRAION RESPONSE SPECRA COURSE Ui 1 Base Exciaio Shock: Classical Pulse By om Irvie Email: omirvie@aol.com Iroucio Cosier a srucure subjece o a base exciaio shock pulse. Base exciaio is also
More informationPrecise Position Control of Pneumatic Servo System Considered Dynamic Characteristics of Servo Valve
Precie Poitio Corol of Peumatic Servo Sytem Coidered Dyamic Characteritic of Takahi MIYAJIMA*, Hidekui IIDA*, Tohiori FUJITA**, eji AWASHIMA*** ad Tohiharu AGAWA*** * Graduated School Stude, Tokyo Iitute
More informationSection 8 Convolution and Deconvolution
APPLICATIONS IN SIGNAL PROCESSING Secio 8 Covoluio ad Decovoluio This docume illusraes several echiques for carryig ou covoluio ad decovoluio i Mahcad. There are several operaors available for hese fucios:
More informationMeromorphic Functions Sharing Three Values *
Alied Maheaic 11 718-74 doi:1436/a11695 Pulihed Olie Jue 11 (h://wwwscirporg/joural/a) Meroorhic Fucio Sharig Three Value * Arac Chagju Li Liei Wag School o Maheaical Sciece Ocea Uiveriy o Chia Qigdao
More informationME 321 Kinematics and Dynamics of Machines S. Lambert Winter 2002
ME 31 Kiemaic ad Dyamic o Machie S. Lamber Wier 6.. Forced Vibraio wih Dampig Coider ow he cae o orced vibraio wih dampig. Recall ha he goverig diereial equaio i: m && c& k F() ad ha we will aume ha he
More informationSampling. AD Conversion (Additional Material) Sampling: Band limited signal. Sampling. Sampling function (sampling comb) III(x) Shah.
AD Coversio (Addiioal Maerial Samplig Samplig Properies of real ADCs wo Sep Flash ADC Pipelie ADC Iegraig ADCs: Sigle Slope, Dual Slope DA Coverer Samplig fucio (samplig comb III(x Shah III III ( x = δ
More information6.302 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 informationELEC 372 LECTURE NOTES, WEEK 4 Dr. Amir G. Aghdam Concordia University
ELEC 37 LECTURE NOTES, WEE 4 Dr Amir G Aghdam Cocordia Uiverity Part of thee ote are adapted from the material i the followig referece: Moder Cotrol Sytem by Richard C Dorf ad Robert H Bihop, Pretice Hall
More informationThe Performance of Feedback Control Systems
The Performace of Feedbac Cotrol Sytem Objective:. Secify the meaure of erformace time-domai the firt te i the deig roce Percet overhoot / Settlig time T / Time to rie / Steady-tate error e. ut igal uch
More information2 f(x) dx = 1, 0. 2f(x 1) dx d) 1 4t t6 t. t 2 dt i)
Mah PracTes Be sure o review Lab (ad all labs) There are los of good quesios o i a) Sae he Mea Value Theorem ad draw a graph ha illusraes b) Name a impora heorem where he Mea Value Theorem was used i he
More informationComparison of Automatically Tuned Cascade Control Systems of Servo-Drives for Numerically Controlled Machine Tools
hp://dx.doi.org/.5755/j.eee...788 ELETRONIA IR ELETROTECHNIA, ISSN 9-5, VOL., NO., Compario of Auomaically Tued Cacade Corol Syem of Servo-Drive for Numerically Corolled Machie Tool S. Madra Iiue of Phyic,
More informationOutline. Classical Control. Lecture 1
Outline Outline Outline 1 Introduction 2 Prerequisites Block diagram for system modeling Modeling Mechanical Electrical Outline Introduction Background Basic Systems Models/Transfers functions 1 Introduction
More informationCalculus BC 2015 Scoring Guidelines
AP Calculus BC 5 Scorig Guidelies 5 The College Board. College Board, Advaced Placeme Program, AP, AP Ceral, ad he acor logo are regisered rademarks of he College Board. AP Ceral is he official olie home
More informationVariational Iteration Method for Solving Differential Equations with Piecewise Constant Arguments
I.J. Egieerig ad Maufacurig, 1,, 36-43 Publihed Olie April 1 i MECS (hp://www.mec-pre.e) DOI: 1.5815/ijem.1..6 Available olie a hp://www.mec-pre.e/ijem Variaioal Ieraio Mehod for Solvig Differeial Equaio
More informationMM4 System s Poles and Feedback Characteristics
MM4 System s Poles ad Feedback Characteristics Readigs: Sectio 3.3 (resose & ole locatios.118-16); Sectio 4.1 (basic roerties of feedback.167-179); Extra readigs (feedback characterisitcs) 9/6/011 Classical
More informationA Design of an Improved Anti-Windup Control Using a PI Controller Based on a Pole Placement Method
KYOHE SAKA e al: A DESGN OF AN MPROVED ANT-WNDUP CONTROL USNG A P CONTROLLER A Deign of an mrove Ani-Winu Conrol Uing a P Conroller Bae on a Pole Placemen Meho Kyohei Saai Grauae School of Science an Technology
More informationHEAT TRANSFER DURING MELTING AND SOLIDIFICATION IN HETEROGENEOUS MATERIALS
HEA RANSFER DURING MELING AND SOLIDIFICAION IN HEEROGENEOUS MAERIALS By Seideh Sayar hei ubmied o he Faculy of he Virgiia Polyechic Iiue ad Sae Uiveriy i arial fulfillme of he requireme for he degree of
More informationLecture 15: Three-tank Mixing and Lead Poisoning
Lecure 15: Three-ak Miig ad Lead Poisoig Eigevalues ad eigevecors will be used o fid he soluio of a sysem for ukow fucios ha saisfy differeial equaios The ukow fucios will be wrie as a 1 colum vecor [
More informationWhen analyzing an object s motion there are two factors to consider when attempting to bring it to rest. 1. The object s mass 2. The object s velocity
SPH4U Momenum LoRuo Momenum i an exenion of Newon nd law. When analyzing an ojec moion here are wo facor o conider when aeming o ring i o re.. The ojec ma. The ojec velociy The greaer an ojec ma, he more
More informationPIECEWISE N TH ORDER ADOMIAN POLYNOMIAL STIFF DIFFERENTIAL EQUATION SOLVER 13
Abrac PIECEWISE N TH ORDER ADOMIAN POLYNOMIAL A piecewie h order Adomia polyomial olver for iiial value differeial equaio capable of olvig highly iff problem i preeed here. Thi powerful echique which employ
More informationLINEAR APPROXIMATION OF THE BASELINE RBC MODEL JANUARY 29, 2013
LINEAR APPROXIMATION OF THE BASELINE RBC MODEL JANUARY 29, 203 Iroducio LINEARIZATION OF THE RBC MODEL For f( x, y, z ) = 0, mulivariable Taylor liear expasio aroud f( x, y, z) f( x, y, z) + f ( x, y,
More informationAn Improved Anti-windup Control Using a PI Controller
05 Third nernaional Conference on Arificial nelligence, Modelling and Simulaion An mroved Ani-windu Conrol Uing a P Conroller Kyohei Saai Graduae School of Science and Technology Meiji univeriy Kanagawa,
More information2007 Spring VLSI Design Mid-term Exam 2:20-4:20pm, 2007/05/11
7 ri VLI esi Mid-erm xam :-4:m, 7/5/11 efieτ R, where R ad deoe he chael resisace ad he ae caaciace of a ui MO ( W / L μm 1μm ), resecively., he chael resisace of a ui PMO, is wo R P imes R. i.e., R R.
More informationLinear System Theory
Naioal Tsig Hua Uiversiy Dearme of Power Mechaical Egieerig Mid-Term Eamiaio 3 November 11.5 Hours Liear Sysem Theory (Secio B o Secio E) [11PME 51] This aer coais eigh quesios You may aswer he quesios
More informationCalculus Limits. Limit of a function.. 1. One-Sided Limits...1. Infinite limits 2. Vertical Asymptotes...3. Calculating Limits Using the Limit Laws.
Limi of a fucio.. Oe-Sided..... Ifiie limis Verical Asympoes... Calculaig Usig he Limi Laws.5 The Squeeze Theorem.6 The Precise Defiiio of a Limi......7 Coiuiy.8 Iermediae Value Theorem..9 Refereces..
More informationLINEAR APPROXIMATION OF THE BASELINE RBC MODEL SEPTEMBER 17, 2013
LINEAR APPROXIMATION OF THE BASELINE RBC MODEL SEPTEMBER 7, 203 Iroducio LINEARIZATION OF THE RBC MODEL For f( xyz,, ) = 0, mulivariable Taylor liear expasio aroud f( xyz,, ) f( xyz,, ) + f( xyz,, )( x
More information5.74 Introductory Quantum Mechanics II
MIT OpeCourseWare hp://ocw.mi.edu 5.74 Iroducory Quaum Mechaics II Sprig 009 For iformaio aou ciig hese maerials or our Terms of Use, visi: hp://ocw.mi.edu/erms. drei Tokmakoff, MIT Deparme of Chemisry,
More informationChapter #3 EEE Subsea Control and Communication Systems
EEE 87 Chter #3 EEE 87 Sube Cotrol d Commuictio Sytem Cloed loo ytem Stedy tte error PID cotrol Other cotroller Chter 3 /3 EEE 87 Itroductio The geerl form for CL ytem: C R ', where ' c ' H or Oe Loo (OL)
More informationarxiv:math/ v1 [math.fa] 1 Feb 1994
arxiv:mah/944v [mah.fa] Feb 994 ON THE EMBEDDING OF -CONCAVE ORLICZ SPACES INTO L Care Schü Abrac. I [K S ] i wa how ha Ave ( i a π(i) ) π i equivale o a Orlicz orm whoe Orlicz fucio i -cocave. Here we
More informationxp (X = x) = P (X = 1) = θ. Hence, the method of moments estimator of θ is
Exercise 7 / page 356 Noe ha X i are ii from Beroulli(θ where 0 θ a Meho of momes: Sice here is oly oe parameer o be esimae we ee oly oe equaio where we equae he rs sample mome wih he rs populaio mome,
More informationElectrical Engineering Department Network Lab.
Par:- Elecrical Egieerig Deparme Nework Lab. Deermiaio of differe parameers of -por eworks ad verificaio of heir ierrelaio ships. Objecive: - To deermie Y, ad ABD parameers of sigle ad cascaded wo Por
More informatione x x s 1 dx ( 1) n n!(n + s) + e s n n n=1 n!n s Γ(s) = lim
Lecure 3 Impora Special FucioMATH-GA 45. Complex Variable The Euler gamma fucio The Euler gamma fucio i ofe ju called he gamma fucio. I i oe of he mo impora ad ubiquiou pecial fucio i mahemaic, wih applicaio
More informationClock Skew and Signal Representation
Clock Skew ad Sigal Represeaio Ch. 7 IBM Power 4 Chip 0/7/004 08 frequecy domai Program Iroducio ad moivaio Sequeial circuis, clock imig, Basic ools for frequecy domai aalysis Fourier series sigal represeaio
More informationA Generalization of Hermite Polynomials
Ieraioal Mahemaical Forum, Vol. 8, 213, o. 15, 71-76 HIKARI Ld, www.m-hikari.com A Geeralizaio of Hermie Polyomials G. M. Habibullah Naioal College of Busiess Admiisraio & Ecoomics Gulberg-III, Lahore,
More informationEEC 483 Computer Organization
EEC 8 Compuer Orgaizaio Chaper. Overview of Pipeliig Chau Yu Laudry Example Laudry Example A, Bria, Cahy, Dave each have oe load of clohe o wah, dry, ad fold Waher ake 0 miue A B C D Dryer ake 0 miue Folder
More informationarxiv: v1 [math.nt] 13 Dec 2010
WZ-PROOFS OF DIVERGENT RAMANUJAN-TYPE SERIES arxiv:0.68v [mah.nt] Dec 00 JESÚS GUILLERA Abrac. We prove ome diverge Ramauja-ype erie for /π /π applyig a Bare-iegral raegy of he WZ-mehod.. Wilf-Zeilberger
More informationVibration damping of the cantilever beam with the use of the parametric excitation
The s Ieraioal Cogress o Soud ad Vibraio 3-7 Jul, 4, Beijig/Chia Vibraio dampig of he cailever beam wih he use of he parameric exciaio Jiří TŮMA, Pavel ŠURÁNE, Miroslav MAHDA VSB Techical Uiversi of Osrava
More informationFourier transform. Continuous-time Fourier transform (CTFT) ω ω
Fourier rasform Coiuous-ime Fourier rasform (CTFT P. Deoe ( he Fourier rasform of he sigal x(. Deermie he followig values, wihou compuig (. a (0 b ( d c ( si d ( d d e iverse Fourier rasform for Re { (
More information6 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 informationExercise: Show that. Remarks: (i) Fc(l) is not continuous at l=c. (ii) In general, we have. yn ¾¾. Solution:
Exercie: Show ha Soluio: y ¾ y ¾¾ L c Þ y ¾¾ p c. ¾ L c Þ F y (l Fc (l I[c,(l "l¹c Þ P( y c
More informationClassical Control. PID controllers and Ziegler-Nichols tuning procedure. Actuator saturation and integrator wind-up.
Claical Crl Tic cvered: Mdelig. ODE. ieariai. alace rafr. Trafer fuci. Blck diagra. Ma Rule. Tie ree ecificai. Effec f er ad le. Sabiliy via Ruh-Hurwi. Feedback: Diurbace reeci, Seiiviy, Seady-ae rackig.
More informationChapter 8: Response of Linear Systems to Random Inputs
Caper 8: epone of Linear yem o anom Inpu 8- Inroucion 8- nalyi in e ime Domain 8- Mean an Variance Value of yem Oupu 8-4 uocorrelaion Funcion of yem Oupu 8-5 Crocorrelaion beeen Inpu an Oupu 8-6 ample
More informationFresnel Dragging Explained
Fresel Draggig Explaied 07/05/008 Decla Traill Decla@espace.e.au The Fresel Draggig Coefficie required o explai he resul of he Fizeau experime ca be easily explaied by usig he priciples of Eergy Field
More informationAutomatic Control Systems
Automatic Cotrol Sytem Lecture-5 Time Domai Aalyi of Orer Sytem Emam Fathy Departmet of Electrical a Cotrol Egieerig email: emfmz@yahoo.com Itrouctio Compare to the implicity of a firt-orer ytem, a eco-orer
More informationFour equations describe the dynamic solution to RBC model. Consumption-leisure efficiency condition. Consumption-investment efficiency condition
LINEAR APPROXIMATION OF THE BASELINE RBC MODEL FEBRUARY, 202 Iroducio For f(, y, z ), mulivariable Taylor liear epasio aroud (, yz, ) f (, y, z) f(, y, z) + f (, y, z)( ) + f (, y, z)( y y) + f (, y, z)(
More informationSolutions Manual 4.1. nonlinear. 4.2 The Fourier Series is: and the fundamental frequency is ω 2π
Soluios Maual. (a) (b) (c) (d) (e) (f) (g) liear oliear liear liear oliear oliear liear. The Fourier Series is: F () 5si( ) ad he fudameal frequecy is ω f ----- H z.3 Sice V rms V ad f 6Hz, he Fourier
More informationSome inequalities for q-polygamma function and ζ q -Riemann zeta functions
Aales Mahemaicae e Iformaicae 37 (1). 95 1 h://ami.ekf.hu Some iequaliies for q-olygamma fucio ad ζ q -Riema zea fucios Valmir Krasiqi a, Toufik Masour b Armed Sh. Shabai a a Dearme of Mahemaics, Uiversiy
More informationRuled surfaces are one of the most important topics of differential geometry. The
CONSTANT ANGLE RULED SURFACES IN EUCLIDEAN SPACES Yuuf YAYLI Ere ZIPLAR Deparme of Mahemaic Faculy of Sciece Uieriy of Aara Tadoğa Aara Turey yayli@cieceaaraedur Deparme of Mahemaic Faculy of Sciece Uieriy
More informationChapter 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 informationModal Analysis of a Tight String
Moal Aalysis of a Tigh Srig Daiel. S. Sus Associae Professor of Mechaical Egieerig a Egieerig Mechaics Presee o ME Moay, Ocober 30, 000 See: hp://web.ms.eu/~sus/me_classes.hml Basic Theory The srig uer
More informationCourse Outline. Problem Identification. Engineering as Design. Amme 3500 : System Dynamics and Control. System Response. Dr. Stefan B.
Course Outlie Amme 35 : System Dyamics a Cotrol System Respose Week Date Cotet Assigmet Notes Mar Itrouctio 8 Mar Frequecy Domai Moellig 3 5 Mar Trasiet Performace a the s-plae 4 Mar Block Diagrams Assig
More informationDesign of feedback control for underdamped systems
FC Coferece o vace i Corol ' Brecia (al), arch 8-, WeB. eig of feeback corol for erampe em. Vračić*. ora Oliveira** *J. Sefa ie, Jamova 9, Ljbljaa Sloveia (Tel: 86--77-7; e-mail: amir.vracic@ij.i). **CES,
More informationANDRONOV-HOPF S BIFURCATION IN A DYNAMIC MODEL OF CELL POPULATION
Mathematical Moelig ANDRONOV-HOPF S BIFURCATION IN A DYNAMIC MODEL OF CELL POPULATION JuG Nekhozhia VA Sobolev Samara Natioal Reearch Uiverity Samara Ruia Abtract The mathematical moel of the ifferetial
More informationEconomics 8723 Macroeconomic Theory Problem Set 3 Sketch of Solutions Professor Sanjay Chugh Spring 2017
Deparme of Ecoomic The Ohio Sae Uiveriy Ecoomic 8723 Macroecoomic Theory Problem Se 3 Skech of Soluio Profeor Sajay Chugh Sprig 27 Taylor Saggered Nomial Price-Seig Model There are wo group of moopoliically-compeiive
More informationConvergence Analysis of Multi-innovation Learning Algorithm Based on PID Neural Network
Sesors & rasducers, Vol., Secial Issue, May 03,. 4-46 Sesors & rasducers 03 by IFSA h://www.sesorsoral.com Coergece Aalysis of Muli-ioaio Learig Algorihm Based o PID Neural Nework Gag Re,, Pile Qi, Mimi
More informationECEN620: Network Theory Broadband Circuit Design Fall 2014
ECE60: etwork Theory Broadbad Circuit Deig Fall 04 Lecture 3: PLL Aalyi Sam Palermo Aalog & Mixed-Sigal Ceter Texa A&M Uiverity Ageda & Readig PLL Overview & Applicatio PLL Liear Model Phae & Frequecy
More informationFour equations describe the dynamic solution to RBC model. Consumption-leisure efficiency condition. Consumption-investment efficiency condition
LINEARIZING AND APPROXIMATING THE RBC MODEL SEPTEMBER 7, 200 For f( x, y, z ), mulivariable Taylor liear expasio aroud ( x, yz, ) f ( x, y, z) f( x, y, z) + f ( x, y, z)( x x) + f ( x, y, z)( y y) + f
More informationECEN620: 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 information11. Adaptive Control in the Presence of Bounded Disturbances Consider MIMO systems in the form,
Lecure 6. Adapive Corol i he Presece of Bouded Disurbaces Cosider MIMO sysems i he form, x Aref xbu x Bref ycmd (.) y Cref x operaig i he presece of a bouded ime-depede disurbace R. All he assumpios ad
More informationFuzzy PID Iterative learning control for a class of Nonlinear Systems with Arbitrary Initial Value Xiaohong Hao and Dongjiang Wang
7h Ieraioal Coferece o Educaio Maageme Compuer ad Medicie (EMCM 216) Fuzzy PID Ieraive learig corol for a class of Noliear Sysems wih Arbirary Iiial Value Xiaohog Hao ad Dogjiag Wag School of Compuer ad
More informationLinear Time Invariant Systems
1 Liear Time Ivaria Sysems Oulie We will show ha he oupu equals he covoluio bewee he ipu ad he ui impulse respose: sysem for a discree-ime, for a coiuous-ime sysdem, y x h y x h 2 Discree Time LTI Sysems
More informationAn interesting result about subset sums. Nitu Kitchloo. Lior Pachter. November 27, Abstract
A ieresig resul abou subse sums Niu Kichloo Lior Pacher November 27, 1993 Absrac We cosider he problem of deermiig he umber of subses B f1; 2; : : :; g such ha P b2b b k mod, where k is a residue class
More informationDETERMINATION OF PARTICULAR SOLUTIONS OF NONHOMOGENEOUS LINEAR DIFFERENTIAL EQUATIONS BY DISCRETE DECONVOLUTION
U.P.B. ci. Bull. eries A Vol. 69 No. 7 IN 3-77 DETERMINATION OF PARTIULAR OLUTION OF NONHOMOGENEOU LINEAR DIFFERENTIAL EQUATION BY DIRETE DEONVOLUTION M. I. ÎRNU e preziă o ouă meoă e eermiare a soluţiilor
More informationDynamic Effects of Feedback Control!
Dynamic Effecs of Feedback Conrol! Rober Sengel! Roboics and Inelligen Sysems MAE 345, Princeon Universiy, 2017 Inner, Middle, and Ouer Feedback Conrol Loops Sep Response of Linear, Time- Invarian (LTI)
More informationComparison between Fourier and Corrected Fourier Series Methods
Malaysia Joural of Mahemaical Scieces 7(): 73-8 (13) MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES Joural homepage: hp://eispem.upm.edu.my/oural Compariso bewee Fourier ad Correced Fourier Series Mehods 1
More information10.3 Autocorrelation Function of Ergodic RP 10.4 Power Spectral Density of Ergodic RP 10.5 Normal RP (Gaussian RP)
ENGG450 Probabiliy ad Saisics for Egieers Iroducio 3 Probabiliy 4 Probabiliy disribuios 5 Probabiliy Desiies Orgaizaio ad descripio of daa 6 Samplig disribuios 7 Ifereces cocerig a mea 8 Comparig wo reames
More information6.003: Signals and Systems
6.003: Sigals ad Sysems Lecure 8 March 2, 2010 6.003: Sigals ad Sysems Mid-erm Examiaio #1 Tomorrow, Wedesday, March 3, 7:30-9:30pm. No reciaios omorrow. Coverage: Represeaios of CT ad DT Sysems Lecures
More informationTheoretical Physics Prof. Ruiz, UNC Asheville, doctorphys on YouTube Chapter Q Notes. Laplace Transforms. Q1. The Laplace Transform.
Theoreical Phyic Prof. Ruiz, UNC Aheville, docorphy o YouTue Chaper Q Noe. Laplace Traform Q1. The Laplace Traform. Pierre-Simo Laplace (1749-187) Courey School of Mhemic ad Siic Uiveriy of S. Adrew, Scolad
More informationControl Systems. Root locus.
Control Sytem Root locu chibum@eoultech.ac.kr Outline Concet of Root Locu Contructing root locu Control Sytem Root Locu Stability and tranient reone i cloely related with the location of ole in -lane How
More informationIntroduction to Hypothesis Testing
Noe for Seember, Iroducio o Hyohei Teig Scieific Mehod. Sae a reearch hyohei or oe a queio.. Gaher daa or evidece (obervaioal or eerimeal) o awer he queio. 3. Summarize daa ad e he hyohei. 4. Draw a cocluio.
More informationThe Eigen Function of Linear Systems
1/25/211 The Eige Fucio of Liear Sysems.doc 1/7 The Eige Fucio of Liear Sysems Recall ha ha we ca express (expad) a ime-limied sigal wih a weighed summaio of basis fucios: v ( ) a ψ ( ) = where v ( ) =
More informationInterpolation and Pulse Shaping
EE345S Real-Time Digial Signal Proceing Lab Spring 2006 Inerpolaion and Pule Shaping Prof. Brian L. Evan Dep. of Elecrical and Compuer Engineering The Univeriy of Texa a Auin Lecure 7 Dicree-o-Coninuou
More informationEXPONENTIAL STABILITY ANALYSIS FOR NEURAL NETWORKS WITH TIME-VARYING DELAY AND LINEAR FRACTIONAL PERTURBATIONS
46 Joural of arie Sciece ad echology Vol. No. pp. 46-53 (4) DOI:.69/JS-3-7-3 EXPONENIL SBILIY NLYSIS FOR NEURL NEWORKS WIH IE-VRYING DELY ND LINER FRCIONL PERURBIONS Chag-Hua Lie ad Ker-Wei Yu Key word:
More informationStability Analysis of Visual Servoing with Sliding-mode Estimation and Neural Compensation
Ieraioal Joural Sabili of Aali Corol of Auomaio Viual Servoig a Sem wih Sliig-moe vol 4 o Eimaio 5 pp 545-558 a Neural Ocober Compeaio 6 545 Sabili Aali of Viual Servoig wih Sliig-moe Eimaio a Neural Compeaio
More informationApplication of Stochastic Lognormal Diffusion Model with Polynomial Exogenous Factors to Energy Consumption in Ghana
Alicaio of Sochaic Logormal Diffuio Model wih Polyomial Eogeou Facor o Eergy Coumio i Ghaa Godfred Kwame Abledu(PhD) School of Alied Sciece Techology, Koforidua Polyechic, PO o 98, Koforidua, Ghaa E-mail
More informationODEs II, Supplement to Lectures 6 & 7: The Jordan Normal Form: Solving Autonomous, Homogeneous Linear Systems. April 2, 2003
ODEs II, Suppleme o Lecures 6 & 7: The Jorda Normal Form: Solvig Auoomous, Homogeeous Liear Sysems April 2, 23 I his oe, we describe he Jorda ormal form of a marix ad use i o solve a geeral homogeeous
More informationFeedforward Control identifiable disturbance measured,
Feeforwar Control So far, mot of the focu of thi coure ha been on feeback control. In certain ituation, the erformance of control ytem can be enhance greatly by the alication of feeforwar control. What
More informationEECE 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 informationA Complex Neural Network Algorithm for Computing the Largest Real Part Eigenvalue and the corresponding Eigenvector of a Real Matrix
4h Ieraioal Coferece o Sesors, Mecharoics ad Auomaio (ICSMA 06) A Complex Neural Newor Algorihm for Compuig he Larges eal Par Eigevalue ad he correspodig Eigevecor of a eal Marix HANG AN, a, XUESONG LIANG,
More informationEECE 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 informationL-functions and Class Numbers
L-fucios ad Class Numbers Sude Number Theory Semiar S. M.-C. 4 Sepember 05 We follow Romyar Sharifi s Noes o Iwasawa Theory, wih some help from Neukirch s Algebraic Number Theory. L-fucios of Dirichle
More information