CHAPTER 1: PEREVIEW. 1. Nature of Process Control Problem CLIENT HARDWARE. LEVEL-6 Planning. LEVEL-5 Scheduling. LEVEL-4 Real-Time Optimization
|
|
- Sara Perry
- 6 years ago
- Views:
Transcription
1 CHPER : PEREVIEW. Nature o Proe Cotrol Proble CLIEN IMERME CIVIY HRDWRE Upper level aageet Week-Mot LEVEL-6 Plaig Corporate oplex etwork Plat ager Da-Week LEVEL-5 Sedulig Platwide Ioratio te Proe Egieer Hour-Da LEVEL-4 Real-ie Optiizatio Proe otrol oputer Proe Egieer Miute-Hour LEVEL-3 Dai Optiizatio Proe otrol oputer Cotrol Egieer Plat operator Seod LEVEL- Regulator Cotrol DCS or PLC Itruet Egieer < Seod LEVEL- Itruetatio Seor ad atuator Raw Material Proe Plat Produt
2 Regulator Cotrol Objetive: Eure ae operatio Collet eauret Ipleet otrol atio Cotrol atio Itruetatio Objetive: Regulate proe Eure ae tartup utdow Iterae to opertaor Cotrol atio Proe Plat Meaureet ield itruet Real-tie Optiizatio Objetive: Deterie optiu tead ate operatig oditio Deterie loal ot ator Update proe odel arget value or upper level otroller Meaureet Dai Optiizatio upper level otrol Objetive: Deterie bet operatioal otrait Maitai output at target value wile avoidig otrait violatio Set poit or low level otroller Regulator Cotrol Low Level otrol Meaureet
3 . Model-Baed Cotroller optiizer Diturbae arget et poit Model-baed otroller optiizer Maipulated variable Proe Model Meaureet Diturbae/ odel error etiatio Cotrolled output e ajor blok aoiated wit Model-baed otroller:. e proe odel. Diturbae /odel error etiatio 3. Cotroller or optiizer e ajor drawbak o odel-baed otroller i te aura o te odel. e proe odel i ued at alot all laer o te ieraral truture: Regulator otrol: Model are ued to tue PID otroller eed-orward ieretial otroller Dai optiizatio: Model are ued to predit te beavior o te proe i te uture opute otrol atio. Real-tie tead tate optiizatio: Model are ued to opute tead tate operatig oditio. Liear odel are alo ued or plaig ad edulig.
4 3. pe o Model-Baed Cotroller odel -baed otrol iteral odel otroller odel preditive otroller Liear otiuou odel Laplae-doai Noliear otiuou odel ODE Liear direte odel IR Noliear otiuou odel ODE 4. pe o Model PROCESS MODELS Stead tate odel Dai odel udaetal irt priiple odel Data -Drive epirial odel Noliear Dieretial Equatio Liearizatio Liear Model Noliear epirial artiial eural etwork Redued order odel Direte tie z-doai Cotiuou tie tate pae raer utio Laplae-doai
5 4.. ie Doai odel tate Spae Noliear tate pae: u x g w u x dx Liear tate pae: t Cx Dw t t Bu t x dx 4. Laplae Doai odel Cx Dw Bu x x w G u G Dw I C Bu I C w p b b b b a a a a G L L 4.3 Buildig State Spae odel ro irt priiple Exaple: Mixig ak L Ma Balae: d d
6 Eerg Balae: Cp Cp Cp Cp d d d d d e tate pae equatio: d d Deie: x ; ; u Liearize: x u B w D
7 C [ ] dx x t Bu t Cx t 3.4 Idetiig a irt-order proe wit dead tie G θ ke uta ut ial tead tate axiu lope t t iitial tead tate t t θ t θ tie. t
8 5. Propertie o raer utio G N D b a z z L z p p L p Pole: i te root o te deoiator o te traer utio i.e. te root o te arateriti poloial. It diretl deterie: e tabilit o te te poitive pole e potetial o periodi traiet iagiar pole Zero: i te root o te uerator o te traer utio. It deterie a ivere repoe poitive zero. Caualit: pial te i aual we te order o te deoiator i greater ta te uerator ad we te traer utio goe to a te te i ee tritl proper. I te traer utio otai e θ or te order o uerator i iger ta te deoiator te te te i o-aual or ot realizable beaue te urret value o te te deped o te uture value o te variable. Stead tate gai: i te tead tate value o te traer utio i evaluated b ettig i te table traer utio. 5. Eet o pole ad zero e pole ad zero o a traer utio aet te dai o a proe. Coider a iular traer utio: G K ζ e pole i.e. te root o te arateriti equatio are: 3 ζ j ζ 4 ζ j ζ
9 e pole a be repreeted i te oplex plae a ollow: iagiar axi ζ ζ Real axi ζ Coplex pole idiate te repoe will otai ie ad oie ode i.e. will exibit oillatio. Negative pole will reult i a table deaig repoe. Poitive pole idiate tat te repoe will ave utable ode. Iagiar Real Negative real root ie Iagiar Real Poitive real root ie
10 Iagiar Real ie Coplex root wit egative real Iagiar Real ie Coplex root wit poitive real proe wit RHP zero i alled o-iiu-pae proe wit odd uber o RHP zero a a ivere repoe.
Transfer Function Analysis
Trasfer Fuctio Aalysis Free & Forced Resposes Trasfer Fuctio Syste Stability ME375 Trasfer Fuctios - Free & Forced Resposes Ex: Let s s look at a stable first order syste: τ y + y = Ku Take LT of the I/O
More informationSchool of Mechanical Engineering Purdue University. ME375 Transfer Functions - 1
Trasfer Fuctio Aalysis Free & Forced Resposes Trasfer Fuctio Syste Stability ME375 Trasfer Fuctios - 1 Free & Forced Resposes Ex: Let s look at a stable first order syste: y y Ku Take LT of the I/O odel
More informationTHE CONCEPT OF THE ROOT LOCUS. H(s) THE CONCEPT OF THE ROOT LOCUS
So far i the tudie of cotrol yte the role of the characteritic equatio polyoial i deteriig the behavior of the yte ha bee highlighted. The root of that polyoial are the pole of the cotrol yte, ad their
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 informationObserver Design with Reduced Measurement Information
Observer Desig with Redued Measuremet Iformatio I pratie all the states aot be measured so that SVF aot be used Istead oly a redued set of measuremets give by y = x + Du p is available where y( R We assume
More information(s)h(s) = K( s + 8 ) = 5 and one finite zero is located at z 1
ROOT LOCUS TECHNIQUE 93 should be desiged differetly to eet differet specificatios depedig o its area of applicatio. We have observed i Sectio 6.4 of Chapter 6, how the variatio of a sigle paraeter like
More informationIntroduction to Control Systems
Itroductio to Cotrol Sytem CLASSIFICATION OF MATHEMATICAL MODELS Icreaig Eae of Aalyi Static Icreaig Realim Dyamic Determiitic Stochatic Lumped Parameter Ditributed Parameter Liear Noliear Cotat Coefficiet
More informationCONTROL SYSTEMS. Chapter 7 : Bode Plot. 40dB/dec 1.0. db/dec so resultant slope will be 20 db/dec and this is due to the factor s
CONTROL SYSTEMS Chapter 7 : Bode Plot GATE Objective & Numerical Type Solutio Quetio 6 [Practice Book] [GATE EE 999 IIT-Bombay : 5 Mark] The aymptotic Bode plot of the miimum phae ope-loop trafer fuctio
More informationECE 422 Power System Operations & Planning 6 Small Signal Stability. Spring 2015 Instructor: Kai Sun
ECE 4 Power Sytem Operatio & Plaig 6 Small Sigal Stability Sprig 15 Itructor: Kai Su 1 Referece Saadat Chapter 11.4 EPRI Tutorial Chapter 8 Power Ocillatio Kudur Chapter 1 Power Ocillatio The power ytem
More informationOn the Asymptotic Behavior of Solutions for a Class of Second Order Nonlinear Difference Equations
IOSR Joral o Matemati IOSR-JM e-issn: 78-578 p-issn: 39-765X. Volme Ie 6 Ver. IV Nov. - De.6 PP 6- www.iorjoral.or O te Aymptoti Beavior o Soltio or a Cla o Seod Order Noliear Dieree Eqatio V. Sadaivam
More informationAnalysis of Analytical and Numerical Methods of Epidemic Models
Iteratioal Joural of Egieerig Reearc ad Geeral Sciece Volue, Iue, Noveber-Deceber, 05 ISSN 09-70 Aalyi of Aalytical ad Nuerical Metod of Epideic Model Pooa Kuari Aitat Profeor, Departet of Mateatic Magad
More informationELIMINATION OF FINITE EIGENVALUES OF STRONGLY SINGULAR SYSTEMS BY FEEDBACKS IN LINEAR SYSTEMS
73 M>D Tadeuz azore Waraw Uiverity of Tehology, Faulty of Eletrial Egieerig Ititute of Cotrol ad Idutrial Eletroi EIMINATION OF FINITE EIENVAUES OF STONY SINUA SYSTEMS BY FEEDBACS IN INEA SYSTEMS Tadeuz
More informationExact Linearization and Fuzzy Logic Applied to the Control of a Magnetic Levitation System
WCCI IEEE World Cogress o Coputatioal Itelligee July, 8-3, - CCIB, Bareloa, Spai UZZ-IEEE Exat Liearizatio ad uzzy Logi Applied to the Cotrol o a Mageti Levitatio Syste Luiz H. S. orres, Carlos A. V. Vasoelos,
More informationNUMERICAL DIFFERENTIAL 1
NUMERICAL DIFFERENTIAL Ruge-Kutta Metods Ruge-Kutta metods are ver popular ecause o teir good eiciec; ad are used i most computer programs or dieretial equatios. Te are sigle-step metods as te Euler metods.
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 informationLecture 11. Solution of Nonlinear Equations - III
Eiciecy o a ethod Lecture Solutio o Noliear Equatios - III The eiciecy ide o a iterative ethod is deied by / E r r: rate o covergece o the ethod : total uber o uctios ad derivative evaluatios at each step
More information8.6 Order-Recursive LS s[n]
8.6 Order-Recurive LS [] Motivate ti idea wit Curve Fittig Give data: 0,,,..., - [0], [],..., [-] Wat to fit a polyomial to data.., but wic oe i te rigt model?! Cotat! Quadratic! Liear! Cubic, Etc. ry
More informationState space systems analysis
State pace ytem aalyi Repreetatio of a ytem i tate-pace (tate-pace model of a ytem To itroduce the tate pace formalim let u tart with a eample i which the ytem i dicuio i a imple electrical circuit with
More information1. Linearization of a nonlinear system given in the form of a system of ordinary differential equations
. Liearizatio of a oliear system give i the form of a system of ordiary differetial equatios We ow show how to determie a liear model which approximates the behavior of a time-ivariat oliear system i a
More informationComputational Methods CMSC/AMSC/MAPL 460. Quadrature: Integration
Computatioal Metods CMSC/AMSC/MAPL 6 Quadrature: Itegratio Ramai Duraiswami, Dept. o Computer Siee Some material adapted rom te olie slides o Eri Sadt ad Diae O Leary Numerial Itegratio Idea is to do itegral
More informationChapter 4: Angle Modulation
57 Chapter 4: Agle Modulatio 4.1 Itrodutio to Agle Modulatio This hapter desribes frequey odulatio (FM) ad phase odulatio (PM), whih are both fors of agle odulatio. Agle odulatio has several advatages
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 informationDiscrete population models
Discrete populatio odels D. Gurarie Ratioal: cclic (seasoal) tiig of reproductio ad developet, schroizatio Topics:. Reewal odels (Fiboacci). Discrete logistic odels (Verhulst vs. Ricker); cobwebs; equilibria,
More informationStudy on Solution of Non-homogeneous Linear Equation based on Ordinary Differential Equation Driving Jing Zhang
Iteratioal Coeree o Automatio Meaial Cotrol ad Computatioal Egieerig AMCCE 05 Stud o Solutio o No-omogeeous Liear Equatio based o Ordiar Dieretial Equatio Drivig Jig Zag Meaial ad Eletrial Egieerig College
More informationState Space Representation
Optimal Cotrol, Guidace ad Estimatio Lecture 2 Overview of SS Approach ad Matrix heory Prof. Radhakat Padhi Dept. of Aerospace Egieerig Idia Istitute of Sciece - Bagalore State Space Represetatio Prof.
More information(8) 1f = f. can be viewed as a real vector space where addition is defined by ( a1+ bi
Geeral Liear Spaes (Vetor Spaes) ad Solutios o ODEs Deiitio: A vetor spae V is a set, with additio ad salig o elemet deied or all elemets o the set, that is losed uder additio ad salig, otais a zero elemet
More informationBio-Systems Modeling and Control
Bio-Sytem Modelig ad otrol Leture Ezyme ooperatio i Ezyme Dr. Zvi Roth FAU Ezyme with Multiple Bidig Site May ezyme have more tha oe bidig ite for ubtrate moleule. Example: Hemoglobi Hb, the oxygearryig
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 informationCurrent Programmed Control (i.e. Peak Current-Mode Control) Lecture slides part 2 More Accurate Models
Curret Progred Cotrol.e. Pek Curret-Mode Cotrol eture lde prt More Aurte Model ECEN 5807 Drg Mkovć Sple Frt-Order CPM Model: Sury Aupto: CPM otroller operte delly, Ueful reult t low frequee, well uted
More informationELEC 372 LECTURE NOTES, WEEK 1 Dr. Amir G. Aghdam Concordia University
EEC 37 ECTURE NOTES, WEEK 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 informationZ-buffering, Interpolation and More W-buffering Doug Rogers NVIDIA Corporation
-buerig, Iterpolatio a More -buerig Doug Roger NVIDIA Corporatio roger@viia.om Itroutio Covertig ooriate rom moel pae to ree pae i a erie o operatio that mut be learly uertoo a implemete or viibility problem
More informationAnalog Filter Design. Part. 3: Time Continuous Filter Implementation. P. Bruschi - Analog Filter Design 1
Aalog Filter Deig Part. 3: Time otiuou Filter Implemetatio P. ruchi - Aalog Filter Deig Deig approache Paive (R) ladder filter acade of iquadratic (iquad) ad iliear cell State Variable Filter Simulatio
More informationME 410 MECHANICAL ENGINEERING SYSTEMS LABORATORY REGRESSION ANALYSIS
ME 40 MECHANICAL ENGINEERING REGRESSION ANALYSIS Regreio problem deal with the relatiohip betwee the frequec ditributio of oe (depedet) variable ad aother (idepedet) variable() which i (are) held fied
More informationEECE 301 Signals & Systems Prof. Mark Fowler
EECE 30 Sigal & Sytem Prof. Mark Fowler Note Set #8 C-T Sytem: Laplace Traform Solvig Differetial Equatio Readig Aigmet: Sectio 6.4 of Kame ad Heck / Coure Flow Diagram The arrow here how coceptual flow
More informationThe Binomial Multi- Section Transformer
4/4/26 The Bioial Multisectio Matchig Trasforer /2 The Bioial Multi- Sectio Trasforer Recall that a ulti-sectio atchig etwork ca be described usig the theory of sall reflectios as: where: ( ω ) = + e +
More informationDigital Signal Processing, Fall 2010
Digital Sigal Proeig, Fall 2 Leture 3: Samplig ad reotrutio, traform aalyi of LTI ytem tem Zheg-ua Ta Departmet of Eletroi Sytem Aalborg Uiverity, Demar t@e.aau.d Coure at a glae MM Direte-time igal ad
More informationLecture 8. Nonlinear Device Stamping
PRINCIPLES OF CIRCUIT SIMULATION Lecture 8. Noliear Device Stampig Guoyog Shi, PhD shiguoyog@ic.sjtu.edu.c School of Microelectroics Shaghai Jiao Tog Uiversity Fall -- Slide Outlie Solvig a oliear circuit
More informationRAYLEIGH'S METHOD Revision D
RAYGH'S METHOD Revisio D B To Irvie Eail: toirvie@aol.co Noveber 5, Itroductio Daic sstes ca be characterized i ters of oe or ore atural frequecies. The atural frequec is the frequec at which the sste
More informationStatistics and Data Analysis in MATLAB Kendrick Kay, February 28, Lecture 4: Model fitting
Statistics ad Data Aalysis i MATLAB Kedrick Kay, kedrick.kay@wustl.edu February 28, 2014 Lecture 4: Model fittig 1. The basics - Suppose that we have a set of data ad suppose that we have selected the
More information5.6 Binomial Multi-section Matching Transformer
4/14/21 5_6 Bioial Multisectio Matchig Trasforers 1/1 5.6 Bioial Multi-sectio Matchig Trasforer Readig Assiget: pp. 246-25 Oe way to axiize badwidth is to costruct a ultisectio Γ f that is axially flat.
More informationOn The Stability and Accuracy of Some Runge-Kutta Methods of Solving Second Order Ordinary Differential Equations
Iteratioal Joural o Computatioal Egieerig Resear Vol Issue 7 O Te Stabilit ad Aura o Some Ruge-Kutta Metods o Solvig Seod Order Ordiar Dieretial Euatios S.O. Salawu R.A. Kareem ad O.T. Arowolo Departmet
More information13.4 Scalar Kalman Filter
13.4 Scalar Kalma Filter Data Model o derive the Kalma filter we eed the data model: a 1 + u < State quatio > + w < Obervatio quatio > Aumptio 1. u i zero mea Gauia, White, u } σ. w i zero mea Gauia, White,
More informationBernoulli Polynomials Talks given at LSBU, October and November 2015 Tony Forbes
Beroulli Polyoials Tals give at LSBU, October ad Noveber 5 Toy Forbes Beroulli Polyoials The Beroulli polyoials B (x) are defied by B (x), Thus B (x) B (x) ad B (x) x, B (x) x x + 6, B (x) dx,. () B 3
More informationFormula List for College Algebra Sullivan 10 th ed. DO NOT WRITE ON THIS COPY.
Forula List for College Algera Sulliva 10 th ed. DO NOT WRITE ON THIS COPY. Itercepts: Lear how to fid the x ad y itercepts. Syetry: Lear how test for syetry with respect to the x-axis, y-axis ad origi.
More informationCDS 101: Lecture 5.1 Controllability and State Space Feedback
CDS, Lecture 5. CDS : Lecture 5. Cotrollability ad State Space Feedback Richard M. Murray 8 October Goals: Deie cotrollability o a cotrol system Give tests or cotrollability o liear systems ad apply to
More informationMath 213b (Spring 2005) Yum-Tong Siu 1. Explicit Formula for Logarithmic Derivative of Riemann Zeta Function
Math 3b Sprig 005 Yum-og Siu Expliit Formula for Logarithmi Derivative of Riema Zeta Futio he expliit formula for the logarithmi derivative of the Riema zeta futio i the appliatio to it of the Perro formula
More informationSystem Control. Lesson #19a. BME 333 Biomedical Signals and Systems - J.Schesser
Sytem Cotrol Leo #9a 76 Sytem Cotrol Baic roblem Say you have a ytem which you ca ot alter but it repoe i ot optimal Example Motor cotrol for exokeleto Robotic cotrol roblem that ca occur Utable Traiet
More information5.6 Binomial Multi-section Matching Transformer
4/14/2010 5_6 Bioial Multisectio Matchig Trasforers 1/1 5.6 Bioial Multi-sectio Matchig Trasforer Readig Assiget: pp. 246-250 Oe way to axiize badwidth is to costruct a ultisectio Γ f that is axially flat.
More informationME203 Section 4.1 Forced Vibration Response of Linear System Nov 4, 2002 (1) kx c x& m mg
ME3 Setio 4.1 Fored Vibratio Respose of Liear Syste Nov 4, Whe a liear ehaial syste is exited by a exteral fore, its respose will deped o the for of the exitatio fore F(t) ad the aout of dapig whih is
More informationSolutions 3.2-Page 215
Solutios.-Page Problem Fid the geeral solutios i powers of of the differetial equatios. State the reurree relatios ad the guarateed radius of overgee i eah ase. ) Substitutig,, ad ito the differetial equatio
More informationLecture 13. Graphical representation of the frequency response. Luca Ferrarini - Basic Automatic Control 1
Lecture 3 Graphical represetatio of the frequecy respose Luca Ferrarii - Basic Automatic Cotrol Graphical represetatio of the frequecy respose Polar plot G Bode plot ( j), G Im 3 Re of the magitude G (
More information2D DSP Basics: Systems Stability, 2D Sampling
- Digital Iage Processig ad Copressio D DSP Basics: Systes Stability D Saplig Stability ty Syste is stable if a bouded iput always results i a bouded output BIBO For LSI syste a sufficiet coditio for stability:
More informationd y f f dy Numerical Solution of Ordinary Differential Equations Consider the 1 st order ordinary differential equation (ODE) . dx
umerical Solutio o Ordiar Dieretial Equatios Cosider te st order ordiar dieretial equatio ODE d. d Te iitial coditio ca be tae as. Te we could use a Talor series about ad obtai te complete solutio or......!!!
More informationSpecial Notes: Filter Design Methods
Page Special Note: Filter Deig Method Spectral Poer epoe For j j j exp What i j Magitude (ut be the ae!): N M Q i i p z K j Phae: N M Q i i a p a z a j ta ta ta N M Q i i a p a z a j ta ta ta herefore
More informationECE 422/522 Power System Operations & Planning/Power Systems Analysis II : 6 - Small Signal Stability
ECE 4/5 Power System Operatios & Plaig/Power Systems Aalysis II : 6 - Small Sigal Stability Sprig 014 Istructor: Kai Su 1 Refereces Kudur s Chapter 1 Saadat s Chapter 11.4 EPRI Tutorial s Chapter 8 Power
More informationCombined Flexure and Axial Load
Cobied Flexure ad Axial Load Iteractio Diagra Partiall grouted bearig wall Bearig Wall: Sleder Wall Deig Procedure Stregth Serviceabilit Delectio Moet Magiicatio Exaple Pilater Bearig ad Cocetrated Load
More informationResearch on Fuzzy Clustering Image Segmentation Algorithm based on GA and Gray Histogram Baoyi Wang1, a, Long Kang1, b, Shaomin Zhang1, c
3rd Iteratioal Coferee o Mahiery, Materials ad Iforatio Tehology Appliatios (ICMMITA 05 Researh o Fuzzy Clusterig Iage Segetatio Algorith based o GA ad Gray Histogra Baoyi Wag, a, Log Kag, b, Shaoi Zhag,
More informationRelated Rates section 3.9
Related Rate ection 3.9 Iportant Note: In olving the related rate proble, the rate of change of a quantity i given and the rate of change of another quantity i aked for. You need to find a relationhip
More informationS Mobile Communications Services and Systems
S-7.60 Mobile ommuniation Serie and Sytem Tutorial, Noember 9, 004. One a pyiit obert Wood did not top i ar beind te red trai ligt. He exue imel by uing oppler eet. Beaue o oppler it te red ligt ad turned
More informationStudy on Coal Consumption Curve Fitting of the Thermal Power Based on Genetic Algorithm
Joural of ad Eergy Egieerig, 05, 3, 43-437 Published Olie April 05 i SciRes. http://www.scirp.org/joural/jpee http://dx.doi.org/0.436/jpee.05.34058 Study o Coal Cosumptio Curve Fittig of the Thermal Based
More informationELG3175 Introduction to Communication Systems. Angle Modulation Continued
ELG3175 Iroduio o Couiaio Sye gle Modulaio Coiued Le araériique de igaux odulé e agle PM Sigal M Sigal Iaaeou phae i Iaaeou requey Maxiu phae deviaio D ax Maxiu requey deviaio D ax Power p p p x où 0 d
More informationLast time: Completed solution to the optimum linear filter in real-time operation
6.3 tochatic Etimatio ad Cotrol, Fall 4 ecture at time: Completed olutio to the oimum liear filter i real-time operatio emi-free cofiguratio: t D( p) F( p) i( p) dte dp e π F( ) F( ) ( ) F( p) ( p) 4444443
More informationIntroduction to Optimization, DIKU Monday 19 November David Pisinger. Duality, motivation
Itroductio to Optiizatio, DIKU 007-08 Moday 9 Noveber David Pisiger Lecture, Duality ad sesitivity aalysis Duality, shadow prices, sesitivity aalysis, post-optial aalysis, copleetary slackess, KKT optiality
More informationPARTIAL DIFFERENTIAL EQUATIONS SEPARATION OF VARIABLES
Diola Bagayoko (0 PARTAL DFFERENTAL EQUATONS SEPARATON OF ARABLES. troductio As discussed i previous lectures, partial differetial equatios arise whe the depedet variale, i.e., the fuctio, varies with
More informationHomework 6: Forced Vibrations Due Friday April 6, 2018
EN40: Dyais ad Vibratios Hoework 6: Fored Vibratios Due Friday April 6, 018 Shool of Egieerig Brow Uiversity 1. The vibratio isolatio syste show i the figure has 0kg, k 19.8 kn / 1.59 kns / If the base
More informationAnswer: 1(A); 2(C); 3(A); 4(D); 5(B); 6(A); 7(C); 8(C); 9(A); 10(A); 11(A); 12(C); 13(C)
Aswer: (A); (C); 3(A); 4(D); 5(B); 6(A); 7(C); 8(C); 9(A); 0(A); (A); (C); 3(C). A two loop positio cotrol system is show below R(s) Y(s) + + s(s +) - - s The gai of the Tacho-geerator iflueces maily the
More informationA PROBABILITY PROBLEM
A PROBABILITY PROBLEM A big superarket chai has the followig policy: For every Euros you sped per buy, you ear oe poit (suppose, e.g., that = 3; i this case, if you sped 8.45 Euros, you get two poits,
More informationLecture 7 Testing Nonlinear Inequality Restrictions 1
Eco 75 Lecture 7 Testig Noliear Iequality Restrictios I Lecture 6, we discussed te testig problems were te ull ypotesis is de ed by oliear equality restrictios: H : ( ) = versus H : ( ) 6= : () We sowed
More informationMultistep Runge-Kutta Methods for solving DAEs
Multitep Ruge-Kutta Method for olvig DAE Heru Suhartato Faculty of Coputer Sciece, Uiverita Idoeia Kapu UI, Depok 6424, Idoeia Phoe: +62-2-786 349 E-ail: heru@c.ui.ac.id Kevi Burrage Advaced Coputatioal
More informationAnother face of DIRECT
Aother ae o DIEC Lakhdar Chiter Departmet o Mathematis, Seti Uiversity, Seti 19000, Algeria E-mail address: hiterl@yahoo.r Abstrat It is show that, otrary to a laim o [D. E. Fikel, C.. Kelley, Additive
More informationThe Binomial Multi-Section Transformer
4/15/2010 The Bioial Multisectio Matchig Trasforer preset.doc 1/24 The Bioial Multi-Sectio Trasforer Recall that a ulti-sectio atchig etwork ca be described usig the theory of sall reflectios as: where:
More informationChap.4 Ray Theory. The Ray theory equations. Plane wave of homogeneous medium
The Ra theor equatio Plae wave of homogeeou medium Chap.4 Ra Theor A plae wave ha the dititive propert that it tregth ad diretio of propagatio do ot var a it propagate through a homogeeou medium p vae
More informationAdaptive control design for a Mimo chemical reactor
Automatio, Cotrol ad Itelliget Sytem 013; 1(3): 64-70 Publihed olie July 10, 013 (http://www.ciecepublihiggroup.com/j/aci) doi: 10.11648/j.aci.0130103.15 Adaptive cotrol deig for a Mimo chemical reactor
More informationCONTROL ENGINEERING LABORATORY
Uiverity of Techology Departmet of Electrical Egieerig Cotrol Egieerig Lab. CONTROL ENGINEERING LABORATORY By Dr. Abdul. Rh. Humed M.Sc. Quay Salim Tawfeeq M.Sc. Nihad Mohammed Amee M.Sc. Waleed H. Habeeb
More informationLab 1 - Wavelet-based biomedical signal processing. Lab Task 1.1 (need 1 week) What & Why is wavelet?
Lab - avelet-based bioedical sigal processig Lab Task. eed week hat & hy is wavelet? Learig goal: avelet tutorial; Cotet: Use Haar or other basic other wavelets to study the Tie-Frequecy doai eatures o
More information_10_EE394J_2_Spring12_Inertia_Calculation.doc. Procedure for Estimating Grid Inertia H from Frequency Droop Measurements
Procedure or Etiating Grid Inertia ro Frequency Droop Meaureent While the exion or inertia and requency droop are well known, it i prudent to rederive the here. Treating all the grid generator a one large
More informationHigh-Speed Serial Interface Circuits and Systems. Lect. 4 Phase-Locked Loop (PLL) Type 1 (Chap. 8 in Razavi)
High-Speed Serial Iterface Circuit ad Sytem Lect. 4 Phae-Locked Loop (PLL) Type 1 (Chap. 8 i Razavi) PLL Phae lockig loop A (egative-feedback) cotrol ytem that geerate a output igal whoe phae (ad frequecy)
More informationChapter 4 : Laplace Transform
4. Itroductio Laplace trasform is a alterative to solve the differetial equatio by the complex frequecy domai ( s = σ + jω), istead of the usual time domai. The DE ca be easily trasformed ito a algebraic
More informationSOLUTION TO CHAPTER 4 EXERCISES: SLURRY TRANSPORT
SOLUTION TO CHAPTER 4 EXERCISES: SLURRY TRANSPORT EXERCISE 4.1 Sales o a osate slurry ixture are aalyzed i a lab. Te ollowig data describe te relatiosi betwee te sear stress ad te sear rate: 1 Sear Rate,γ&
More informationLebesgue Constant Minimizing Bivariate Barycentric Rational Interpolation
Appl. Math. If. Sci. 8, No. 1, 187-192 (2014) 187 Applied Matheatics & Iforatio Scieces A Iteratioal Joural http://dx.doi.org/10.12785/ais/080123 Lebesgue Costat Miiizig Bivariate Barycetric Ratioal Iterpolatio
More information2-D Groundwater Flow Through A Confined Aquifer
-D Groudwater Flow Troug A Coied Aquier Gordo Wybur ad Ajoy Vase Pooa College May 5 t, 006 Abstract We attepted to odel te groudwater low i a -D coied aquier uder dieret coditios usig te iite dierece etod.
More informationLC Oscillations. di Q. Kirchoff s loop rule /27/2018 1
L Oscillatios Kirchoff s loop rule I di Q VL V L dt ++++ - - - - L 3/27/28 , r Q.. 2 4 6 x 6.28 I. f( x) f( x).. r.. 2 4 6 x 6.28 di dt f( x) Q Q cos( t) I Q si( t) di dt Q cos( t) 2 o x, r.. V. x f( )
More informationDigital Signal Processing. Homework 2 Solution. Due Monday 4 October Following the method on page 38, the difference equation
Digital Sigal Proessig Homework Solutio Due Moda 4 Otober 00. Problem.4 Followig the method o page, the differee equatio [] (/4[-] + (/[-] x[-] has oeffiiets a0, a -/4, a /, ad b. For these oeffiiets A(z
More information11. Ideal Gas Mixture
. Ideal Ga xture. Geeral oderato ad xture of Ideal Gae For a geeral xture of N opoet, ea a pure ubtae [kg ] te a for ea opoet. [kol ] te uber of ole for ea opoet. e al a ( ) [kg ] N e al uber of ole (
More informationDeveloping Transfer Functions from Heat & Material Balances
Colorado Sool of Mine CHEN43 Stirred ank Heater Develoing ranfer untion from Heat & Material Balane Examle ranfer untion Stirred ank Heater,,, A,,,,, We will develo te tranfer funtion for a tirred tank
More informationEE415/515 Fundamentals of Semiconductor Devices Fall 2012
090 EE4555 Fudaetals of Seicoductor evices Fall 0 ecture : MOSFE hapter 0.3, 0.4 090 J. E. Morris Reider: Here is what the MOSFE looks like 090 N-chael MOSFEs: Ehaceet & epletio odes 090 J. E. Morris 3
More informationEE 380. Linear Control Systems. Lecture 10
EE 380 Linear Control Systems Lecture 10 Professor Jeffrey Schiano Department of Electrical Engineering Lecture 10. 1 Lecture 10 Topics Stability Definitions Methods for Determining Stability Lecture 10.
More informationEE 508 Lecture 6. Dead Networks Scaling, Normalization and Transformations
EE 508 Lecture 6 Dead Network Scalig, Normalizatio ad Traformatio Filter Cocept ad Termiology 2-d order polyomial characterizatio Biquadratic Factorizatio Op Amp Modelig Stability ad Itability Roll-off
More information1. Introduction. 2. Numerical Methods
America Joural o Computatioal ad Applied Matematics, (5: 9- DOI:.59/j.ajcam.5. A Stud o Numerical Solutios o Secod Order Iitial Value Problems (IVP or Ordiar Dieretial Equatios wit Fourt Order ad Butcer
More information( ) ( s ) Answers to Practice Test Questions 4 Electrons, Orbitals and Quantum Numbers. Student Number:
Anwer to Practice Tet Quetion 4 Electron, Orbital Quantu Nuber. Heienberg uncertaint principle tate tat te preciion of our knowledge about a particle poition it oentu are inverel related. If we ave ore
More informationPhysics 6C. De Broglie Wavelength Uncertainty Principle. Prepared by Vince Zaccone For Campus Learning Assistance Services at UCSB
Pyic 6C De Broglie Wavelengt Uncertainty Principle De Broglie Wavelengt Bot ligt and atter ave bot particle and wavelike propertie. We can calculate te wavelengt of eiter wit te ae forula: p v For large
More informationFuzzy n-normed Space and Fuzzy n-inner Product Space
Global Joural o Pure ad Applied Matheatics. ISSN 0973-768 Volue 3, Nuber 9 (07), pp. 4795-48 Research Idia Publicatios http://www.ripublicatio.co Fuzzy -Nored Space ad Fuzzy -Ier Product Space Mashadi
More informationu t u 0 ( 7) Intuitively, the maximum principles can be explained by the following observation. Recall
Oct. Heat Equatio M aximum priciple I thi lecture we will dicu the maximum priciple ad uiquee of olutio for the heat equatio.. Maximum priciple. The heat equatio alo ejoy maximum priciple a the Laplace
More informationCHAPTER 13 FILTERS AND TUNED AMPLIFIERS
HAPTE FILTES AND TUNED AMPLIFIES hapter Outline. Filter Traniion, Type and Specification. The Filter Tranfer Function. Butterworth and hebyhev Filter. Firt Order and Second Order Filter Function.5 The
More informationMetasurface Cloak Performance Near-by Multiple Line Sources and PEC Cylindrical Objects
Metaurfae Cloa Performae Near-by Multiple Lie Soure ad PEC Cylidrial Objet S. Arlaagić, W. Y. amilto, S. Pehro, ad A. B. Yaovlev 2 Departmet of Eletrial Egieerig Eletromageti Sytem Tehial Uiverity of Demar
More informationNeural Networks Trained with the EEM Algorithm: Tuning the Smoothing Parameter
eural etworks Trained wit te EEM Algorit: Tuning te Sooting Paraeter JORGE M. SATOS,2, JOAQUIM MARQUES DE SÁ AD LUÍS A. ALEXADRE 3 Intituto de Engenaria Bioédica, Porto, Portugal 2 Instituto Superior de
More informationNURTURE COURSE TARGET : JEE (MAIN) Test Type : ALL INDIA OPEN TEST TEST DATE : ANSWER KEY HINT SHEET. 1. Ans.
Test Type : LL INDI OPEN TEST Paper Code : 0000CT005 00 CLSSROOM CONTCT PROGRMME (cadeic Sessio : 05-06) NURTURE COURSE TRGET : JEE (MIN) 07 TEST DTE : - 0-06 NSWER KEY HINT SHEET Corporate Office : CREER
More informationPhysics 30 Lesson 3 Impulse and Change in Momentum
Phyic 30 Leon 3 Ipule and Change in Moentu I. Ipule and change in oentu According to Newton nd Law of Motion (Phyic Principle 1 on the Data Sheet), to change the otion (i.e. oentu) of an object an unbalanced
More informationSTABILITY OF THE ACTIVE VIBRATION CONTROL OF CANTILEVER BEAMS
Iteratioal Coferece o Vibratio Problem September 9-,, Liboa, Portugal STBILITY OF THE CTIVE VIBRTIO COTROL OF CTILEVER BEMS J. Tůma, P. Šuráe, M. Mahdal VSB Techical Uierity of Otraa Czech Republic Outlie.
More informationVasyl Moisyshyn*, Bogdan Borysevych*, Oleg Vytyaz*, Yuriy Gavryliv*
AGH DRILLING, OIL, GAS Vol. 3 No. 3 204 http://dx.doi.org/0.7494/drill.204.3.3.43 Vasyl Moisyshy*, Bogda Borysevych*, Oleg Vytyaz*, Yuriy Gavryliv* DEVELOPMENT OF THE MATHEMATICAL MODELS OF THE INTEGRAL
More information