Static Error EECS240 Spring Settling. Static Error (cont.) Step Response. Dynamic Errors. c 1 FA { V 1. Lecture 13: Settling

Size: px
Start display at page:

Download "Static Error EECS240 Spring Settling. Static Error (cont.) Step Response. Dynamic Errors. c 1 FA { V 1. Lecture 13: Settling"

Transcription

1 Statc Error EES240 Srng 200 Lecture 3: Settlng KL o c FA { T o Elad Alon Det. o EES - o /A v tatc error te wth F + + c EES240 Lecture 3 4 Settlng Why ntereted n ettlng? Ocllocoe: track nut waveor wthout rngng AD (wtched-ca aler): gan a gnal u by a rece aount wthn T ale Φ 2 Statc Error (cont.) o c c FA { FA relatve error Exale: loed loo gan: c -4, F, 4F, F F /6 ( hurt!) Φ Φ Φ2 Φ2 o Error eccaton: <0.% FA > 000 A > 6000 over outut range EES240 Lecture 3 2 EES240 Lecture 3 5 Ste Reone Two tye o ettlng error : Statc Fnte gan, caactor atch Dynac Take te to reach nal value - o /A v Dynac Error Many oble dynac eect that act ettlng error: Fnte bandwdth Feedorward zero Non-donant ole Doublet Slewng Aroxate analy aroach: Decooe each error ource, olate nteracton Add all error together te EES240 Lecture 3 3 EES240 Lecture 3 6

2 Sngle Te ontant Lnear Settlng ae : /z << For dynac ettlng (and or T 0 >> ), can generally gnore r o x o L o c L + ( F ) () t v o, te tec e 23 deal reone Relatve ettlng error: ( t ) ( t t) e ( t ) t ln Eaet nuber to reeber: 2.3 er decade Exale: % ettlng, 4.6n clock cycle: n L,e uually et by noe ue ettlng to deterne requred g EES240 Lecture 3 7 EES240 Lecture 3 0 Te Doan Ste Reone ae 2: /z not neglgble Frequency doan: ote, z te Te doan: v () Relatve ettlng error: t o, te t tec e 23 z deal reone ( t ) ( t t) e ( t ) z t ln + F Le Exale: c 0.25, F, 250F, 250F, L F F 0.67, L,e.33F 0.%: t (no eedorward) 6.9 t (wth eedorward) -ln[e-3/(0.67*0.75)]7.3 EES240 Lecture 3 8 EES240 Lecture 3 Te Doan Ste Reone Frequency doan: nut te: te te, outut te: z z ote, te, te Te doan: (nvere Lalace tranor) t v () t ote, tec e 23 { z deal reone ntal error (eedorward) exonentally decayng error Non-Donant Pole Ignore eed-orward zero or lcty (Jut ncreae nal wng by F / L,e ) H () o c n Le Model or non-donant ole: 0 ( ) Ku unty gan bandwdth o T u ( ) EES240 Lecture 3 9 EES240 Lecture 3 2

3 Ste Reone Non-Donant Pole v. Otu K actually deend on requred accuracy Stll, alway want to ad K<~2 EES240 Lecture 3 3 EES240 Lecture 3 6 Non-Donant Pole (cont.) Doublet Relatve error : - v ( t, K) Aler odel: G () G o z wth β 3dB, 3dB z α α wth bandwdth o T () << loed-loo gan (gnore eedorward zero): o c z n Le 3dB wth ( ) 3dB o Le EES240 Lecture 3 4 EES240 Lecture 3 7 Settlng Te Doublet Analy Settlng te : t 3 ( K) or 0, Otu at K3.3 Ste reone () te ( 3 ) db v t c Ae Be o, te wth B β ( β ) 2 A B EES240 Lecture 3 5 EES240 Lecture 3 8

4 Doublet Exale Slewng Tranconductor I v. : α β Model or (nonlnear) lewng aler Pecewe lnear aroxaton: Slewng wth contant current, ollowed by Lnear ettlng exonental t t lew + t,ln EES240 Lecture 3 9 EES240 Lecture 3 22 Doublet oncluon ae A: 2.e. β Doublet ettle ater than aler Ha no act on overall ettlng te Slewng Analy rcut odel durng lewng: > ae B: 2 Doublet ettle ore lowly than aler Deterne overall ettlng te (unle wthn ettlng accuracy requreent) x I SS L o Ad low doublet! EES240 Lecture 3 20 EES240 Lecture 3 23 Fnal Note on Doublet Slewng Analy (cont.),te x x,te * o tlew tln o,te te EES240 Lecture 3 2 EES240 Lecture 3 24

5 Slewng Analy (cont.) Slewng erod: L xte, te, wth L x x x, te * o F o x Le tlew SR FI SS Lnear ettlng durng nal * o wng at x : Ste durng lnear ettlng: * F t, ln cte, F Lnear ettlng te: ln * EES240 Lecture 3 25

Static Error EECS240 Spring Static Error (cont.) Settling. Step Response. Dynamic Errors V 1. c 1 FA. Lecture 13: Settling

Static Error EECS240 Spring Static Error (cont.) Settling. Step Response. Dynamic Errors V 1. c 1 FA. Lecture 13: Settling Statc Error EES240 Srng 202 Lecture 3: Settlng KL o c FA T o Elad Alon Det. o EES - o /A v tatc error te F c EES240 Lecture 3 4 Settlng Why ntereted n ettlng? Ocllocoe: track nut waveor out rngng AD (wtched-ca

More information

EECS240 Spring Lecture 13: Settling. Lingkai Kong Dept. of EECS

EECS240 Spring Lecture 13: Settling. Lingkai Kong Dept. of EECS EES240 Spring 203 Lecture 3: Settling Lingkai Kong Dept. of EES Settling Why intereted in ettling? Ocillocope: track input waveform without ringing AD (witchedcap amplifier): gain a ignal up by a precie

More information

Design of Recursive Digital Filters IIR

Design of Recursive Digital Filters IIR Degn of Recurve Dgtal Flter IIR The outut from a recurve dgtal flter deend on one or more revou outut value, a well a on nut t nvolve feedbac. A recurve flter ha an nfnte mule reone (IIR). The mulve reone

More information

Lesson 16: Basic Control Modes

Lesson 16: Basic Control Modes 0/8/05 Lesson 6: Basc Control Modes ET 438a Automatc Control Systems Technology lesson6et438a.tx Learnng Objectves Ater ths resentaton you wll be able to: Descrbe the common control modes used n analog

More information

Collisions! Short, Sharp Shocks

Collisions! Short, Sharp Shocks d b n, b d,, -4 Introducng Collsons Quz 9 L9 Mult-artcle Systes 6-8 Scatterng 9- Collson Colcatons L Collsons 5, Derent Reerence Fraes ranslatonal ngular Moentu Quz RE a RE b RE c EP9 RE a; HW: Pr s 3*,,

More information

Circuit Theorems. Introduction

Circuit Theorems. Introduction //5 Crcut eorem ntroducton nearty Property uperpoton ource Tranformaton eenn eorem orton eorem Maxmum Power Tranfer ummary ntroducton To deelop analy technque applcable to lnear crcut. To mplfy crcut analy

More information

Departure Process from a M/M/m/ Queue

Departure Process from a M/M/m/ Queue Dearture rocess fro a M/M// Queue Q - (-) Q Q3 Q4 (-) Knowledge of the nature of the dearture rocess fro a queue would be useful as we can then use t to analyze sle cases of queueng networs as shown. The

More information

How does the momentum before an elastic and an inelastic collision compare to the momentum after the collision?

How does the momentum before an elastic and an inelastic collision compare to the momentum after the collision? Experent 9 Conseraton o Lnear Moentu - Collsons In ths experent you wll be ntroduced to the denton o lnear oentu. You wll learn the derence between an elastc and an nelastc collson. You wll explore how

More information

Chapter 5: Root Locus

Chapter 5: Root Locus Chater 5: Root Locu ey condton for Plottng Root Locu g n G Gven oen-loo tranfer functon G Charactertc equaton n g,,.., n Magntude Condton and Arguent Condton 5-3 Rule for Plottng Root Locu 5.3. Rule Rule

More information

Description of the Force Method Procedure. Indeterminate Analysis Force Method 1. Force Method con t. Force Method con t

Description of the Force Method Procedure. Indeterminate Analysis Force Method 1. Force Method con t. Force Method con t Indeternate Analyss Force Method The force (flexblty) ethod expresses the relatonshps between dsplaceents and forces that exst n a structure. Prary objectve of the force ethod s to deterne the chosen set

More information

Class: Life-Science Subject: Physics

Class: Life-Science Subject: Physics Class: Lfe-Scence Subject: Physcs Frst year (6 pts): Graphc desgn of an energy exchange A partcle (B) of ass =g oves on an nclned plane of an nclned angle α = 3 relatve to the horzontal. We want to study

More information

Discrete Memoryless Channels

Discrete Memoryless Channels Dscrete Meorless Channels Source Channel Snk Aount of Inforaton avalable Source Entro Generall nos, dstorted and a be te varng ow uch nforaton s receved? ow uch s lost? Introduces error and lts the rate

More information

Source-Channel-Sink Some questions

Source-Channel-Sink Some questions Source-Channel-Snk Soe questons Source Channel Snk Aount of Inforaton avalable Source Entro Generall nos and a be te varng Introduces error and lts the rate at whch data can be transferred ow uch nforaton

More information

Thermodynamics Lecture Series

Thermodynamics Lecture Series Therodynac Lecture Sere Dynac Enery Traner Heat, ork and Ma ppled Scence Educaton Reearch Group (SERG) Faculty o ppled Scence Unvert Teknolo MR Pure utance Properte o Pure Sutance- Revew CHPTER eal: drjjlanta@hotal.co

More information

EE C245 ME C218 Introduction to MEMS Design

EE C245 ME C218 Introduction to MEMS Design EE C45 ME C8 Introducton to MEM Desgn Fall 7 Prof. Clark T.C. Nguyen Dept. of Electrcal Engneerng & Computer cences Unersty of Calforna at Berkeley Berkeley, C 947 Dscusson: eew of Op mps EE C45: Introducton

More information

Small signal analysis

Small signal analysis Small gnal analy. ntroducton Let u conder the crcut hown n Fg., where the nonlnear retor decrbed by the equaton g v havng graphcal repreentaton hown n Fg.. ( G (t G v(t v Fg. Fg. a D current ource wherea

More information

Ch. 6 Single Variable Control ES159/259

Ch. 6 Single Variable Control ES159/259 Ch. 6 Single Variable Control Single variable control How o we eterine the otor/actuator inut o a to coan the en effector in a eire otion? In general, the inut voltage/current oe not create intantaneou

More information

Section J8b: FET Low Frequency Response

Section J8b: FET Low Frequency Response ection J8b: FET ow Frequency epone In thi ection of our tudie, we re o to reiit the baic FET aplifier confiuration but with an additional twit The baic confiuration are the ae a we etiated ection J6 of

More information

Chapter 8: Fast Convolution. Keshab K. Parhi

Chapter 8: Fast Convolution. Keshab K. Parhi Cater 8: Fat Convoluton Keab K. Par Cater 8 Fat Convoluton Introducton Cook-Too Algort and Modfed Cook-Too Algort Wnograd Algort and Modfed Wnograd Algort Iterated Convoluton Cyclc Convoluton Degn of Fat

More information

Figure 1 Siemens PSSE Web Site

Figure 1 Siemens PSSE Web Site Stability Analyi of Dynamic Sytem. In the lat few lecture we have een how mall ignal Lalace domain model may be contructed of the dynamic erformance of ower ytem. The tability of uch ytem i a matter of

More information

Introduction. Modeling Data. Approach. Quality of Fit. Likelihood. Probabilistic Approach

Introduction. Modeling Data. Approach. Quality of Fit. Likelihood. Probabilistic Approach Introducton Modelng Data Gven a et of obervaton, we wh to ft a mathematcal model Model deend on adutable arameter traght lne: m + c n Polnomal: a + a + a + L+ a n Choce of model deend uon roblem Aroach

More information

1.3 Hence, calculate a formula for the force required to break the bond (i.e. the maximum value of F)

1.3 Hence, calculate a formula for the force required to break the bond (i.e. the maximum value of F) EN40: Dynacs and Vbratons Hoework 4: Work, Energy and Lnear Moentu Due Frday March 6 th School of Engneerng Brown Unversty 1. The Rydberg potental s a sple odel of atoc nteractons. It specfes the potental

More information

Chapter 7 Four-Wave Mixing phenomena

Chapter 7 Four-Wave Mixing phenomena Chapter 7 Four-Wave Mx phenomena We wll dcu n th chapter the general nonlnear optcal procee wth four nteract electromagnetc wave n a NLO medum. Frt note that FWM procee are allowed n all meda (nveron or

More information

55:041 Electronic Circuits

55:041 Electronic Circuits 55:04 Electronic ircuit Frequency eone hater 7 A. Kruger Frequency eone- ee age 4-5 o the Prologue in the text Imortant eview v = M co ωt + θ m = M e e j ωt+θ m = e M e jθ me jωt Thi lead to the concet

More information

Physics 3A: Linear Momentum. Physics 3A: Linear Momentum. Physics 3A: Linear Momentum. Physics 3A: Linear Momentum

Physics 3A: Linear Momentum. Physics 3A: Linear Momentum. Physics 3A: Linear Momentum. Physics 3A: Linear Momentum Recall that there was ore to oton than just spee A ore coplete escrpton of oton s the concept of lnear oentu: p v (8.) Beng a prouct of a scalar () an a vector (v), oentu s a vector: p v p y v y p z v

More information

Timing-Driven Placement. Outline

Timing-Driven Placement. Outline Tmng-Drven Placement DAC 97 Tutoral 1997 Blaauw, Cong, Tsay Outlne Background + Net-Based Aroach Zero-Slack Algorthm Modfed Zero-Slack Algorthm Path-Based Aroach Analytcal Aroach Fall 99, Prof. Le He 1

More information

CHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS

CHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS CHAPTER 9 LINEAR MOMENTUM, IMPULSE AND COLLISIONS 103 Phy 1 9.1 Lnear Momentum The prncple o energy conervaton can be ued to olve problem that are harder to olve jut ung Newton law. It ued to decrbe moton

More information

Ali Karimpour Associate Professor Ferdowsi University of Mashhad

Ali Karimpour Associate Professor Ferdowsi University of Mashhad LINEAR CONTROL SYSTEMS Ali Karimour Aoiate Profeor Ferdowi Univerity of Mahhad Leture 0 Leture 0 Frequeny domain hart Toi to be overed inlude: Relative tability meaure for minimum hae ytem. ain margin.

More information

Lecture 3 Examples and Problems

Lecture 3 Examples and Problems Lecture 3 Examles and Problems Mechancs & thermodynamcs Equartton Frst Law of Thermodynamcs Ideal gases Isothermal and adabatc rocesses Readng: Elements Ch. 1-3 Lecture 3, 1 Wllam Thomson (1824 1907) a.k.a.

More information

Problem Free Expansion of Ideal Gas

Problem Free Expansion of Ideal Gas Problem 4.3 Free Expanon o Ideal Ga In general: ds ds du P dv P dv NR V dn Snce U o deal ga ndependent on olume (du=), and N = cont n the proce: dv In a ere o nntemal ree expanon, entropy change by: S

More information

MOSFET Internal Capacitances

MOSFET Internal Capacitances ead MOSFET Iteral aactace S&S (5ed): Sec. 4.8, 4.9, 6.4, 6.6 S&S (6ed): Sec. 9., 9.., 9.3., 9.4-9.5 The curret-voltae relatoh we have dcued thu far for the MOSFET cature the ehavor at low ad oderate frequece.

More information

Feedforward Control identifiable disturbance measured,

Feedforward 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 information

SUPPLEMENTARY INFORMATION

SUPPLEMENTARY INFORMATION do: 0.08/nature09 I. Resonant absorpton of XUV pulses n Kr + usng the reduced densty matrx approach The quantum beats nvestgated n ths paper are the result of nterference between two exctaton paths of

More information

ASYMMETRIC TRAFFIC ASSIGNMENT WITH FLOW RESPONSIVE SIGNAL CONTROL IN AN URBAN NETWORK

ASYMMETRIC TRAFFIC ASSIGNMENT WITH FLOW RESPONSIVE SIGNAL CONTROL IN AN URBAN NETWORK AYMMETRIC TRAFFIC AIGNMENT WITH FLOW REPONIVE IGNAL CONTROL IN AN URBAN NETWORK Ken'etsu UCHIDA *, e'ch KAGAYA **, Tohru HAGIWARA *** Dept. of Engneerng - Hoado Unversty * E-al: uchda@eng.houda.ac.p **

More information

Built in Potential, V 0

Built in Potential, V 0 9/5/7 Indan Insttute of Technology Jodhur, Year 7 nalog Electroncs (Course Code: EE34) Lecture 3 4: ode contd Course Instructor: hree Prakash Twar Emal: stwar@tj.ac.n Webage: htt://home.tj.ac.n/~stwar/

More information

I Poles & zeros. I First-order systems. I Second-order systems. I E ect of additional poles. I E ect of zeros. I E ect of nonlinearities

I Poles & zeros. I First-order systems. I Second-order systems. I E ect of additional poles. I E ect of zeros. I E ect of nonlinearities EE C28 / ME C34 Lecture Chater 4 Time Resonse Alexandre Bayen Deartment of Electrical Engineering & Comuter Science University of California Berkeley Lecture abstract Toics covered in this resentation

More information

ELG3336: Op Amp-based Active Filters

ELG3336: Op Amp-based Active Filters ELG6: Op Amp-baed Actve Flter Advantage: educed ze and weght, and thereore paratc. Increaed relablty and mproved perormance. Smpler degn than or pave lter and can realze a wder range o uncton a well a

More information

Multipoint Analysis for Sibling Pairs. Biostatistics 666 Lecture 18

Multipoint Analysis for Sibling Pairs. Biostatistics 666 Lecture 18 Multpont Analyss for Sblng ars Bostatstcs 666 Lecture 8 revously Lnkage analyss wth pars of ndvduals Non-paraetrc BS Methods Maxu Lkelhood BD Based Method ossble Trangle Constrant AS Methods Covered So

More information

ECEN 605 LINEAR SYSTEMS. Lecture 20 Characteristics of Feedback Control Systems II Feedback and Stability 1/27

ECEN 605 LINEAR SYSTEMS. Lecture 20 Characteristics of Feedback Control Systems II Feedback and Stability 1/27 1/27 ECEN 605 LINEAR SYSTEMS Lecture 20 Characteristics of Feedback Control Systems II Feedback and Stability Feedback System Consider the feedback system u + G ol (s) y Figure 1: A unity feedback system

More information

The 7 th Balkan Conference on Operational Research BACOR 05 Constanta, May 2005, Romania

The 7 th Balkan Conference on Operational Research BACOR 05 Constanta, May 2005, Romania The 7 th alan onerence on Oeratonal Reearch AOR 5 ontanta, May 5, Roana THE ESTIMATIO OF THE GRAPH OX DIMESIO OF A LASS OF FRATALS ALIA ÃRULESU Ovdu Unverty, ontanta, Roana Abtract Fractal denon are the

More information

Lecture 8 Modal Analysis

Lecture 8 Modal Analysis Lecture 8 Modal Analyss 16.0 Release Introducton to ANSYS Mechancal 1 2015 ANSYS, Inc. February 27, 2015 Chapter Overvew In ths chapter free vbraton as well as pre-stressed vbraton analyses n Mechancal

More information

Week 11: Differential Amplifiers

Week 11: Differential Amplifiers ELE 0A Electronc rcuts Week : Dfferental Amplfers Lecture - Large sgnal analyss Topcs to coer A analyss Half-crcut analyss eadng Assgnment: hap 5.-5.8 of Jaeger and Blalock or hap 7. - 7.3, of Sedra and

More information

i-clicker i-clicker A B C a r Work & Kinetic Energy

i-clicker i-clicker A B C a r Work & Kinetic Energy ork & c Energ eew of Preou Lecture New polc for workhop You are epected to prnt, read, and thnk about the workhop ateral pror to cong to cla. (Th part of the polc not new!) There wll be a prelab queton

More information

Chapter 12 Lyes KADEM [Thermodynamics II] 2007

Chapter 12 Lyes KADEM [Thermodynamics II] 2007 Chapter 2 Lyes KDEM [Therodynacs II] 2007 Gas Mxtures In ths chapter we wll develop ethods for deternng therodynac propertes of a xture n order to apply the frst law to systes nvolvng xtures. Ths wll be

More information

Momentum. Momentum. Impulse. Momentum and Collisions

Momentum. Momentum. Impulse. Momentum and Collisions Momentum Momentum and Collsons From Newton s laws: orce must be present to change an object s elocty (speed and/or drecton) Wsh to consder eects o collsons and correspondng change n elocty Gol ball ntally

More information

Complete Variance Decomposition Methods. Cédric J. Sallaberry

Complete Variance Decomposition Methods. Cédric J. Sallaberry Comlete Varance Decomoston Methods Cédrc J. allaberry enstvty Analyss y y [,,, ] [ y, y,, ] y ny s a vector o uncertan nuts s a vector o results s a comle uncton successon o derent codes, systems o de,

More information

Lecture 5: Operational Amplifiers and Op Amp Circuits

Lecture 5: Operational Amplifiers and Op Amp Circuits Lecture 5: peratonal mplers and p mp Crcuts Gu-Yeon We Dson o Engneerng and ppled Scences Harard Unersty guyeon@eecs.harard.edu We erew eadng S&S: Chapter Supplemental eadng Background rmed wth our crcut

More information

Physical Chemistry I for Biochemists. Lecture 18 (2/23/11) Announcement

Physical Chemistry I for Biochemists. Lecture 18 (2/23/11) Announcement Physcal Chestry I or Bochests Che34 Lecture 18 (2/23/11) Yoshtaka Ish Ch5.8-5.11 & HW6 Revew o Ch. 5 or Quz 2 Announceent Quz 2 has a slar orat wth Quz1. e s the sae. ~2 ns. Answer or HW5 wll be uploaded

More information

Quasi-Static transient Thermal Stresses in a Robin's thin Rectangular plate with internal moving heat source

Quasi-Static transient Thermal Stresses in a Robin's thin Rectangular plate with internal moving heat source 31-7871 Weely Scence Research Journal Orgnal Artcle Vol-1, Issue-44, May 014 Quas-Statc transent Theral Stresses n a Robn's n Rectangular late w nternal ovng heat source D. T. Solane and M.. Durge ABSTRACT

More information

Lecture 6: Resonance II. Announcements

Lecture 6: Resonance II. Announcements EES 5 Spring 4, Lecture 6 Lecture 6: Reonance II EES 5 Spring 4, Lecture 6 Announcement The lab tart thi week You mut how up for lab to tay enrolled in the coure. The firt lab i available on the web ite,

More information

LECTURE :FACTOR ANALYSIS

LECTURE :FACTOR ANALYSIS LCUR :FACOR ANALYSIS Rta Osadchy Based on Lecture Notes by A. Ng Motvaton Dstrbuton coes fro MoG Have suffcent aount of data: >>n denson Use M to ft Mture of Gaussans nu. of tranng ponts If

More information

Lecture 12. Transport in Membranes (2)

Lecture 12. Transport in Membranes (2) Lecture 12. Transport n embranes (2) odule Flow Patterns - Perfect mxng - Countercurrent flow - Cocurrent flow - Crossflow embrane Cascades External ass-transfer Resstances Concentraton Polarzaton and

More information

3. MODELING OF PARALLEL THREE-PHASE CURRENT-UNIDIRECTIONAL CONVERTERS 3. MODELING OF PARALLEL THREE-PHASE CURRENT-

3. MODELING OF PARALLEL THREE-PHASE CURRENT-UNIDIRECTIONAL CONVERTERS 3. MODELING OF PARALLEL THREE-PHASE CURRENT- 3. MOEING OF PARAE THREE-PHASE URRENT-UNIIRETIONA ONERTERS 3. MOEING OF PARAE THREE-PHASE URRENT- UNIIRETIONA ONERTERS Ths chater eelos the moels of the arallel three-hase current-unrectonal swtch base

More information

Solution of Equilibrium Equation in Dynamic Analysis. Mode Superposition. Dominik Hauswirth Method of Finite Elements II Page 1

Solution of Equilibrium Equation in Dynamic Analysis. Mode Superposition. Dominik Hauswirth Method of Finite Elements II Page 1 Soluton of Equlbrum Equaton n Dynamc Analyss Mode Superposton Domnk Hauswrth..7 Method of Fnte Elements II Page Contents. Mode Superposton: Idea and Equatons. Example 9.7 3. Modes 4. Include Dampng 5.

More information

ECEN474/704: (Analog) VLSI Circuit Design Spring 2018

ECEN474/704: (Analog) VLSI Circuit Design Spring 2018 EEN474/704: (Anal) LSI cut De S 08 Lectue 8: Fequency ene Sa Pale Anal & Mxed-Sal ente Texa A&M Unety Annunceent & Aenda HW Due Ma 6 ead aza hate 3 & 6 Annunceent & Aenda n-suce A Fequency ene Oen-cut

More information

Linear Momentum. Equation 1

Linear Momentum. Equation 1 Lnear Momentum OBJECTIVE Obsere collsons between two carts, testng or the conseraton o momentum. Measure energy changes durng derent types o collsons. Classy collsons as elastc, nelastc, or completely

More information

Output Stages and Power Amplifiers

Output Stages and Power Amplifiers Output Stages and Power Aplfers Output stages wth a low output resstance can delver the output voltage to the load wthout loss of gan. arge sgnal aplfer are used to drve a CT, a loud speaker, a servootor,

More information

Lecture 14: More MOS Circuits and the Differential Amplifier

Lecture 14: More MOS Circuits and the Differential Amplifier Lecture 4: More MOS rcuts an the Dfferental Aplfer Gu-Yeon We Dson of nneern an Apple Scences Harar Unersty uyeon@eecs.harar.eu We Oerew Rean S&S: hapter 5.0, 6.~, 6.6 ackroun Han seen soe of the basc

More information

Rectilinear motion. Lecture 2: Kinematics of Particles. External motion is known, find force. External forces are known, find motion

Rectilinear motion. Lecture 2: Kinematics of Particles. External motion is known, find force. External forces are known, find motion Lecture : Kneatcs of Partcles Rectlnear oton Straght-Lne oton [.1] Analtcal solutons for poston/veloct [.1] Solvng equatons of oton Analtcal solutons (1 D revew) [.1] Nuercal solutons [.1] Nuercal ntegraton

More information

Quantum Particle Motion in Physical Space

Quantum Particle Motion in Physical Space Adv. Studes Theor. Phys., Vol. 8, 014, no. 1, 7-34 HIKARI Ltd, www.-hkar.co http://dx.do.org/10.1988/astp.014.311136 Quantu Partcle Moton n Physcal Space A. Yu. Saarn Dept. of Physcs, Saara State Techncal

More information

COMP th April, 2007 Clement Pang

COMP th April, 2007 Clement Pang COMP 540 12 th Aprl, 2007 Cleent Pang Boostng Cobnng weak classers Fts an Addtve Model Is essentally Forward Stagewse Addtve Modelng wth Exponental Loss Loss Functons Classcaton: Msclasscaton, Exponental,

More information

Chapter 25: Machining Centers, Machine Tool Structures and Machining Economics

Chapter 25: Machining Centers, Machine Tool Structures and Machining Economics Manufacturng Engneerng echnology n SI Unts, 6 th Edton Chapter 25: Machnng Centers, Machne ool Structures and Machnng Econocs Copyrght 200 Pearson Educaton South Asa Pte Ltd Chapter Outlne 2 Introducton

More information

Sampling Theory MODULE V LECTURE - 17 RATIO AND PRODUCT METHODS OF ESTIMATION

Sampling Theory MODULE V LECTURE - 17 RATIO AND PRODUCT METHODS OF ESTIMATION Samplng Theory MODULE V LECTURE - 7 RATIO AND PRODUCT METHODS OF ESTIMATION DR. SHALABH DEPARTMENT OF MATHEMATICS AND STATISTICS INDIAN INSTITUTE OF TECHNOLOG KANPUR Propertes of separate rato estmator:

More information

Page 1. SPH4U: Lecture 7. New Topic: Friction. Today s Agenda. Surface Friction... Surface Friction...

Page 1. SPH4U: Lecture 7. New Topic: Friction. Today s Agenda. Surface Friction... Surface Friction... SPH4U: Lecture 7 Today s Agenda rcton What s t? Systeatc catagores of forces How do we characterze t? Model of frcton Statc & Knetc frcton (knetc = dynac n soe languages) Soe probles nvolvng frcton ew

More information

Module 3: Element Properties Lecture 1: Natural Coordinates

Module 3: Element Properties Lecture 1: Natural Coordinates Module 3: Element Propertes Lecture : Natural Coordnates Natural coordnate system s bascally a local coordnate system whch allows the specfcaton of a pont wthn the element by a set of dmensonless numbers

More information

Lecture 3. Camera Models 2 & Camera Calibration. Professor Silvio Savarese Computational Vision and Geometry Lab. 13- Jan- 15.

Lecture 3. Camera Models 2 & Camera Calibration. Professor Silvio Savarese Computational Vision and Geometry Lab. 13- Jan- 15. Lecture Caera Models Caera Calbraton rofessor Slvo Savarese Coputatonal Vson and Geoetry Lab Slvo Savarese Lecture - - Jan- 5 Lecture Caera Models Caera Calbraton Recap of caera odels Caera calbraton proble

More information

Lecture #4 Capacitors and Inductors Energy Stored in C and L Equivalent Circuits Thevenin Norton

Lecture #4 Capacitors and Inductors Energy Stored in C and L Equivalent Circuits Thevenin Norton EES ntro. electroncs for S Sprng 003 Lecture : 0/03/03 A.R. Neureuther Verson Date 0/0/03 EES ntroducton to Electroncs for omputer Scence Andrew R. Neureuther Lecture # apactors and nductors Energy Stored

More information

Small-Signal Model for Buck/Boost Converter

Small-Signal Model for Buck/Boost Converter 4 Small-Sgnal Model for Buck/Boot Converter For the buck/boot converter, k k and k k becaue v v and v v. * f r m e The model can be ued to derve k, k, F, and H ( ),whch can be adapted to all the three

More information

FEEDFORWARD CONTROLLER DESIGN BASED ON H ANALYSIS

FEEDFORWARD CONTROLLER DESIGN BASED ON H ANALYSIS 271 FEEDFORWARD CONTROLLER DESIGN BASED ON H ANALYSIS Eduardo J. Adam * and Jacinto L. Marchetti Instituto de Desarrollo Tecnológico para la Industria Química (Universidad Nacional del Litoral - CONICET)

More information

s 0.068μ s Rearrange the function into a more convenient form and verify that it is still equal to the original.

s 0.068μ s Rearrange the function into a more convenient form and verify that it is still equal to the original. Title: TCS Traner Function Author: Eric Warmbier Decription: Thi document derive the variou traner unction or the TCS ytem on the IRTF. The ytem i broken down into block in a Viio document. A traner unction

More information

Lecture 16 Statistical Analysis in Biomaterials Research (Part II)

Lecture 16 Statistical Analysis in Biomaterials Research (Part II) 3.051J/0.340J 1 Lecture 16 Statstcal Analyss n Bomaterals Research (Part II) C. F Dstrbuton Allows comparson of varablty of behavor between populatons usng test of hypothess: σ x = σ x amed for Brtsh statstcan

More information

Prof. Paolo Colantonio a.a

Prof. Paolo Colantonio a.a Pro. Paolo olantono a.a. 3 4 Let s consder a two ports network o Two ports Network o L For passve network (.e. wthout nternal sources or actve devces), a general representaton can be made by a sutable

More information

Practical Newton s Method

Practical Newton s Method Practcal Newton s Method Lecture- n Newton s Method n Pure Newton s method converges radly once t s close to. It may not converge rom the remote startng ont he search drecton to be a descent drecton rue

More information

Digital PI Controller Equations

Digital PI Controller Equations Ver. 4, 9 th March 7 Dgtal PI Controller Equatons Probably the most common tye of controller n ndustral ower electroncs s the PI (Proortonal - Integral) controller. In feld orented motor control, PI controllers

More information

The multivariate Gaussian probability density function for random vector X (X 1,,X ) T. diagonal term of, denoted

The multivariate Gaussian probability density function for random vector X (X 1,,X ) T. diagonal term of, denoted Appendx Proof of heorem he multvarate Gauan probablty denty functon for random vector X (X,,X ) px exp / / x x mean and varance equal to the th dagonal term of, denoted he margnal dtrbuton of X Gauan wth

More information

2-Adic Complexity of a Sequence Obtained from a Periodic Binary Sequence by Either Inserting or Deleting k Symbols within One Period

2-Adic Complexity of a Sequence Obtained from a Periodic Binary Sequence by Either Inserting or Deleting k Symbols within One Period -Adc Comlexty of a Seuence Obtaned from a Perodc Bnary Seuence by Ether Insertng or Deletng Symbols wthn One Perod ZHAO Lu, WEN Qao-yan (State Key Laboratory of Networng and Swtchng echnology, Bejng Unversty

More information

Physics 207, Lecture 13, Oct. 15. Energy

Physics 207, Lecture 13, Oct. 15. Energy Physcs 07 Lecture 3 Physcs 07, Lecture 3, Oct. 5 Goals: Chapter 0 Understand the relatonshp between moton and energy Dene Potental Energy n a Hooke s Law sprng Deelop and explot conseraton o energy prncple

More information

PHYSICS 151 Notes for Online Lecture 2.3

PHYSICS 151 Notes for Online Lecture 2.3 PHYSICS 151 Note for Online Lecture.3 riction: The baic fact of acrocopic (everda) friction are: 1) rictional force depend on the two aterial that are liding pat each other. bo liding over a waed floor

More information

Scattering cross section (scattering width)

Scattering cross section (scattering width) Scatterng cro ecton (catterng wdth) We aw n the begnnng how a catterng cro ecton defned for a fnte catterer n ter of the cattered power An nfnte cylnder, however, not a fnte object The feld radated by

More information

Correlations in Underwater Acoustic Particle Velocity and Pressure Channels H. Guo 1, A. Abdi 1, A. Song 2, and M.Badiey 2

Correlations in Underwater Acoustic Particle Velocity and Pressure Channels H. Guo 1, A. Abdi 1, A. Song 2, and M.Badiey 2 Correlaton n Underwater Acoutc Partcle Veloct Preure Channel H. Guo A. Ad A. Song M.Bade Center for Wrele Councaton Sgnal Proceng Reearch et. of Electrcal Couter Engneerng New Jere Inttute of Technolog

More information

Distance-Based Approaches to Inferring Phylogenetic Trees

Distance-Based Approaches to Inferring Phylogenetic Trees Dstance-Base Approaches to Inferrng Phylogenetc Trees BMI/CS 576 www.bostat.wsc.eu/bm576.html Mark Craven craven@bostat.wsc.eu Fall 0 Representng stances n roote an unroote trees st(a,c) = 8 st(a,d) =

More information

Designing of Analog Filters.

Designing of Analog Filters. Deigning of Analog Filter. Aliaing and recontruction filter are analog filter, therefore we need to undertand the deign of analog filter firt before going into the deign of digital filter. Further the

More information

Chapter #3 EEE Subsea Control and Communication Systems

Chapter #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 information

Lecture-24. Enzyme kinetics and Enzyme inhibition-ii

Lecture-24. Enzyme kinetics and Enzyme inhibition-ii Lecture-24 Enzye knetcs and Enzye nhbton-ii Noncopette Inhbton A noncopette nhbtor can bnd wth enzye or wth enzye-substrate coplex to produce end coplex. Hence the nhbtor ust bnd at a dfferent ste fro

More information

OPTIMISATION. Introduction Single Variable Unconstrained Optimisation Multivariable Unconstrained Optimisation Linear Programming

OPTIMISATION. Introduction Single Variable Unconstrained Optimisation Multivariable Unconstrained Optimisation Linear Programming OPTIMIATION Introducton ngle Varable Unconstraned Optmsaton Multvarable Unconstraned Optmsaton Lnear Programmng Chapter Optmsaton /. Introducton In an engneerng analss, sometmes etremtes, ether mnmum or

More information

ECSE 4440 Control System Engineering. Project 1. Controller Design of a Second Order System TA

ECSE 4440 Control System Engineering. Project 1. Controller Design of a Second Order System TA ECSE 4440 Control Sytem Enineerin Project 1 Controller Dein of a Secon Orer Sytem TA Content 1. Abtract. Introuction 3. Controller Dein for a Sinle Penulum 4. Concluion 1. Abtract The uroe of thi roject

More information

OPTIMAL CONTROL FOR THREE-PHASE POWER CONVERTERS SVPWM BASED ON LINEAR QUADRATIC REGULATOR

OPTIMAL CONTROL FOR THREE-PHASE POWER CONVERTERS SVPWM BASED ON LINEAR QUADRATIC REGULATOR INERNAIONA JOURNA o ACADEMIC RESEARCH Vol. 4. No. 3. May, 0 OPIMA CONRO FOR HREE-PHASE POWER CONVERERS SVPWM BASED ON INEAR QUADRAIC REGUAOR Har Sutkno, e Jaa, Mochamad Ahar 3, Maurdh Hery Purnomo 3 Sekolah

More information

CHAPTER 4d. ROOTS OF EQUATIONS

CHAPTER 4d. ROOTS OF EQUATIONS CHAPTER 4d. ROOTS OF EQUATIONS A. J. Clark School o Engneerng Department o Cvl and Envronmental Engneerng by Dr. Ibrahm A. Assakka Sprng 00 ENCE 03 - Computaton Methods n Cvl Engneerng II Department o

More information

CANKAYA UNIVERSITY FACULTY OF ENGINEERING AND ARCHITECTURE MECHANICAL ENGINEERING DEPARTMENT ME 212 THERMODYNAMICS II CHAPTER 11 EXAMPLES SOLUTION

CANKAYA UNIVERSITY FACULTY OF ENGINEERING AND ARCHITECTURE MECHANICAL ENGINEERING DEPARTMENT ME 212 THERMODYNAMICS II CHAPTER 11 EXAMPLES SOLUTION CANKAYA UNIVESIY FACULY OF ENGINEEING AND ACHIECUE MECHANICAL ENGINEEING DEPAMEN ME HEMODYNAMICS II CHAPE EXAMPLES SOLUION ) he reure wthn a. m tank hould not exeed 0 ar. Chek the reure wthn the tank f

More information

INPUT-OUTPUT PAIRING OF MULTIVARIABLE PREDICTIVE CONTROL

INPUT-OUTPUT PAIRING OF MULTIVARIABLE PREDICTIVE CONTROL INPUT-OUTPUT PAIRING OF MULTIVARIABLE PREDICTIVE CONTROL Lng-Cong Chen #, Pu Yuan*, Gu-L Zhang* *Unversty of Petroleu, P.O. Box 902 Beng 00083, Chna # GAIN Tech Co., P.O. Box 902ext.79, Beng 00083, Chna

More information

Approximation of Optimal Interface Boundary Conditions for Two-Lagrange Multiplier FETI Method

Approximation of Optimal Interface Boundary Conditions for Two-Lagrange Multiplier FETI Method Aroxmaton of Otmal Interface Boundary Condtons for Two-Lagrange Multler FETI Method F.-X. Roux, F. Magoulès, L. Seres, Y. Boubendr ONERA, 29 av. de la Dvson Leclerc, BP72, 92322 Châtllon, France, ,

More information

Physics for Scientists and Engineers. Chapter 9 Impulse and Momentum

Physics for Scientists and Engineers. Chapter 9 Impulse and Momentum Physcs or Scentsts and Engneers Chapter 9 Impulse and Momentum Sprng, 008 Ho Jung Pak Lnear Momentum Lnear momentum o an object o mass m movng wth a velocty v s dened to be p mv Momentum and lnear momentum

More information

Sensitivity analysis of computer experiments

Sensitivity analysis of computer experiments Senstvty analyss o comuter exerments Fabrce Gamboa Bertrand Iooss 0/03/03 The global methodology o uncertanty management Ste C : Proagaton o uncertanty sources Ste B: Quantcaton o uncertanty sources Modeled

More information

Identification of Modal Parameters from Ambient Vibration Data by Modified Eigensystem Realization Algorithm *

Identification of Modal Parameters from Ambient Vibration Data by Modified Eigensystem Realization Algorithm * Journal of Aeronautcs, Astronautcs and Avaton, Seres A, Vol.42, No.2.079-086 (2010) 79 Identfcaton of Modal Paraeters fro Abent Vbraton Data by Modfed Egensyste ealzaton Algorth * Dar-Yun Chang **, Chang-Sheng

More information

Clock-Driven Scheduling (in-depth) Cyclic Schedules: General Structure

Clock-Driven Scheduling (in-depth) Cyclic Schedules: General Structure CPSC-663: Real-me Systems n-depth Precompute statc schedule o-lne e.g. at desgn tme: can aord expensve algorthms. Idle tmes can be used or aperodc jobs. Possble mplementaton: able-drven Schedulng table

More information

Lecture 09 Systems of Particles and Conservation of Linear Momentum

Lecture 09 Systems of Particles and Conservation of Linear Momentum Lecture 09 Systes o Partcles and Conseraton o Lnear oentu 9. Lnear oentu and Its Conseraton 9. Isolated Syste lnear oentu: P F dp dt d( dt d dt a solated syste F ext 0 dp dp F, F dt dt dp dp d F F 0, 0

More information

IMPROVEMENT OF CONTROL PERFORMANCES USING FRACTIONAL PI λ D μ CONTROLLERS. K. Bettou., A. Charef

IMPROVEMENT OF CONTROL PERFORMANCES USING FRACTIONAL PI λ D μ CONTROLLERS. K. Bettou., A. Charef MPROVMT OF OTROL PRFORMAS USG FRATOAL P λ μ OTROLLRS. Bettou., A. haref éartement d lectronque Unverté Mentour Route An l-bey-5 - ontantne Algére -mal: bettou_kh@yahoo.com Abtract: Th aer deal wth the

More information

Confidence intervals for weighted polynomial calibrations

Confidence intervals for weighted polynomial calibrations Confdence ntervals for weghted olynomal calbratons Sergey Maltsev, Amersand Ltd., Moscow, Russa; ur Kalambet, Amersand Internatonal, Inc., Beachwood, OH e-mal: kalambet@amersand-ntl.com htt://www.chromandsec.com

More information

Priority Queuing with Finite Buffer Size and Randomized Push-out Mechanism

Priority Queuing with Finite Buffer Size and Randomized Push-out Mechanism ICN 00 Prorty Queung wth Fnte Buffer Sze and Randomzed Push-out Mechansm Vladmr Zaborovsy, Oleg Zayats, Vladmr Muluha Polytechncal Unversty, Sant-Petersburg, Russa Arl 4, 00 Content I. Introducton II.

More information

1. The number of significant figures in the number is a. 4 b. 5 c. 6 d. 7

1. The number of significant figures in the number is a. 4 b. 5 c. 6 d. 7 Name: ID: Anwer Key There a heet o ueul ormulae and ome converon actor at the end. Crcle your anwer clearly. All problem are pont ecept a ew marked wth ther own core. Mamum core 100. There are a total

More information