Kinematics and kinematic functions

Size: px
Start display at page:

Download "Kinematics and kinematic functions"

Transcription

1 Kinemaics and kinemaic funcions Kinemaics deals wih he sudy of four funcions (called kinemaic funcions or KFs) ha mahemaically ransform join variables ino caresian variables and vice versa Direc Posiion KF: from join space variables o ask space pose Inverse Posiion KF: from ask space pose o join space variables Direc Velociy KF: from join space velociies o ask space velociies Inverse Velociy KF: from ask space velociies o join space velociies

2 Kinemaic funcions Posiions and velociies of wha? I can be he posiion or velociy of any poin of he robo, bu, usually, is he las RF posiion and velociy LAST RF R P R BASE 0? Wha is he relaion beween hese wo RF?

3 Kinemaic funcions The firs sep for defining KFs is o fix a reference frame on each body In general, o move from a RF o he following one, i is necessary o define 6 parameers (hree ranslaions of he RF origin + hree angles of he RF roaion) A number of convenions were inroduced o reduce henumber of parameers and o find a common way o describe he relaive posiion of reference frames Denavi Harenberg convenions (1955) were he firs o be inroduced and are widely used in indusry (wih some minor modificaions)

4 A procedure o compue he KFs 1 1. Selec and idenify bodies and he relaive consrains 2. Se he RF on each body 3. Compue he homogeneous ransformaion beween he base RF and he final RF 4. Exrac he direc posiion KF from he homogeneous ransformaion 5. Compue he inverse posiion KF 6. Inverse velociy KF: analyical or geomerical approach

5 A procedure o compue he KFs 2 1. Selec and idenify links and joins 2. Se all RFs using DH convenions 3. Define consan geomerical parameers q () 4 q () 5 q () 2 q () 6 q () 1 R P FINAL R 0 BASE 0 T P () () q () q T q = R P P P T 0 1

6 Join and caresian variables Join variables q1() q2() q 3() q() = q4() q 5() q6() Direc KF Task/caresian variables/pose x 1() x2() x 3() p() = α1() α2() α3() Inverse KF posiion orienaion 1 p() = f ( q () ) q() = f ( p() )

7 Direc posiion KF 1 q1() p1() q 2() p2() q ( ()) 3() p3() x q q() = ( ()) = = p q q 4() p4() q ( ()) 5() p5() α q q6() p6() posiion orienaion P P P 1 ( q1) 2 ( q2) 3 ( q3) 4 ( q4) 5 ( q5) 6 ( q6) R T = T T T T T T T P = 1 0 T orienaion posiion R = R ( q () ) = ( q () ) P P P P

8 Direc posiion KF 2 T 0 P 0 0 RP P = 0 T 1 Direc caresian posiion KF: easy x x 1 1 x 0 2 P 2 x 3 3 Direc caresian orienaion KF: no so easy o compue, bu no difficul We will solve he problem in he following slides

9 Direc posiion KF 3 ( () ) α( q() ) Rq We wan o compue angles from he roaion marix. Bu i is imporan o decide which represenaion o use α ( q() )? Euler angles RPY angles Quaernions Axis angle represenaion

10 q () ( ) 2 () x q q () 3 pq ( ( )) = = q( ) q () α ( ) 4 () q q () 5 q () 6 Inverse posiion KF 1 q () 1 This KF is imporan, since conrol acion are applied o he join moors, while he user wans o work wih caresian posiions and orienaions q () 3 q () 1 q () 2 ( () ) x q α( q() )

11 Inverse posiion KF 2 1. The problem is complex and here is no clear recipe o solve i 2. If a spherical wris is presen, hen a soluion is guaraneed, bu we mus find i There are several possibiliies Use brue force or previous soluions found for similar chains Use inverse velociy KF Usesymbolicmanipulaion symbolic manipulaion programs (compuer algebra sysems as Mahemaica, Maple, Maxima,, Lisp) Ieraively compue an approximaed numerical expression for he nonlinear equaion (Newon mehod or ohers) ( ) 1 ( ) { 1 q() f ( p() ) } q f p 1 () = () q() f p() = 0 min () ()

12 Direc velociy KF 1 Linear and angular direc velociy KF q () p () 1 1 q () p () 2 2 (), () x q q q () p () 3 3 q () = () q () p = p () = 4 4 (), () q q q () p () 5 5 q () p () 6 6 ( ) Linear velociy ( (), () ) vq q = (), () ω q q α ( ) ( ) Angular velociy

13 Direc velociy KF 2 A bi brief review of mahemaical i noaions i General rule d pq (()) d d ( () ) x q d = d ( () ) α q d d d f ( q () ) = f ( q (),, q (),, q () ) i i 1 j n d d f i f i f i = q () + + q () + + q () 1 j n q q q 1 j n

14 Direc velociy KF 3 q () 1 d f f f ( ()) i i i f q () T q = ( () ) () i = j fi J q q d q q q 1 j n q () n f f f JACOBIAN q q q 1 j n q () 1 d ( ) f f f i i i f q() = q () ( () ) () j d = q q q J q q 1 j n q () n f f f m m m q q q 1 j n

15 Furher noes on he Jacobians Velociykinemaics is characerizedby Jacobians There are wo ypes of Jacobians: Geomerical Jacobian Analyical ljacobian J g J a ( ) p () = J q() q () also called Task Jacobian The firs one is relaed o Geomerical Velociies v p x = = ω J q g The second one is relaed o Analyical Velociies p x = = α α J q a

16 Geomerical and Analyical velociies Wha is he difference beween hese wo angular velociies? On he conrary, linear velociies do no have his problem: analyical and geomerical velociies are he same vecor, ha can be inegraed o give he caresian posiion

17

18

19

20

21 Derivaive of a roaion marix

22

23 Some useful formulas

Basilio Bona ROBOTICA 03CFIOR 1

Basilio Bona ROBOTICA 03CFIOR 1 Indusrial Robos Kinemaics 1 Kinemaics and kinemaic funcions Kinemaics deals wih he sudy of four funcions (called kinemaic funcions or KFs) ha mahemaically ransform join variables ino caresian variables

More information

Kinematics and kinematic functions

Kinematics and kinematic functions ROBOTICS 01PEEQW Basilio Bona DAUIN Poliecnico di Torino Kinemaic funcions Kinemaics and kinemaic funcions Kinemaics deals wih he sudy of four funcions(called kinemaic funcions or KFs) ha mahemaically

More information

Announcements: Warm-up Exercise:

Announcements: Warm-up Exercise: Fri Apr 13 7.1 Sysems of differenial equaions - o model muli-componen sysems via comparmenal analysis hp//en.wikipedia.org/wiki/muli-comparmen_model Announcemens Warm-up Exercise Here's a relaively simple

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

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

More information

From Particles to Rigid Bodies

From Particles to Rigid Bodies Rigid Body Dynamics From Paricles o Rigid Bodies Paricles No roaions Linear velociy v only Rigid bodies Body roaions Linear velociy v Angular velociy ω Rigid Bodies Rigid bodies have boh a posiion and

More information

Trajectory planning in Cartesian space

Trajectory planning in Cartesian space Roboics 1 Trajecory planning in Caresian space Prof. Alessandro De Luca Roboics 1 1 Trajecories in Caresian space in general, he rajecory planning mehods proposed in he join space can be applied also in

More information

Solutions from Chapter 9.1 and 9.2

Solutions from Chapter 9.1 and 9.2 Soluions from Chaper 9 and 92 Secion 9 Problem # This basically boils down o an exercise in he chain rule from calculus We are looking for soluions of he form: u( x) = f( k x c) where k x R 3 and k is

More information

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still. Lecure - Kinemaics in One Dimension Displacemen, Velociy and Acceleraion Everyhing in he world is moving. Nohing says sill. Moion occurs a all scales of he universe, saring from he moion of elecrons in

More information

THE 2-BODY PROBLEM. FIGURE 1. A pair of ellipses sharing a common focus. (c,b) c+a ROBERT J. VANDERBEI

THE 2-BODY PROBLEM. FIGURE 1. A pair of ellipses sharing a common focus. (c,b) c+a ROBERT J. VANDERBEI THE 2-BODY PROBLEM ROBERT J. VANDERBEI ABSTRACT. In his shor noe, we show ha a pair of ellipses wih a common focus is a soluion o he 2-body problem. INTRODUCTION. Solving he 2-body problem from scrach

More information

Robotics I. April 11, The kinematics of a 3R spatial robot is specified by the Denavit-Hartenberg parameters in Tab. 1.

Robotics I. April 11, The kinematics of a 3R spatial robot is specified by the Denavit-Hartenberg parameters in Tab. 1. Roboics I April 11, 017 Exercise 1 he kinemaics of a 3R spaial robo is specified by he Denavi-Harenberg parameers in ab 1 i α i d i a i θ i 1 π/ L 1 0 1 0 0 L 3 0 0 L 3 3 able 1: able of DH parameers of

More information

Chapter 2. First Order Scalar Equations

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

More information

ME 391 Mechanical Engineering Analysis

ME 391 Mechanical Engineering Analysis Fall 04 ME 39 Mechanical Engineering Analsis Eam # Soluions Direcions: Open noes (including course web posings). No books, compuers, or phones. An calculaor is fair game. Problem Deermine he posiion of

More information

Hamilton- J acobi Equation: Explicit Formulas In this lecture we try to apply the method of characteristics to the Hamilton-Jacobi equation: u t

Hamilton- J acobi Equation: Explicit Formulas In this lecture we try to apply the method of characteristics to the Hamilton-Jacobi equation: u t M ah 5 2 7 Fall 2 0 0 9 L ecure 1 0 O c. 7, 2 0 0 9 Hamilon- J acobi Equaion: Explici Formulas In his lecure we ry o apply he mehod of characerisics o he Hamilon-Jacobi equaion: u + H D u, x = 0 in R n

More information

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

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

More information

Distance Between Two Ellipses in 3D

Distance Between Two Ellipses in 3D Disance Beween Two Ellipses in 3D David Eberly Magic Sofware 6006 Meadow Run Cour Chapel Hill, NC 27516 eberly@magic-sofware.com 1 Inroducion An ellipse in 3D is represened by a cener C, uni lengh axes

More information

Starting from a familiar curve

Starting from a familiar curve In[]:= NoebookDirecory Ou[]= C:\Dropbox\Work\myweb\Courses\Mah_pages\Mah_5\ You can evaluae he enire noebook by using he keyboard shorcu Al+v o, or he menu iem Evaluaion Evaluae Noebook. Saring from a

More information

Lab #2: Kinematics in 1-Dimension

Lab #2: Kinematics in 1-Dimension Reading Assignmen: Chaper 2, Secions 2-1 hrough 2-8 Lab #2: Kinemaics in 1-Dimension Inroducion: The sudy of moion is broken ino wo main areas of sudy kinemaics and dynamics. Kinemaics is he descripion

More information

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

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

More information

Some Basic Information about M-S-D Systems

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

More information

Two Coupled Oscillators / Normal Modes

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

More information

The motions of the celt on a horizontal plane with viscous friction

The motions of the celt on a horizontal plane with viscous friction The h Join Inernaional Conference on Mulibody Sysem Dynamics June 8, 18, Lisboa, Porugal The moions of he cel on a horizonal plane wih viscous fricion Maria A. Munisyna 1 1 Moscow Insiue of Physics and

More information

CSE 3802 / ECE Numerical Methods in Scientific Computation. Jinbo Bi. Department of Computer Science & Engineering

CSE 3802 / ECE Numerical Methods in Scientific Computation. Jinbo Bi. Department of Computer Science & Engineering CSE 3802 / ECE 3431 Numerical Mehods in Scienific Compuaion Jinbo Bi Deparmen of Compuer Science & Engineering hp://www.engr.uconn.edu/~jinbo 1 Ph.D in Mahemaics The Insrucor Previous professional experience:

More information

Chapter 3 Boundary Value Problem

Chapter 3 Boundary Value Problem Chaper 3 Boundary Value Problem A boundary value problem (BVP) is a problem, ypically an ODE or a PDE, which has values assigned on he physical boundary of he domain in which he problem is specified. Le

More information

Math Week 14 April 16-20: sections first order systems of linear differential equations; 7.4 mass-spring systems.

Math Week 14 April 16-20: sections first order systems of linear differential equations; 7.4 mass-spring systems. Mah 2250-004 Week 4 April 6-20 secions 7.-7.3 firs order sysems of linear differenial equaions; 7.4 mass-spring sysems. Mon Apr 6 7.-7.2 Sysems of differenial equaions (7.), and he vecor Calculus we need

More information

EE 315 Notes. Gürdal Arslan CLASS 1. (Sections ) What is a signal?

EE 315 Notes. Gürdal Arslan CLASS 1. (Sections ) What is a signal? EE 35 Noes Gürdal Arslan CLASS (Secions.-.2) Wha is a signal? In his class, a signal is some funcion of ime and i represens how some physical quaniy changes over some window of ime. Examples: velociy of

More information

Elements of Computer Graphics

Elements of Computer Graphics CS580: Compuer Graphics Min H. Kim KAIST School of Compuing Elemens of Compuer Graphics Geomery Maerial model Ligh Rendering Virual phoography 2 Foundaions of Compuer Graphics A PINHOLE CAMERA IN 3D 3

More information

Lecture 20: Riccati Equations and Least Squares Feedback Control

Lecture 20: Riccati Equations and Least Squares Feedback Control 34-5 LINEAR SYSTEMS Lecure : Riccai Equaions and Leas Squares Feedback Conrol 5.6.4 Sae Feedback via Riccai Equaions A recursive approach in generaing he marix-valued funcion W ( ) equaion for i for he

More information

Non-uniform circular motion *

Non-uniform circular motion * OpenSax-CNX module: m14020 1 Non-uniform circular moion * Sunil Kumar Singh This work is produced by OpenSax-CNX and licensed under he Creaive Commons Aribuion License 2.0 Wha do we mean by non-uniform

More information

Chapter 6. Systems of First Order Linear Differential Equations

Chapter 6. Systems of First Order Linear Differential Equations Chaper 6 Sysems of Firs Order Linear Differenial Equaions We will only discuss firs order sysems However higher order sysems may be made ino firs order sysems by a rick shown below We will have a sligh

More information

L07. KALMAN FILTERING FOR NON-LINEAR SYSTEMS. NA568 Mobile Robotics: Methods & Algorithms

L07. KALMAN FILTERING FOR NON-LINEAR SYSTEMS. NA568 Mobile Robotics: Methods & Algorithms L07. KALMAN FILTERING FOR NON-LINEAR SYSTEMS NA568 Mobile Roboics: Mehods & Algorihms Today s Topic Quick review on (Linear) Kalman Filer Kalman Filering for Non-Linear Sysems Exended Kalman Filer (EKF)

More information

ODEs II, Lecture 1: Homogeneous Linear Systems - I. Mike Raugh 1. March 8, 2004

ODEs II, Lecture 1: Homogeneous Linear Systems - I. Mike Raugh 1. March 8, 2004 ODEs II, Lecure : Homogeneous Linear Sysems - I Mike Raugh March 8, 4 Inroducion. In he firs lecure we discussed a sysem of linear ODEs for modeling he excreion of lead from he human body, saw how o ransform

More information

Traveling Waves. Chapter Introduction

Traveling Waves. Chapter Introduction Chaper 4 Traveling Waves 4.1 Inroducion To dae, we have considered oscillaions, i.e., periodic, ofen harmonic, variaions of a physical characerisic of a sysem. The sysem a one ime is indisinguishable from

More information

10. State Space Methods

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

More information

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon 3..3 INRODUCION O DYNAMIC OPIMIZAION: DISCREE IME PROBLEMS A. he Hamilonian and Firs-Order Condiions in a Finie ime Horizon Define a new funcion, he Hamilonian funcion, H. H he change in he oal value of

More information

2. Nonlinear Conservation Law Equations

2. Nonlinear Conservation Law Equations . Nonlinear Conservaion Law Equaions One of he clear lessons learned over recen years in sudying nonlinear parial differenial equaions is ha i is generally no wise o ry o aack a general class of nonlinear

More information

MATH 128A, SUMMER 2009, FINAL EXAM SOLUTION

MATH 128A, SUMMER 2009, FINAL EXAM SOLUTION MATH 28A, SUMME 2009, FINAL EXAM SOLUTION BENJAMIN JOHNSON () (8 poins) [Lagrange Inerpolaion] (a) (4 poins) Le f be a funcion defined a some real numbers x 0,..., x n. Give a defining equaion for he Lagrange

More information

This is an example to show you how SMath can calculate the movement of kinematic mechanisms.

This is an example to show you how SMath can calculate the movement of kinematic mechanisms. Dec :5:6 - Kinemaics model of Simple Arm.sm This file is provided for educaional purposes as guidance for he use of he sofware ool. I is no guaraeed o be free from errors or ommissions. The mehods and

More information

Lecture 10: Wave equation, solution by spherical means

Lecture 10: Wave equation, solution by spherical means Lecure : Wave equaion, soluion by spherical means Physical modeling eample: Elasodynamics u (; ) displacemen vecor in elasic body occupying a domain U R n, U, The posiion of he maerial poin siing a U in

More information

Multi-scale 2D acoustic full waveform inversion with high frequency impulsive source

Multi-scale 2D acoustic full waveform inversion with high frequency impulsive source Muli-scale D acousic full waveform inversion wih high frequency impulsive source Vladimir N Zubov*, Universiy of Calgary, Calgary AB vzubov@ucalgaryca and Michael P Lamoureux, Universiy of Calgary, Calgary

More information

Week 1 Lecture 2 Problems 2, 5. What if something oscillates with no obvious spring? What is ω? (problem set problem)

Week 1 Lecture 2 Problems 2, 5. What if something oscillates with no obvious spring? What is ω? (problem set problem) Week 1 Lecure Problems, 5 Wha if somehing oscillaes wih no obvious spring? Wha is ω? (problem se problem) Sar wih Try and ge o SHM form E. Full beer can in lake, oscillaing F = m & = ge rearrange: F =

More information

Differential Equations

Differential Equations Mah 21 (Fall 29) Differenial Equaions Soluion #3 1. Find he paricular soluion of he following differenial equaion by variaion of parameer (a) y + y = csc (b) 2 y + y y = ln, > Soluion: (a) The corresponding

More information

ROBOTICS 01PEEQW. Basilio Bona DAUIN Politecnico di Torino

ROBOTICS 01PEEQW. Basilio Bona DAUIN Politecnico di Torino ROBOTICS 01PEEQW Basilio Bona DAUIN Politecnico di Torino Kinematic Functions Kinematic functions Kinematics deals with the study of four functions(called kinematic functions or KFs) that mathematically

More information

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

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

More information

Solving a System of Nonlinear Functional Equations Using Revised New Iterative Method

Solving a System of Nonlinear Functional Equations Using Revised New Iterative Method Solving a Sysem of Nonlinear Funcional Equaions Using Revised New Ieraive Mehod Sachin Bhalekar and Varsha Dafardar-Gejji Absrac In he presen paper, we presen a modificaion of he New Ieraive Mehod (NIM

More information

SUMMARY. CS380: Introduction to Computer Graphics Quaternions Chapter 7. Min H. Kim KAIST School of Computing 18/04/06.

SUMMARY. CS380: Introduction to Computer Graphics Quaternions Chapter 7. Min H. Kim KAIST School of Computing 18/04/06. CS380: Inroducion o Compuer Graphics Quaernions Chaper 7 Min H. Kim KAIST School of Compuing Hello World 3D SUMMARY 2 1 Modelview marix Modelview marix (MVM) E 1 O Describes he orienaion and posiion of

More information

Overview. COMP14112: Artificial Intelligence Fundamentals. Lecture 0 Very Brief Overview. Structure of this course

Overview. COMP14112: Artificial Intelligence Fundamentals. Lecture 0 Very Brief Overview. Structure of this course OMP: Arificial Inelligence Fundamenals Lecure 0 Very Brief Overview Lecurer: Email: Xiao-Jun Zeng x.zeng@mancheser.ac.uk Overview This course will focus mainly on probabilisic mehods in AI We shall presen

More information

Computation of the Effect of Space Harmonics on Starting Process of Induction Motors Using TSFEM

Computation of the Effect of Space Harmonics on Starting Process of Induction Motors Using TSFEM Journal of elecrical sysems Special Issue N 01 : November 2009 pp: 48-52 Compuaion of he Effec of Space Harmonics on Saring Process of Inducion Moors Using TSFEM Youcef Ouazir USTHB Laboraoire des sysèmes

More information

4.1.1 Mindlin plates: Bending theory and variational formulation

4.1.1 Mindlin plates: Bending theory and variational formulation Chaper 4 soropic fla shell elemens n his chaper, fia shell elemens are formulaed hrough he assembly of membrane and plae elemens. The exac soluion of a shell approximaed by fia faces compared o he exac

More information

KINEMATICS IN ONE DIMENSION

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

More information

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

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

More information

Theory of! Partial Differential Equations!

Theory of! Partial Differential Equations! hp://www.nd.edu/~gryggva/cfd-course/! Ouline! Theory o! Parial Dierenial Equaions! Gréar Tryggvason! Spring 011! Basic Properies o PDE!! Quasi-linear Firs Order Equaions! - Characerisics! - Linear and

More information

Theory of! Partial Differential Equations-I!

Theory of! Partial Differential Equations-I! hp://users.wpi.edu/~grear/me61.hml! Ouline! Theory o! Parial Dierenial Equaions-I! Gréar Tryggvason! Spring 010! Basic Properies o PDE!! Quasi-linear Firs Order Equaions! - Characerisics! - Linear and

More information

5.2 GRAPHICAL VELOCITY ANALYSIS Polygon Method

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

More information

R t. C t P t. + u t. C t = αp t + βr t + v t. + β + w t

R t. C t P t. + u t. C t = αp t + βr t + v t. + β + w t Exercise 7 C P = α + β R P + u C = αp + βr + v (a) (b) C R = α P R + β + w (c) Assumpions abou he disurbances u, v, w : Classical assumions on he disurbance of one of he equaions, eg. on (b): E(v v s P,

More information

Online Appendix to Solution Methods for Models with Rare Disasters

Online Appendix to Solution Methods for Models with Rare Disasters Online Appendix o Soluion Mehods for Models wih Rare Disasers Jesús Fernández-Villaverde and Oren Levinal In his Online Appendix, we presen he Euler condiions of he model, we develop he pricing Calvo block,

More information

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Simulaion-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Week Descripion Reading Maerial 2 Compuer Simulaion of Dynamic Models Finie Difference, coninuous saes, discree ime Simple Mehods Euler Trapezoid

More information

HOMEWORK # 2: MATH 211, SPRING Note: This is the last solution set where I will describe the MATLAB I used to make my pictures.

HOMEWORK # 2: MATH 211, SPRING Note: This is the last solution set where I will describe the MATLAB I used to make my pictures. HOMEWORK # 2: MATH 2, SPRING 25 TJ HITCHMAN Noe: This is he las soluion se where I will describe he MATLAB I used o make my picures.. Exercises from he ex.. Chaper 2.. Problem 6. We are o show ha y() =

More information

HW6: MRI Imaging Pulse Sequences (7 Problems for 100 pts)

HW6: MRI Imaging Pulse Sequences (7 Problems for 100 pts) HW6: MRI Imaging Pulse Sequences (7 Problems for 100 ps) GOAL The overall goal of HW6 is o beer undersand pulse sequences for MRI image reconsrucion. OBJECTIVES 1) Design a spin echo pulse sequence o image

More information

Estimation of Poses with Particle Filters

Estimation of Poses with Particle Filters Esimaion of Poses wih Paricle Filers Dr.-Ing. Bernd Ludwig Chair for Arificial Inelligence Deparmen of Compuer Science Friedrich-Alexander-Universiä Erlangen-Nürnberg 12/05/2008 Dr.-Ing. Bernd Ludwig (FAU

More information

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

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

More information

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

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

More information

Notes on Kalman Filtering

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

More information

LAPLACE TRANSFORM AND TRANSFER FUNCTION

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

More information

1 1 + x 2 dx. tan 1 (2) = ] ] x 3. Solution: Recall that the given integral is improper because. x 3. 1 x 3. dx = lim dx.

1 1 + x 2 dx. tan 1 (2) = ] ] x 3. Solution: Recall that the given integral is improper because. x 3. 1 x 3. dx = lim dx. . Use Simpson s rule wih n 4 o esimae an () +. Soluion: Since we are using 4 seps, 4 Thus we have [ ( ) f() + 4f + f() + 4f 3 [ + 4 4 6 5 + + 4 4 3 + ] 5 [ + 6 6 5 + + 6 3 + ]. 5. Our funcion is f() +.

More information

Translational-Rotational Motion of Earth Artificial Satellite (EAS) in Hill's Gravity Field

Translational-Rotational Motion of Earth Artificial Satellite (EAS) in Hill's Gravity Field Translaional-Roaional Moion of Earh Arificial Saellie (EAS) in Hill's Graviy Field Asemessova alamkas,a, Bekov Askar,b, Shinibaev Maksu, Ussipbekova Dinara Republic of azakhsan, Almay, Sapaev Sree, azakh

More information

Vehicle Arrival Models : Headway

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

More information

Class Meeting # 10: Introduction to the Wave Equation

Class Meeting # 10: Introduction to the Wave Equation MATH 8.5 COURSE NOTES - CLASS MEETING # 0 8.5 Inroducion o PDEs, Fall 0 Professor: Jared Speck Class Meeing # 0: Inroducion o he Wave Equaion. Wha is he wave equaion? The sandard wave equaion for a funcion

More information

Modal identification of structures from roving input data by means of maximum likelihood estimation of the state space model

Modal identification of structures from roving input data by means of maximum likelihood estimation of the state space model Modal idenificaion of srucures from roving inpu daa by means of maximum likelihood esimaion of he sae space model J. Cara, J. Juan, E. Alarcón Absrac The usual way o perform a forced vibraion es is o fix

More information

Kinematics Vocabulary. Kinematics and One Dimensional Motion. Position. Coordinate System in One Dimension. Kinema means movement 8.

Kinematics Vocabulary. Kinematics and One Dimensional Motion. Position. Coordinate System in One Dimension. Kinema means movement 8. Kinemaics Vocabulary Kinemaics and One Dimensional Moion 8.1 WD1 Kinema means movemen Mahemaical descripion of moion Posiion Time Inerval Displacemen Velociy; absolue value: speed Acceleraion Averages

More information

CHEMICAL KINETICS: 1. Rate Order Rate law Rate constant Half-life Temperature Dependence

CHEMICAL KINETICS: 1. Rate Order Rate law Rate constant Half-life Temperature Dependence CHEMICL KINETICS: Rae Order Rae law Rae consan Half-life Temperaure Dependence Chemical Reacions Kineics Chemical ineics is he sudy of ime dependence of he change in he concenraion of reacans and producs.

More information

Chapter Q1. We need to understand Classical wave first. 3/28/2004 H133 Spring

Chapter Q1. We need to understand Classical wave first. 3/28/2004 H133 Spring Chaper Q1 Inroducion o Quanum Mechanics End of 19 h Cenury only a few loose ends o wrap up. Led o Relaiviy which you learned abou las quarer Led o Quanum Mechanics (1920 s-30 s and beyond) Behavior of

More information

A DELAY-DEPENDENT STABILITY CRITERIA FOR T-S FUZZY SYSTEM WITH TIME-DELAYS

A DELAY-DEPENDENT STABILITY CRITERIA FOR T-S FUZZY SYSTEM WITH TIME-DELAYS A DELAY-DEPENDENT STABILITY CRITERIA FOR T-S FUZZY SYSTEM WITH TIME-DELAYS Xinping Guan ;1 Fenglei Li Cailian Chen Insiue of Elecrical Engineering, Yanshan Universiy, Qinhuangdao, 066004, China. Deparmen

More information

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality

Matrix Versions of Some Refinements of the Arithmetic-Geometric Mean Inequality Marix Versions of Some Refinemens of he Arihmeic-Geomeric Mean Inequaliy Bao Qi Feng and Andrew Tonge Absrac. We esablish marix versions of refinemens due o Alzer ], Carwrigh and Field 4], and Mercer 5]

More information

System of Linear Differential Equations

System of Linear Differential Equations Sysem of Linear Differenial Equaions In "Ordinary Differenial Equaions" we've learned how o solve a differenial equaion for a variable, such as: y'k5$e K2$x =0 solve DE yx = K 5 2 ek2 x C_C1 2$y''C7$y

More information

Final Spring 2007

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

More information

Single and Double Pendulum Models

Single and Double Pendulum Models Single and Double Pendulum Models Mah 596 Projec Summary Spring 2016 Jarod Har 1 Overview Differen ypes of pendulums are used o model many phenomena in various disciplines. In paricular, single and double

More information

Navneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi

Navneet Saini, Mayank Goyal, Vishal Bansal (2013); Term Project AML310; Indian Institute of Technology Delhi Creep in Viscoelasic Subsances Numerical mehods o calculae he coefficiens of he Prony equaion using creep es daa and Herediary Inegrals Mehod Navnee Saini, Mayank Goyal, Vishal Bansal (23); Term Projec

More information

Position, Velocity, and Acceleration

Position, Velocity, and Acceleration rev 06/2017 Posiion, Velociy, and Acceleraion Equipmen Qy Equipmen Par Number 1 Dynamic Track ME-9493 1 Car ME-9454 1 Fan Accessory ME-9491 1 Moion Sensor II CI-6742A 1 Track Barrier Purpose The purpose

More information

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

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

More information

EXPLICIT TIME INTEGRATORS FOR NONLINEAR DYNAMICS DERIVED FROM THE MIDPOINT RULE

EXPLICIT TIME INTEGRATORS FOR NONLINEAR DYNAMICS DERIVED FROM THE MIDPOINT RULE Version April 30, 2004.Submied o CTU Repors. EXPLICIT TIME INTEGRATORS FOR NONLINEAR DYNAMICS DERIVED FROM THE MIDPOINT RULE Per Krysl Universiy of California, San Diego La Jolla, California 92093-0085,

More information

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum

Lecture 4 Kinetics of a particle Part 3: Impulse and Momentum MEE Engineering Mechanics II Lecure 4 Lecure 4 Kineics of a paricle Par 3: Impulse and Momenum Linear impulse and momenum Saring from he equaion of moion for a paricle of mass m which is subjeced o an

More information

We here collect a few numerical tests, in order to put into evidence the potentialities of HBVMs [4, 6, 7].

We here collect a few numerical tests, in order to put into evidence the potentialities of HBVMs [4, 6, 7]. Chaper Numerical Tess We here collec a few numerical ess, in order o pu ino evidence he poenialiies of HBVMs [4, 6, 7]. Tes problem Le us consider he problem characerized by he polynomial Hamilonian (4.)

More information

Math Final Exam Solutions

Math Final Exam Solutions Mah 246 - Final Exam Soluions Friday, July h, 204 () Find explici soluions and give he inerval of definiion o he following iniial value problems (a) ( + 2 )y + 2y = e, y(0) = 0 Soluion: In normal form,

More information

1 Review of Zero-Sum Games

1 Review of Zero-Sum Games COS 5: heoreical Machine Learning Lecurer: Rob Schapire Lecure #23 Scribe: Eugene Brevdo April 30, 2008 Review of Zero-Sum Games Las ime we inroduced a mahemaical model for wo player zero-sum games. Any

More information

KNOWLEDGE about the mechanical state of a system is

KNOWLEDGE about the mechanical state of a system is JOURNAL OF PHYSICAL AGENTS, VOL 8, NO, JULY 7 Orienaion Esimaion by Means of Exended Kalman Filer, Quaernions, and Chars P Bernal-Polo and H Marínez-Barberá Absrac An orienaion esimaion algorihm is presened

More information

WEEK-3 Recitation PHYS 131. of the projectile s velocity remains constant throughout the motion, since the acceleration a x

WEEK-3 Recitation PHYS 131. of the projectile s velocity remains constant throughout the motion, since the acceleration a x WEEK-3 Reciaion PHYS 131 Ch. 3: FOC 1, 3, 4, 6, 14. Problems 9, 37, 41 & 71 and Ch. 4: FOC 1, 3, 5, 8. Problems 3, 5 & 16. Feb 8, 018 Ch. 3: FOC 1, 3, 4, 6, 14. 1. (a) The horizonal componen of he projecile

More information

Sections 2.2 & 2.3 Limit of a Function and Limit Laws

Sections 2.2 & 2.3 Limit of a Function and Limit Laws Mah 80 www.imeodare.com Secions. &. Limi of a Funcion and Limi Laws In secion. we saw how is arise when we wan o find he angen o a curve or he velociy of an objec. Now we urn our aenion o is in general

More information

Math 334 Fall 2011 Homework 11 Solutions

Math 334 Fall 2011 Homework 11 Solutions Dec. 2, 2 Mah 334 Fall 2 Homework Soluions Basic Problem. Transform he following iniial value problem ino an iniial value problem for a sysem: u + p()u + q() u g(), u() u, u () v. () Soluion. Le v u. Then

More information

Continuous Time. Time-Domain System Analysis. Impulse Response. Impulse Response. Impulse Response. Impulse Response. ( t) + b 0.

Continuous Time. Time-Domain System Analysis. Impulse Response. Impulse Response. Impulse Response. Impulse Response. ( t) + b 0. Time-Domain Sysem Analysis Coninuous Time. J. Robers - All Righs Reserved. Edied by Dr. Rober Akl 1. J. Robers - All Righs Reserved. Edied by Dr. Rober Akl 2 Le a sysem be described by a 2 y ( ) + a 1

More information

Concourse Math Spring 2012 Worked Examples: Matrix Methods for Solving Systems of 1st Order Linear Differential Equations

Concourse Math Spring 2012 Worked Examples: Matrix Methods for Solving Systems of 1st Order Linear Differential Equations Concourse Mah 80 Spring 0 Worked Examples: Marix Mehods for Solving Sysems of s Order Linear Differenial Equaions The Main Idea: Given a sysem of s order linear differenial equaions d x d Ax wih iniial

More information

Augmented Reality II - Kalman Filters - Gudrun Klinker May 25, 2004

Augmented Reality II - Kalman Filters - Gudrun Klinker May 25, 2004 Augmened Realiy II Kalman Filers Gudrun Klinker May 25, 2004 Ouline Moivaion Discree Kalman Filer Modeled Process Compuing Model Parameers Algorihm Exended Kalman Filer Kalman Filer for Sensor Fusion Lieraure

More information

Outline of Topics. Analysis of ODE models with MATLAB. What will we learn from this lecture. Aim of analysis: Why such analysis matters?

Outline of Topics. Analysis of ODE models with MATLAB. What will we learn from this lecture. Aim of analysis: Why such analysis matters? of Topics wih MATLAB Shan He School for Compuaional Science Universi of Birmingham Module 6-3836: Compuaional Modelling wih MATLAB Wha will we learn from his lecure Aim of analsis: Aim of analsis. Some

More information

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

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

More information

Math 315: Linear Algebra Solutions to Assignment 6

Math 315: Linear Algebra Solutions to Assignment 6 Mah 35: Linear Algebra s o Assignmen 6 # Which of he following ses of vecors are bases for R 2? {2,, 3, }, {4,, 7, 8}, {,,, 3}, {3, 9, 4, 2}. Explain your answer. To generae he whole R 2, wo linearly independen

More information

The Contradiction within Equations of Motion with Constant Acceleration

The Contradiction within Equations of Motion with Constant Acceleration The Conradicion wihin Equaions of Moion wih Consan Acceleraion Louai Hassan Elzein Basheir (Daed: July 7, 0 This paper is prepared o demonsrae he violaion of rules of mahemaics in he algebraic derivaion

More information

New effective moduli of isotropic viscoelastic composites. Part I. Theoretical justification

New effective moduli of isotropic viscoelastic composites. Part I. Theoretical justification IOP Conference Series: Maerials Science and Engineering PAPE OPEN ACCESS New effecive moduli of isoropic viscoelasic composies. Par I. Theoreical jusificaion To cie his aricle: A A Sveashkov and A A akurov

More information

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

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

More information

Improved Approximate Solutions for Nonlinear Evolutions Equations in Mathematical Physics Using the Reduced Differential Transform Method

Improved Approximate Solutions for Nonlinear Evolutions Equations in Mathematical Physics Using the Reduced Differential Transform Method Journal of Applied Mahemaics & Bioinformaics, vol., no., 01, 1-14 ISSN: 179-660 (prin), 179-699 (online) Scienpress Ld, 01 Improved Approimae Soluions for Nonlinear Evoluions Equaions in Mahemaical Physics

More information

Design of a control system

Design of a control system SE3 Prof. Davide Manca Poliecnico di Milano Dynamics and Conrol of Chemical Processes Soluion o Lab #3 Design of a conrol sysem Davide Manca Dynamics and Conrol of Chemical Processes Maser Degree in ChemEng

More information

BU Macro BU Macro Fall 2008, Lecture 4

BU Macro BU Macro Fall 2008, Lecture 4 Dynamic Programming BU Macro 2008 Lecure 4 1 Ouline 1. Cerainy opimizaion problem used o illusrae: a. Resricions on exogenous variables b. Value funcion c. Policy funcion d. The Bellman equaion and an

More information