Response to a pure sinusoid

Similar documents
EECE 301 Signals & Systems Prof. Mark Fowler

Systems Analysis and Control

CHAPTER 7 : BODE PLOTS AND GAIN ADJUSTMENTS COMPENSATION

8.1.6 Quadratic pole response: resonance

Systems Analysis and Control

Plan of the Lecture. Goal: wrap up lead and lag control; start looking at frequency response as an alternative methodology for control systems design.

Frequency Response Analysis

Step Response Analysis. Frequency Response, Relation Between Model Descriptions

Dynamic circuits: Frequency domain analysis

R. W. Erickson. Department of Electrical, Computer, and Energy Engineering University of Colorado, Boulder

Chapter 8: Converter Transfer Functions

Frequency methods for the analysis of feedback systems. Lecture 6. Loop analysis of feedback systems. Nyquist approach to study stability

ME 375 EXAM #1 Friday, March 13, 2015 SOLUTION

Homework 7 - Solutions

School of Mechanical Engineering Purdue University

ROOT LOCUS. Consider the system. Root locus presents the poles of the closed-loop system when the gain K changes from 0 to. H(s) H ( s) = ( s)

INTRODUCTION TO DIGITAL CONTROL

Radar Dish. Armature controlled dc motor. Inside. θ r input. Outside. θ D output. θ m. Gearbox. Control Transmitter. Control. θ D.

100 (s + 10) (s + 100) e 0.5s. s 100 (s + 10) (s + 100). G(s) =

Control Systems I. Lecture 9: The Nyquist condition

Chapter 8: Converter Transfer Functions

Frequency domain analysis

16.30/31, Fall 2010 Recitation # 2

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Mechanical Engineering Dynamics and Control II Fall 2007

Notes for ECE-320. Winter by R. Throne

Module 3F2: Systems and Control EXAMPLES PAPER 2 ROOT-LOCUS. Solutions

Overview of Bode Plots Transfer function review Piece-wise linear approximations First-order terms Second-order terms (complex poles & zeros)

Frequency Response Techniques

Systems Analysis and Control

Process Control & Instrumentation (CH 3040)

Transient response via gain adjustment. Consider a unity feedback system, where G(s) = 2. The closed loop transfer function is. s 2 + 2ζωs + ω 2 n

UNIVERSITY OF CALIFORNIA AT BERKELEY College of Engineering Department of Electrical Engineering and Computer Sciences. EE105 Lab Experiments

Frequency Response. Re ve jφ e jωt ( ) where v is the amplitude and φ is the phase of the sinusoidal signal v(t). ve jφ

Systems Analysis and Control

STABILITY. Have looked at modeling dynamic systems using differential equations. and used the Laplace transform to help find step and impulse

r + - FINAL June 12, 2012 MAE 143B Linear Control Prof. M. Krstic

Lecture 6 Classical Control Overview IV. Dr. Radhakant Padhi Asst. Professor Dept. of Aerospace Engineering Indian Institute of Science - Bangalore

Definitions. Decade: A ten-to-one range of frequency. On a log scale, each 10X change in frequency requires the same distance on the scale.

Introduction to Feedback Control

Refinements to Incremental Transistor Model

MAS107 Control Theory Exam Solutions 2008

Delhi Noida Bhopal Hyderabad Jaipur Lucknow Indore Pune Bhubaneswar Kolkata Patna Web: Ph:

Frequency Response of Linear Time Invariant Systems

Review of Linear Time-Invariant Network Analysis

Review: transient and steady-state response; DC gain and the FVT Today s topic: system-modeling diagrams; prototype 2nd-order system

ECE382/ME482 Spring 2005 Homework 6 Solution April 17, (s/2 + 1) s(2s + 1)[(s/8) 2 + (s/20) + 1]

2.010 Fall 2000 Solution of Homework Assignment 1

MAE 143B - Homework 9

Dynamic Response. Assoc. Prof. Enver Tatlicioglu. Department of Electrical & Electronics Engineering Izmir Institute of Technology.

Systems Analysis and Control

Exercise 1 (A Non-minimum Phase System)

EE C128 / ME C134 Fall 2014 HW 8 - Solutions. HW 8 - Solutions

Raktim Bhattacharya. . AERO 422: Active Controls for Aerospace Vehicles. Frequency Response-Design Method

MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Mechanical Engineering Dynamics and Control II Fall K(s +1)(s +2) G(s) =.

Chapter 6 - Solved Problems

Control Systems 2. Lecture 4: Sensitivity function limits. Roy Smith

ELECTRONICS & COMMUNICATIONS DEP. 3rd YEAR, 2010/2011 CONTROL ENGINEERING SHEET 5 Lead-Lag Compensation Techniques

The Frequency-Response

Single-Time-Constant (STC) Circuits This lecture is given as a background that will be needed to determine the frequency response of the amplifiers.

Exercise 1 (A Non-minimum Phase System)

Asymptotic Bode Plot & Lead-Lag Compensator

Control Systems I. Lecture 6: Poles and Zeros. Readings: Emilio Frazzoli. Institute for Dynamic Systems and Control D-MAVT ETH Zürich

The requirements of a plant may be expressed in terms of (a) settling time (b) damping ratio (c) peak overshoot --- in time domain

Studio Exercise Time Response & Frequency Response 1 st -Order Dynamic System RC Low-Pass Filter

Lecture 5: Frequency domain analysis: Nyquist, Bode Diagrams, second order systems, system types

EKT 119 ELECTRIC CIRCUIT II. Chapter 3: Frequency Response of AC Circuit Sem2 2015/2016 Dr. Mohd Rashidi Che Beson

Sinusoidal Forcing of a First-Order Process. / τ

( ) Frequency Response Analysis. Sinusoidal Forcing of a First-Order Process. Chapter 13. ( ) sin ω () (

Control Systems I. Lecture 9: The Nyquist condition

Transfer func+ons, block diagram algebra, and Bode plots. by Ania- Ariadna Bae+ca CDS Caltech 11/05/15

1 Closed Loop Systems

Software Engineering 3DX3. Slides 8: Root Locus Techniques

Course roadmap. Step response for 2nd-order system. Step response for 2nd-order system

APPLICATIONS FOR ROBOTICS

FREQUENCY-RESPONSE DESIGN

16.362: Signals and Systems: 1.0

Lecture 1 Root Locus

Discrete-time Fourier transform (DTFT) representation of DT aperiodic signals Section The (DT) Fourier transform (or spectrum) of x[n] is

Automatic Control 2. Loop shaping. Prof. Alberto Bemporad. University of Trento. Academic year

Systems Analysis and Control

Frequency Response part 2 (I&N Chap 12)

Raktim Bhattacharya. . AERO 632: Design of Advance Flight Control System. Preliminaries

Poles and Zeros and Transfer Functions

Systems Analysis and Control

Control of Manufacturing Processes

Antiderivatives. Definition A function, F, is said to be an antiderivative of a function, f, on an interval, I, if. F x f x for all x I.

An Internal Stability Example

Steady State Frequency Response Using Bode Plots

2.004 Dynamics and Control II Spring 2008

CHEE 319 Tutorial 3 Solutions. 1. Using partial fraction expansions, find the causal function f whose Laplace transform. F (s) F (s) = C 1 s + C 2

CHAPTER # 9 ROOT LOCUS ANALYSES

Stability & Compensation

Basic Electronics. Introductory Lecture Course for. Technology and Instrumentation in Particle Physics Chicago, Illinois June 9-14, 2011

Lecture 15 Nyquist Criterion and Diagram

Dr Ian R. Manchester Dr Ian R. Manchester AMME 3500 : Review

9.5 The Transfer Function

EE3CL4: Introduction to Linear Control Systems

Asymptote. 2 Problems 2 Methods

New Mexico State University Klipsch School of Electrical Engineering EE312 - Signals and Systems I Fall 2015 Final Exam

Solution: K m = R 1 = 10. From the original circuit, Z L1 = jωl 1 = j10 Ω. For the scaled circuit, L 1 = jk m ωl 1 = j10 10 = j100 Ω, Z L

Transcription:

Harvard University Division of Engineering and Applied Sciences ES 145/215 - INTRODUCTION TO SYSTEMS ANALYSIS WITH PHYSIOLOGICAL APPLICATIONS Fall Lecture 14: The Bode Plot Response to a pure sinusoid We previously stated that if an input to a linear system is sinusoidal (u(t) =Asin(ω t)), then the output would be a sine wave at the same frequency shifted in phase and changed in magnitude. If we have: Y (s) U (s) = G(s) then the output is: y(t) = jg( jω )jasin(ω t + φ) where: jg( jω )j = q [Re(G( jω ))] 2 +[Im(G( jω ))] 2 and: φ = tan 1 Im(G( jω )) Re(G( jω )) Note that the magnitude and phase shift depend on the frequency at which you are driving the system. Example. Consider the following system: s 2 + 2s + 1 with an input u(t) =5sint. We then can write: y(t) = jg( j)j5sin(t + φ) The transfer function G(s) evaluated at s = jω = j is: G( j) = j 2 + 2 j + 1 = 1 + 2 j 1 = 2 j 2 j 2 j = 5 j

ES145/215 - Lecture 14 2 Figure 1: The Complex Plane Imag -9 o Real -5j The quantity 5 j has magnitude 5 and angle 9 ffi. To find the magnitude, we can write: jg( j)j = p 2 + 5 2 = 5 The angle of a negative purely real number is 9 ffi or π 2 rad/sec. We can easily see this in the complex plane, as shown in Figure 1. The solution then takes the form: y(t) = 5 5sin t π = 25sin t π 2 2 It is easy to see the effect of the system on this pure sinusoidal input graphically, as shown in Figure 2. Figure 2: System Input and Output 3 Input (solid) and output (dashed) signals 3 5 15 25 3 Time (seconds) Note that if u(t) =5sint, then ω = 1 rad/sec, so the frequency in cycles/sec is f = ω =2π = 1=2π cycles/sec. This gives a period of T = 2π ß 6 sec. The General Case In general, the above discussion is useful not because we typically experience purely sinusoidal inputs in real life. The utility lies in the linearity of the relationship. From Fourier analysis, we

ES145/215 - Lecture 14 3 know that any signal can be written as a linear combination of sine waves at different frequencies, magnitudes, and phases: u(t) = A sin(ω t + ψ )+A 1 sin(ω 1 t + ψ 1 )+::: Because the system is linear, the output is equal to the sum of the outputs as if you had applied each one of these sine waves individually. The output of the system to an input of this type is: y(t) = jg( jω )jsin(ω t + ψ + φ )+jg( jω 1 )jsin(ω 1 t + ψ 1 + φ 1 )+::: So by knowing jg( jω)j and G( jω) 8ω, we can completely describe the output to any arbitrary input. For any transfer function, we can do this by simply evaluating the magnitude and phase over the entire frequency range. It s a very straight-forward thing to do using a computer, but we will find out that some very simple tools are pretty useful in sketching these relationships out by hand and will give you some insight as to the dynamics of the system. The type of plot that we will be generating is called a Bode plot, which will now be described. The Bode Plot The Bode plot is a plot of the magnitude and phase of a transfer function, as a function of frequency. We can write any transfer function in the following form: N(s) K(s D(s) = + z 1)(s + z 2 ) :::(s + z m ) (s + p 1 )(s + p 2 ) :::(s + p n ) e T ds = G 1 (s)g 2 (s) :::G N (s) where each of the G i (s) is of a very simple form. Taking a look at the magnitude, we have: jg( jω)j = jg 1 ( jω)g 2 ( jω) :::G N ( jω)j = jg 1 ( jω)jjg 2 ( jω)j :::jg N ( jω)j We often look at the log of the magnitude in decibels, which is defined as: jg( jω)j db = log jg( jω)j = [log jg 1 ( jω)j + log jg 2 ( jω)j + :::+ log jg N ( jω)j] = log jg 1 ( jω)j + log jg 2 ( jω)j + :::+ log jg N ( jω)j = jg 1 ( jω)j db + jg 2 ( jω)j db + :::+ jg N ( jω)j db So the utility is that the product turned into a sum. We ll see why this is handy shortly. Similarly, with the phase we have: G( jω) = G 1 ( jω)+ G 2 ( jω)+:::+ G N ( jω) So with both the magnitude and the phase angle, the different components sum. We can therefore look at each component, draw the magnitude and phase as a function of the frequency ω, and add.

ES145/215 - Lecture 14 4 Example. Consider the following system: (s + z 1 )(s + z 2 ) s(s + p 1 )(s 2 + 2ζ s + ω 2 n )e T ds We can easily rearrange this: K(1 + s z 1 )(1 + s z 2 ) s(1 + s p 1 )(1 + 2ζ s + s2 ω 2 ) n e T ds where K;z 1 ;z 2 ; p 1 ;ζ; ;T d 2 R. The magnitude is: jg( jω)j db = log jg( jω)j The phase angle can be computed as: = log jkj + log fi 1 + jω z 1 fi + log fi 1 + jω z 2 fi log j jωj G( jω) = K + log fi 1 jω + p 1 fi log 2ζ jω fi1 + 2ζ jω 1 + 1 + jω z 1 + + ( jω) 2 ωt d + ( jω) 2 ω fi 2 + n 1 jω + ( jω) 1 jω + z 2 p 1 Bode Plot Elements So in general, we can break things down into these simple types of components no matter how complicated the transfer function is. The types of elements break down into the following: ffl Constant gain K 2 R ffl Poles/zeros at the origin: s or 1 s ffl Poles/zeros real at p i or z i : 1 + s z i or 1 1+ s p i ffl Complex conjugate pair of poles/zeros: 1 + 2ζ s + s2 or ω 2 n ffl Pure time delay: e T ds 1 1+ 2ζ ωn s+ s2 ω 2 n Let s look at the properties of each type.

ES145/215 - Lecture 14 5 Constant K. Suppose we have a constant K 2 R. The magnitude can be written: The phase angle depends on the sign of K: jkj db = log jkj = constant 8ω K = if k> = 18 ffi else As an example, consider 1. Let the input u(t) =Asin(ω t). The output can then be written as: y(t) = jg( jω )jasin(ω t + φ) = Asin(ω t π) So the input and the output are completely out of phase with each other. Figure 3 shows the Bode plot for a constant gain of K =. Figure 3: Constant Gain Element K = Constant Gain 21.5 19.5 19 1.5.5 1.1 1 Pole/Zero at the Origin. Suppose that we have a pole at the origin: The magnitude is: 1 s jg( jω)j db = log fi 1 jωfi = log j jωj = log ω This means that jg( jω)j db vs. log ω is a straight line with a slope of db/log unit, which is often called db/decade. The magnitude is db at frequency ω = 1. The phase angle is just the angle associated with jω, which is 9 ffi : < G( jω) = 9 ffi The same argument can be made for a zero at the origin s, except that the magnitude will be jg( jω)j db =+log ω, having a positive slope of db/decade and passing through db at ω = 1. Figure 4 shows the Bode plot for a pole and a zero at the origin.

ES145/215 - Lecture 14 6 Figure 4: Pole/Zero at Origin s (solid), 1/s (dashed) 4 4 5 5.1 1 Real Pole/Zero. Suppose we have a zero at z i 2 R: Evaluating at s = jω gives us: The magnitude is: 1 + s z i G( jω) = 1 + jω z i jg( jω)j db = log jg( jω)j = log s1 2 + ω z i 2 Of course we could plot this on the computer very easily, but to get a handle on it first, let s look at the asymptotic properties. For small ω (ω=z i fi 1) we have: For large ω (ω=z i fl 1) we have: jg( jω)j db ß log p1 2 + 2 = db jg( jω)j db ß log s ω 2 z 2 i = log ω z i = log ω log z i This is a straight line, with slope +db/decade, and is db at ω = z i. The straight-line approximation starts with an initial magnitude of db, constant until ω = z i, at which point it breaks upward at +db/decade. The phase angle can be expressed as: G( jω) = 1 jω + = tan 1 ω=zi z i 1

ES145/215 - Lecture 14 7 Again using the asymptotic properties, we have for small ω (ω=z i fi 1): and for large ω (ω=z i fl 1) we have: G( jω) ß π G( jω) ß 9 ffi or 2 The straight-line approximation of the phase has an initial phase of ffi, breaks upward one decade before z i (or at :1z i ) at a slope of 45 ffi /decade, and levels off at one decade after z i (or at z i ). Similar arguments can be made for a pole at p i, except that the magnitude plot for large ω asymptotes to a straight line with a db/decade slope, and the phase angle for large ω asymptotes to 9 ffi or π 2. Figure 5 shows the Bode plot for a real pole (p = 3) and a real zero (z = 3). Figure 5: Real Pole/Zero (1+s/z) (solid), 1/(1 + s/p) (dashed) 3 3 5 5.1 1 Complex Poles/Zeros. Suppose that we cannot factor an element down to first order terms with real roots. We can at least factor to the corresponding quadratic, and the result is a complex conjugate pair of roots. Suppose we have the following: 1 1 +(2ζ= )s +(1=ω 2 n )s2 Evaluating at s = jω we have: G( jω) = = 1 1 +(2ζ= ) jω +(1=ω 2 n )( jω)2 1 [1 ω 2 =ω 2 n ]+[2ζω=] j We can again look at the asymptotic properties. For small ω, we have: jg( jω)j db ß log q(1 ) 2 + 2 = log 1 =

ES145/215 - Lecture 14 8 For large ω, wehave: jg( jω)j db ß log s ω 4 = log ω 2 ω 2 n ω 4 n = 4log ω The resulting Bode plot for a system with = 5 and different ζ s is shown in Figure 6. Figure 6: Complex Poles 1/(1+(2*ζ/ )s + (1/ 2 )s 2 ), ζ = 1.5 (solid) and ζ =.1 (dashed) 4 4 5 15.1.1 1 Pure Time Delay. Suppose we have a pure time delay as one of our elements. In this Laplace domain, this shows up as: e T ds where T d is the pure delay in seconds. Evaluating at s = jω we obtain: The corresponding magnitude is: and the corresponding phase angle is: G( jω) = e T d jω jg( jω)j db = log 1 = G( jω) = T d ω So the magnitude plot is a constant for all frequencies, and the phase is a straight line with slope T d, which passes through T d degrees at ω = 1. Putting it all together So we have learned a bit about the individual components, but how do we put it all together. This is best illustrated with an example. Suppose we have the following system: (s + ) s(s + 2)(s + 5)

ES145/215 - Lecture 14 9 The first step is to put it in the following form: = (1 + s=) s(1 + s=2)(1 + s=5) 2 5 (1 + s=) s(1 + s=2)(1 + s=5) Evaluating at s = jω we have: G( jω) = (1 + jω=) jω(1 + jω=2)(1 + jω=5) Each of the elements of the transfer function are in a form that we recognize. We simply plot each one on the same graph. Let s first consider the magnitude plot. The gain of has a constant magnitude at db. The zero at has zero magnitude until rad/sec, where it breaks upwards at +db/decade. The pole at the origin has a slope of db/decade, passing through db at 1rad/sec. The pole at 2 has a magnitude of db until 2rad/sec, at which point it breaks downward at db/decade. The pole at 5 has a magnitude of db until 5rad/sec, at which point it breaks downward at db/decade. We can simply add up all of these components to get the total magnitude in decibels. For the phase, we do exactly the same thing. The gain of contributes nothing to the phase. The zero at initially has a phase of ffi, breaks upward at 45 ffi /decade at 1rad/sec, and flattens back out at rad/sec at 9 ffi. The pole at the origin contributes a constant 9 ffi over all frequencies. The pole at 2 initially has a phase of ffi, breaks downward at 45 ffi /decade at :2rad/sec, and flattens back out at rad/sec at 9 ffi. The pole at 5 initially has a phase of ffi, breaks downward at 45 ffi /decade at :5rad/sec, and flattens back out at 5rad/sec at 9 ffi. As with the magnitude plot, we simply add these up to get the total phase profile. The resulting Bode plots of the components are shown in Figure 7. Figure 7: Components of the Bode Example Bode Diagrams constant pole at origin zero at pole at 5 3 4 5 pole at 2 zero at 5 pole at origin pole at 2 pole at 5 constant.1 1 If we combine all of the components, the resulting Bode plot is shown in Figure 8.

ES145/215 - Lecture 14 Figure 8: Composite of the Bode Example Composite Diagram from Elements 6 4 4 6 1 14 16 18.1.1 1