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8/10/2019 443 Lecture 13 http://slidepdf.com/reader/full/443-lecture-13 1/31 Systems Analysis and Control Matthew M. Peet Illinois Institute of Technology Lecture 13: Root Locus Continued

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Page 1: 443 Lecture 13

8/10/2019 443 Lecture 13

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Systems Analysis and Control

Matthew M. Peet

Illinois Institute of Technology

Lecture 13: Root Locus Continued

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Overview

In this Lecture, you will learn:

Review

•  Definition of Root Locus

Points on the Real Axis

•   Symmetry

•  Drawing the Real Axis

What Happens at High Gain?•  The effect of Zeros

•   Asymptotes

M. Peet   Lecture 13:   Control Systems   2 / 31

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Root LocusReview

−3.5 −3 −2.5 −2 −1.5 −1 −0.5 0 0.5 1 1.5−4

−3

−2

−1

0

1

2

3

4

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

Definition 1.

The   Root Locus of  G(s)   is the set of all poles of 

kG(s)

1 + kG(s)

as k

 ranges from  0  to  ∞M. Peet   Lecture 13:   Control Systems   3 / 31

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Root LocusReview

G(s) = (s − z1) · · · (s − zm)

(s − p1) · · · (s − pn)

Im(s)

Re(s)

< s-p1

< s-p2

< s-z

For a point on the root locus:

∠G(s) =

mi=1

∠(s − zi) −

ni=1

∠(s − pi) = −180◦

M. Peet   Lecture 13:   Control Systems   4 / 31

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Root Locus Demo 1

Wiley+ Root Locus Demo 1

M. Peet   Lecture 13:   Control Systems   5 / 31

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Constructing the Root LocusSymmetry

−3.5 −3 −2.5 −2 −1.5 −1 −0.5 0 0.5 1 1.5−4

−3

−2

−1

0

1

2

3

4

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

Our goal is to find all points on the root locus.

•  Our path will be easier by using some basic properties

Symmetry:

•  Complex roots come in pairs:   a ± bı.

•  Points on the root locus are mirrored above/below the real axis

We can divide points on root locus into

•  Points on the real axis

•  Symmetric Pairs off the real axis.M. Peet   Lecture 13:   Control Systems   6 / 31

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Constructing the Root Locus: The Real AxisThe Zeros

Examine a point   s =  a   on the  Real Axis.

•  On the real axis,  s =  a   is a real number.

•  For a point on the Root Locus,

m

i=1

∠(a − zi) −n

i=1

∠(a − pi) = −180◦

Phase Contribution:  The Zeros(a − zi):

Case 1:   zi   is Real

•   If  a > zi0, then  ∠(a − zi) = 0◦

•   If  a < zi, then  ∠(a − zi) = −180◦

Contribution is  0◦ or 180◦!

Im(s)

Re(s)

< s-z=180o

M. Peet   Lecture 13:   Control Systems   7 / 31

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Constructing the Root Locus:The Real AxisThe Zeros

Case 2:   zi   is Complex:  Complex Roots some in pairs.

z1,2  =  b ± cı

•  Zero 1:   a − z1 = a − b + cı

∠(a − z1) = tan−1a − b

c

•  Zero 2:   a − z2 = a − b − cı

∠(a − z2) = tan−1−a − b

c

= −∠(a − z1)

Im(s)

Re(s)

< a-z1

< a-z1= - < a-z

2

a

Therefore, the total contribution to phase is  0◦!

∠(a − z1) + ∠(a − z2) = ∠(a − z1) − ∠(a − z1) = 0◦

M. Peet   Lecture 13:   Control Systems   8 / 31

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Constructing the Root Locus: The Real AxisThe Poles

The Polesmi=1

∠(a − zi) −

ni=1

∠(a − pi) = −180◦

Now lets do the  poles .

Case 1:   pi   is Real

•   If  a − pi  > 0, then  ∠(a − pi) = 0◦

•   If  a − pi  < 0, then∠(a − pi) = −180◦

Contribution is either  0◦ or 180◦!

Im(s)

Re(s)

< s-p=180o

Same as for zeros!!!M. Peet   Lecture 13:   Control Systems   9 / 31

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Constructing the Root LocusThe Real Axis

Case 2:   pi  are Complex:  Complex Roots some in pairs.

z1,2  =  b ± cı

•   Pole 1:   a − p1 = a − b + cı

∠(a − p1) = tan−1a − b

c

•   Pole 2:   a − p2 = a − b − cı

∠(a − p2) = −∠(a − p1)

Im(s)

Re(s)

< a-p1

< a-p1= - < a-p

2

Again, the Total Contribution is  0◦

!M. Peet   Lecture 13:   Control Systems   10 / 31

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Constructing the Root Locus: The Real AxisON-OFF

Summary:  A point on the real axis:   s =  a

•  Complex poles and zeros don’t matter•  Real poles and zeros contribute  0◦ or 180◦

0◦ if the pole/zero is to the left of   a

180◦ if the pole/zero is to the right of   a

The  PHASE  of  G(a)   is

∠G(a) = 180◦ · (# of poles and zeros to the right of  a)

A Simple Rule:

•  If the # of poles and zeros to the right of  a   is EVEN. We are  OFF the root locus.

•  If the # of poles and zeros to the right of  a   is ODD.

We are  ON  the root locus.M. Peet   Lecture 13:   Control Systems   11 / 31

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Constructing the Root LocusExamples

M. Peet   Lecture 13:   Control Systems   12 / 31

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Constructing the Root LocusExamples

−3.5 −3 −2.5 −2 −1.5 −1 −0.5 0 0.5 1 1.5−4

−3

−2

−1

0

1

2

3

4

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

M. Peet   Lecture 13:   Control Systems   13 / 31

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Constructing the Root LocusExamples

G(s) =

  1

s2 −   1

2

−0.8 −0.6 −0.4 −0.2 0 0.2 0.4 0.6 0.8−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

M. Peet   Lecture 13:   Control Systems   14 / 31

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Constructing the Root LocusExamples

The inverted pendulum with some derivative feedback:  K̂ (s) = k(1 + s)

−4 −3.5 −3 −2.5 −2 −1.5 −1 −0.5 0 0.5 1−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

M. Peet   Lecture 13:   Control Systems   15 / 31

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Constructing the Root LocusLarge Gain

Now lets look at what happens when gain increases.

−1.2 −1 −0.8 −0.6 −0.4 −0.2 0 0.2−8

−6

−4

−2

0

2

4

6

8

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A

  x   i  s

Figure:  Suspension Problem

Conclusion:  Stable poles oscillate more.M. Peet   Lecture 13:   Control Systems   16 / 31

C i h R L

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Constructing the Root LocusLarge Gain

G(s) = (s + 3)(s + 4)

(s + 1)(s + 2)

Conclusion:  Nothing Happens.

M. Peet   Lecture 13:   Control Systems   17 / 31

C i h R L

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Constructing the Root LocusLarge Gain

Again, Inverted Pendulum with derivative feedback.

−4 −3.5 −3 −2.5 −2 −1.5 −1 −0.5 0 0.5 1

−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

Conclusion:  Poles get  More Stable.

M. Peet   Lecture 13:   Control Systems   18 / 31

C i h R L

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Constructing the Root LocusLarge Gain

G(s) =  s + 3

s(s + 1)(s + 2)(s + 4)

Conclusion:  Poles Destabilize.

Notice the  Asymptotes.M. Peet   Lecture 13:   Control Systems   19 / 31

C t ti th R t L

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Constructing the Root LocusLarge Gain

So what happens when  k   is large?

Logically, there are  TWO CASES:•  Poles can remain small.

•  Poles can get big.

Lets start with  Small Poles (s < ∞).

G(s) =  n(s)

d(s)•  OL zeros are roots of  n(s) = 0.

•  OL poles are roots of  d(s) = 0.

Now, closed loop:kG(s)

1 + kG(s) =

  kn(s)

d(s) + kn(s)

CL poles are roots of d(s) + kn(s) = 0

−1.2 −1 −0.8 −0.6 −0.4 −0.2 0 0.2−8

−6

−4

−2

0

2

4

6

8

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

−10 −8 −6 −4 −2 0 2 4 6 8

−10

−8

−6

−4

−2

0

2

4

6

8

10

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A

  x   i  s

M. Peet   Lecture 13:   Control Systems   20 / 31

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Constructing the Root Locus

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Constructing the Root LocusAsymptotics

Now consider the other possibility:

Very Large Poles: still satisfy

d(s) + kn(s) = 0

In this case,  d(s)   is not small.

Very Large solutions of 

1 + kG(s)

are called asymptotics.

•  asymptotics increase forever with  k limk→∞s  = ∞

Questions:

•  Do asymptotes exist?

•  Where do they go?

−10 −8 −6 −4 −2 0 2 4 6 8

−10

−8

−6

−4

−2

0

2

4

6

8

10

Root Locus

Real Axis

   I  m  a

  g   i  n  a  r  y   A  x   i  s

M. Peet   Lecture 13:   Control Systems   22 / 31

Constructing the Root Locus

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Constructing the Root LocusAsymptotics

Recall that a point is on the root locusif 

∠G(s) = 180◦

Which means:

mi=1

∠(s − zi) −

ni=1

∠(s − pi) = −180◦

However, when  s → ∞,

All Angles are the Same!!!

Im(s)

Re(s)

< s-p1

< s-z = < s-p1= < s-p

2= < s-p

3

∠(s − z1) = ∠(s − z2) = . . . = ∠(s − zm)

= ∠(s − p1) = ∠(s − p2) = . . . = ∠(s − pn) = ∠∞

M. Peet   Lecture 13:   Control Systems   23 / 31

Constructing the Root Locus

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Constructing the Root LocusAsymptotics

This makes life easier.

•  just solve for one angle,  ∠∞.

∠∞ · (m − n) = 180◦

where

•   m   is the number of OL zeros

•   n is the number of OL poles

Im(s)

Re(s)

< s-p1

< s-z = < s-p1= < s-p

2= < s-p

3

So asymptotics occur at

∠∞ =  1

m − n (180◦ + 360◦l)

for integers   l = 0, 1, 2, · · · .

M. Peet   Lecture 13:   Control Systems   24 / 31

Asymptotes

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AsymptotesCase 1:   n−m   = 0

G(s) = (s + 3)(s + 4)

(s + 1)(s + 2)

Count:  2 zeros, 2 poles.

m − n = 0   ∠∞  = 1

0180◦ = ∞

No Asymptotes.

M. Peet   Lecture 13:   Control Systems   25 / 31

Asymptotes

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AsymptotesCase 2:   n−m   = 1

G(s) =  1

s2

  1

2

K (s) = k(1 + s)

−4 −3.5 −3 −2.5 −2 −1.5 −1 −0.5 0 0.5 1−0.8

−0.6

−0.4

−0.2

0

0.2

0.4

0.6

0.8

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

Count:  1 zeros, 2 poles.

m − n = −1   ∠∞  = −180◦

1 asymptote at  −180◦

.M. Peet   Lecture 13:   Control Systems   26 / 31

Asymptotes

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AsymptotesCase 3:   n−m   = 2

The suspension system.Count:  2 zeros, 4 poles.

m − n = −2

−1.2 −1 −0.8 −0.6 −0.4 −0.2 0 0.2−8

−6

−4

−2

0

2

4

6

8

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

∠∞ = −1

2 (180◦ + 360◦l) = −90◦ − 180◦l = −90◦,−270◦

2 vertical asymptotes at  90◦ and  270◦.

Poles  MAY  destabilize at large gain.

M. Peet   Lecture 13:   Control Systems   27 / 31

Asymptotes

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AsymptotesCase 4:   n−m   = 3

The suspension systemwith integral Feedback.

Count:  2 zeros, 5 poles.

m − n = −3

−3.5 −3 −2.5 −2 −1.5 −1 −0.5 0 0.5 1 1.5−4

−3

−2

−1

0

1

2

3

4

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

∠∞ = −1

3

 (180◦ + 360◦l) = −60◦ − 120◦l = −60◦,−180◦,−300◦

3 asymptotes at  60◦,  180◦ and  300◦.

Poles  WILL  destabilize at large gain.

M. Peet   Lecture 13:   Control Systems   28 / 31

Asymptotes

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AsymptotesCase 5:   n−m   = 4

n(s)   is degree 2,  d(s)   is degree 6.

G(s) =  s2 + s + 1

s6 + 2s5 + 5s4 − s3 + 2s2 + 1

Count:  2 zeros, 6 poles.

m − n = −4

−10 −8 −6 −4 −2 0 2 4 6 8−10

−8

−6

−4

−2

0

2

4

6

8

10

Root Locus

Real Axis

   I  m  a  g   i  n  a  r  y   A  x   i  s

∠∞ = −1

4 (180◦ + 360◦l) = −45◦ − 90◦l = −45◦,−135◦,−225◦,−315◦

4 asymptotes at  45◦,  135◦,  225◦ and  315◦.

Poles  WILL  destabilize at large gain.

M. Peet   Lecture 13:   Control Systems   29 / 31

Asymptotics

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AsymptoticsSummary

Asymptotes depend only on relative number of poles and zeros.

•  Location of poles/zeros doesn’t matter At least not for the angle

One pole goes to each zero.

When there are more poles than zeros:Cases:

•   n − m = 0  - No Asymptotes

•   n − m = 1  - Asymptote at  180◦

•   n − m = 2  - Asymptotes at  ±90◦

•   n − m = 3  - Asymptotes at  180◦,  ±60◦

•   n−m = 4 - Asymptotes at ±45◦ and ±135◦

Im(s)

Re(s)

M. Peet   Lecture 13:   Control Systems   30 / 31

Summary

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Summary

What have we learned today?

Review

•  Definition of Root Locus

Points on the Real Axis

•   Symmetry•  Drawing the Real Axis

What Happens at High Gain?

•  The effect of Zeros

•   Asymptotes

Next Lecture: Centers of Asymptotes, Break Points and Departure

Angles

M. Peet   Lecture 13:   Control Systems   31 / 31