Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR...

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EE C128 / ME C134 – Feedback Control Systems Lecture – Chapter 10 – Frequency Response Techniques Alexandre Bayen Department of Electrical Engineering & Computer Science University of California Berkeley September 10, 2013 Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 1 / 64 Lecture abstract Topics covered in this presentation I Advantages of FR techniques over RL I Define FR I Define Bode & Nyquist plots I Relation between poles & zeros to Bode plots (slope, etc.) I Features of 1 st -&2 nd -order system Bode plots I Define Nyquist criterion I Method of dealing with OL poles & zeros on imaginary axis I Simple method of dealing with OL stable & unstable systems I Determining gain & phase margins from Bode & Nyquist plots I Define static error constants I Determining static error constants from Bode & Nyquist plots I Determining TF from experimental FR data Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 2 / 64 Chapter outline 1 10 Frequency response techniques 10.1 Introduction 10.2 Asymptotic approximations: Bode plots 10.3 Introduction to Nyquist criterion 10.4 Sketching the Nyquist diagram 10.5 Stability via the Nyquist diagram 10.6 Gain margin and phase margin via the Nyquist diagram 10.7 Stability, gain margin, and phase margin via Bode plots 10.8 Relation between closed-loop transient and closed-loop frequency responses 10.9 Relation between closed- and open-loop frequency responses 10.10 Relation between closed-loop transient and open-loop frequency responses 10.11 Steady-state error characteristics from frequency response 10.12 System with time delay 10.13 Obtaining transfer functions experimentally Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 3 / 64 10 FR techniques 10.1 Intro 1 10 Frequency response techniques 10.1 Introduction 10.2 Asymptotic approximations: Bode plots 10.3 Introduction to Nyquist criterion 10.4 Sketching the Nyquist diagram 10.5 Stability via the Nyquist diagram 10.6 Gain margin and phase margin via the Nyquist diagram 10.7 Stability, gain margin, and phase margin via Bode plots 10.8 Relation between closed-loop transient and closed-loop frequency responses 10.9 Relation between closed- and open-loop frequency responses 10.10 Relation between closed-loop transient and open-loop frequency responses 10.11 Steady-state error characteristics from frequency response 10.12 System with time delay 10.13 Obtaining transfer functions experimentally Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 4 / 64 10 FR techniques 10.1 Intro Advantages of frequency response (FR) methods, [1, p. 534] In the following situations I When modeling TFs from physical data I When designing lead compensators to meet a steady-state error requirements I When finding the stability of NL systems I In settling ambiguities when sketching a root locus Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 5 / 64 10 FR techniques 10.1 Intro The concept of FR, [1, p. 535] I At steady-state, sinusoidal inputs to a linear system generate sinusoidal responses of the same frequency with dierent amplitudes and phase angle from the input, each of which are a function of frequency. I Phasor – complex representation of a sinusoid I ||G(!)|| – amplitude I \G(!) – phase angle I M cos(!t + φ) ... M\φ Figure: Sinusoidal FR: a. system; b. TF; c. IO waveforms Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 6 / 64

Transcript of Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR...

Page 1: Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR techniques 10.2 Asymptotic approximations: Bode plots Simple Bode plots, [1, p. 542]

EE C128 / ME C134 – Feedback Control SystemsLecture – Chapter 10 – Frequency Response Techniques

Alexandre Bayen

Department of Electrical Engineering & Computer ScienceUniversity of California Berkeley

September 10, 2013

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 1 / 64

Lecture abstract

Topics covered in this presentation

I Advantages of FR techniques over RL

I Define FR

I Define Bode & Nyquist plots

I Relation between poles & zeros to Bode plots (slope, etc.)

I Features of 1st- & 2nd-order system Bode plots

I Define Nyquist criterion

I Method of dealing with OL poles & zeros on imaginary axis

I Simple method of dealing with OL stable & unstable systems

I Determining gain & phase margins from Bode & Nyquist plots

I Define static error constants

I Determining static error constants from Bode & Nyquist plots

I Determining TF from experimental FR data

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 2 / 64

Chapter outline

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 3 / 64

10 FR techniques 10.1 Intro

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 4 / 64

10 FR techniques 10.1 Intro

Advantages of frequency response (FR) methods, [1, p.534]

In the following situations

I When modeling TFs from physical data

I When designing lead compensators to meet a steady-state errorrequirements

I When finding the stability of NL systems

I In settling ambiguities when sketching a root locus

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 5 / 64

10 FR techniques 10.1 Intro

The concept of FR, [1, p. 535]

I At steady-state, sinusoidalinputs to a linear systemgenerate sinusoidal responsesof the same frequency withdi↵erent amplitudes and phaseangle from the input, each ofwhich are a function offrequency.

I Phasor – complexrepresentation of a sinusoid

I ||G(!)|| – amplitudeI \G(!) – phase angleI M cos(!t+ �) ... M\� Figure: Sinusoidal FR: a. system; b.

TF; c. IO waveforms

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 6 / 64

Page 2: Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR techniques 10.2 Asymptotic approximations: Bode plots Simple Bode plots, [1, p. 542]

10 FR techniques 10.1 Intro

The concept of FR, [1, p. 535]

I Steady-state output sinusoid

Mo(!)\�o(!)

= Mi(!)M(!)\(�i(!) + �(!))

I Magnitude FR

M(!) =Mo(!)

Mi(!)

I Phase FR

�(!) = �o(!)� �i(!)

I FRM(!)\�(!)

Figure: Sinusoidal FR: a. system; b.TF; c. IO waveforms

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 7 / 64

10 FR techniques 10.1 Intro

Analytical expressions for FR, [1, p. 536]

I General input sinusoid

r(t) = A cos(!t) +B sin(!t)

=

pA2

+B2cos

�!t� tan

�1�BA

��

I Input phasor formsI Polar, Mi\�i

Mi =

pA2

+B2

�i = � tan

�1�BA

I Rectangular, A� jBI Euler’s, Miej�i

Figure: System withsinusoidal input

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 8 / 64

10 FR techniques 10.1 Intro

Analytical expressions for FR, [1, p. 536]

I Forced response

C(s) =As+B!

s2 + !2G(s)

I Steady-state forced response after partial fraction expansion

Css(s) =MiMG

2 e�j(�i��G)

s+ j!+

MiMG2 ej(�i��G)

s� j!

where MG = ||G(j!)|| and �G = \G(j!)I Time-domain response

c(t) = MiMG cos(!t+ �i + �G)

I Time-domain response in phasor form

Mo\�o = (Mi\�i)(MG\�G)

I FR of systemG(j!) = G(s)|s!j!

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 9 / 64

10 FR techniques 10.2 Asymptotic approximations: Bode plots

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 10 / 64

10 FR techniques 10.2 Asymptotic approximations: Bode plots

History interlude

History (Hendrik Wade Bode)

I 1905 – 1982

I American engineer

I 1930s – Inventor of Bode plots,gain margin, & phase margin

I 1944 – WWII anti-aircraft(including V-1 flying bombs)systems

I 1947 – Cold War anti-ballisticmissiles

I 1957 – Served on NACA (nowNASA) with Wernher vonBraun (inventor of V-1 flyingbombs & V-2 rockets)

Figure: Hendrik Wade Bode

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10 FR techniques 10.2 Asymptotic approximations: Bode plots

General Bode plots, [1, p. 540]

G(j!) = MG(!)\�G(!)

I Separate magnitude and phase plots as a function of frequencyI Magnitude – decibels (dB) vs. log(!), where dB = 20 log(M)

I Phase – phase angle vs. log(!)

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 12 / 64

Page 3: Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR techniques 10.2 Asymptotic approximations: Bode plots Simple Bode plots, [1, p. 542]

10 FR techniques 10.2 Asymptotic approximations: Bode plots

Bode plots approximations, [1, p. 542]

I TFG(s) = s+ a

I Low frequencies

G(j!) ⇡ a\0�

I High frequencies

G(j!) ⇡ !\90�

I Asymptotes – straight-lineapproximations

I Low-frequencyI Break frequencyI High-frequency

Figure: Bode plots of s+ a: a.magnitude plot; b. phase plot

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 13 / 64

10 FR techniques 10.2 Asymptotic approximations: Bode plots

Simple Bode plots, [1, p. 542]

0

10

20

30

40

Ma

gn

itud

e (

dB

)

10−2

10−1

100

101

102

0

30

60

90

Ph

ase

(d

eg

)

Frequency (Hz)

Figure: Bode plot of s+aa

−40

−30

−20

−10

0

Ma

gn

itud

e (

dB

)

10−2

10−1

100

101

102

−90

−60

−30

0

Ph

ase

(d

eg

)

Frequency (Hz)

Figure: Bode plot of as+a

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 14 / 64

10 FR techniques 10.2 Asymptotic approximations: Bode plots

Simple Bode plots, [1, p. 545]

0

10

20

30

Ma

gn

itud

e (

dB

)

10−1

100

101

8989.289.489.689.8

9090.290.490.690.8

91

Ph

ase

(d

eg

)

Frequency (Hz)

Figure: Bode plot of s

−30

−20

−10

0

Ma

gn

itud

e (

dB

)

10−1

100

101

−91−90.8−90.6−90.4−90.2

−90−89.8−89.6−89.4−89.2

−89

Ph

ase

(d

eg

)

Frequency (Hz)

Figure: Bode plot of 1s

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 15 / 64

10 FR techniques 10.2 Asymptotic approximations: Bode plots

Simple Bode plots, [1, p. 549]

0

20

40

60

80

Ma

gn

itud

e (

dB

)

10−2

10−1

100

101

102

0

45

90

135

180

Ph

ase

(d

eg

)

Frequency (Hz)

Figure: Bode plot of s2+2⇣!ns+!2n

!2n

−80

−60

−40

−20

0

Ma

gn

itud

e (

dB

)

10−2

10−1

100

101

102

−180

−135

−90

−45

0

Ph

ase

(d

eg

)

Frequency (Hz)

Figure: Bode plot of !2n

s2+2⇣!ns+!2n

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 16 / 64

10 FR techniques 10.2 Asymptotic approximations: Bode plots

Detailed 2nd-order Bode plots, [1, p. 550]

Figure: Bode plot of s2+2⇣!ns+!2n

!2n

Figure: Bode plot of !2n

s2+2⇣!ns+!2n

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 17 / 64

10 FR techniques 10.3 Intro to Nyquist criterion

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 18 / 64

Page 4: Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR techniques 10.2 Asymptotic approximations: Bode plots Simple Bode plots, [1, p. 542]

10 FR techniques 10.3 Intro to Nyquist criterion

History interlude

History (Harry Theodor Nyquist)

I 1889 – 1976

I American engineer

I 1917 – 1934 AT&T

I 1934 – 1954 Bell TelephoneLabs

I 1924 – Nyquist-Shannonsampling theorem

I 1926 – Johnson–Nyquist noise

I 1932 – Nyquist stabilitycriterion Figure: Harry Theodor Nyquist

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 19 / 64

10 FR techniques 10.3 Intro to Nyquist criterion

Introduction, [1, p. 559]

I Relates the stability of a CLsystem to the OL FR and theOL poles and zeros

I# CL poles in RHP

I Provides information on thetransient response andsteady-state error

Figure: CL control system

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 20 / 64

10 FR techniques 10.3 Intro to Nyquist criterion

Derivation concepts, [1, p. 560]

G(s) =NG

DGand H(s) =

NH

DH

G(s)H(s) =NGHG

DGDH

F (s) = 1 +G(s)H(s) =DGDH +NGNH

DGDH

T (s) =G(s)

1 +G(s)H(s)=

NGNH

DGDH +NGNH

I Poles of 1 +G(s)H(s) are the same as the poles of the OL system,G(s)H(s)

I Zeros of 1 +G(s)H(s) are the same as the poles of the CL system,T (s)

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 21 / 64

10 FR techniques 10.3 Intro to Nyquist criterion

Derivation concepts, [1, p. 560]

I Map – function

I Contour – collection of points

I For our particular scenario,assume

F (s) =(s� z1)(s� z2)...

(s� p1)(s� p2)...

and a clockwise direction formapping the points on thecontour A

Figure: Mapping contour A throughfunction F (s) to contour B

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 22 / 64

10 FR techniques 10.3 Intro to Nyquist criterion

Derivation concepts, [1, p. 561]

I If F (s) has only zeros or onlypoles that are not encircled bythe contour then contour Bmaps in a clockwise direction

Figure: Contour mapping – withoutencirclements

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 23 / 64

10 FR techniques 10.3 Intro to Nyquist criterion

Derivation concepts, [1, p. 561]

I If F (s) has only zeros that areencircled by the contour thencontour B maps in a clockwisedirection

I If F (s) has only poles that areencircled by the contour thencontour B maps in acounterclockwise direction

I If F (s) has only poles or onlyzeros that are encircled by thecontour then contour B mapdoes encircle the origin

Figure: Contour mapping – withencirclements

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 24 / 64

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10 FR techniques 10.3 Intro to Nyquist criterion

Derivation concepts, [1, p. 562]

I If F (s) has #poles

= #

zeros

that are encircled by thecontour then contour B mapdoes not encircle the origin Figure: Contour mapping – with

encirclements

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 25 / 64

10 FR techniques 10.3 Intro to Nyquist criterion

Derivation concepts, [1, p. 562]

I Each pole or zero of1 +G(s)H(s) whose vectorundergoes a complete rotationof contour A must yield achange of 360� in theresultant, R, or a completerotation of contour B

I A zero inside a CW contour Ayields a CW rotation ofcontour B

I A pole inside a CW contour Ayields a CCW rotation ofcontour B

I N = P � ZI N , # CCW rotations of

contour B about the originI P , # poles of 1 +G(s)H(s)

inside contour AI Z, # zeros of 1 +G(s)H(s)

inside contour A

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 26 / 64

10 FR techniques 10.3 Intro to Nyquist criterion

Derivation concepts, [1, p. 562]

Adjustment – extend the contour A to includethe entire RHP

I Z, # RHP CL polesI CL stability!

I P , # RHP OL polesI Easy

I N , # CCW rotations of contour B aboutorigin

I Di�cult

Adjustment – map G(s)H(s) instead of1 +G(s)H(s)

I N , # CCW rotations of contour B about�1

I Less di�cult

Figure: Contour enclosingRHP to determinestability

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 27 / 64

10 FR techniques 10.3 Intro to Nyquist criterion

Definition, [1, p. 563]

Definition (Nyquist stability criterion)

I If a contour, A, that encircles the entire RHP is mapped through theOL system, G(s)H(s), then the # of RHP CL poles, Z, equals the #of RHP OL poles, P , minus the # of CCW revolutions, N , around�1 of the mapping.

Z = P �N

I The mapping is called the Nyquist diagram of G(s)H(s).

I FR technique because the mapping of points on the positive j!-axisthrough G(s)H(s) is the same as substituting s = j! into G(s)H(s)to form the FR function G(j!)H(j!).

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 28 / 64

10 FR techniques 10.3 Intro to Nyquist criterion

Applying the Nyquist stability criterion, [1, p. 563]

I No RHP CL polesI P = 0

I N = 0

I Z = 0

I CL system is stable

I 2 RHP CL polesI P = 0

I N = �2

I Z = 2

I CL system is unstable Figure: Mapping examples – withencirclement: a. contour does notenclose CL poles; b. contour doesenclose CL poles

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 29 / 64

10 FR techniques 10.4 Sketching the Nyquist diagram

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 30 / 64

Page 6: Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR techniques 10.2 Asymptotic approximations: Bode plots Simple Bode plots, [1, p. 542]

10 FR techniques 10.4 Sketching the Nyquist diagram

Method

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 31 / 64

10 FR techniques 10.4 Sketching the Nyquist diagram

Example, [1, p. 564]

Example (general)

I G(s) = 500(s+10)(s+3)(s+1)

Figure: Vector evaluation of theNyquist diagram: a. vectors on contourat low frequency, b. vectors on contouraround 1; c. Nyquist diagram

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 32 / 64

10 FR techniques 10.4 Sketching the Nyquist diagram

Example, [1, p. 567]

Example (poles on contour)

I G(s) = s+2s2

Figure: a. contour, b. Nyquist diagram

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 33 / 64

10 FR techniques 10.5 Stability via the Nyquist diagram

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 34 / 64

10 FR techniques 10.5 Stability via the Nyquist diagram

Example, [1, p. 569]

Example (general)

I G(s) = K(s+3)(s+5)(s�2)(s�4)

Figure: a. system; b. contour, c.Nyquist diagram

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 35 / 64

10 FR techniques 10.5 Stability via the Nyquist diagram

Example, [1, p. 570]

Example (general)

I G(s) = Ks(s+3)(s+5)

Figure: a. contour; b. Nyquist diagram

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 36 / 64

Page 7: Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR techniques 10.2 Asymptotic approximations: Bode plots Simple Bode plots, [1, p. 542]

10 FR techniques 10.5 Stability via the Nyquist diagram

Stability via mapping only the positive j!-axis, [1, p. 571]

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 37 / 64

10 FR techniques 10.6 Gain margin & phase margin via the Nyquist diagram

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 38 / 64

10 FR techniques 10.6 Gain margin & phase margin via the Nyquist diagram

Definitions, [1, p. 574]

Two quantitative measures of howstable a system is

I Gain margin, GM – the changein OL gain, expressed in dB,required at 180� of phase shiftto make the CL systemunstable

I Phase margin, �M – thechange in OL phase shiftrequired at unity gain to makethe CL system unstable

Figure: Nyquist diagram showing gainand phase margins

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 39 / 64

10 FR techniques 10.7 Stability, gain margin, & phase margin via Bode plots

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 40 / 64

10 FR techniques 10.7 Stability, gain margin, & phase margin via Bode plots

Stability via Bode plots, [1, p. 576]

Method

I Draw a Bode log-magnitude plot

I Determine the range of the gain that ensures that the magnitude isless than 0 dB (unity gain) at that frequency where the phase is±180�

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 41 / 64

10 FR techniques 10.7 Stability, gain margin, & phase margin via Bode plots

Example, [1, p. 577]

Example (general)

I Use Bode plots to determinethe range of K within whichthe unity FB system is stable.

G(s) =k

(s+ 2)(s+ 4)(s+ 5)

Figure: Bode log-magnitude and phasediagrams

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 42 / 64

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10 FR techniques 10.7 Stability, gain margin, & phase margin via Bode plots

Gain & phase margin via Bode plots, [1, p. 578]

MethodI Gain margin

I Phase plot !!GM = !|�=180�

I At !GM , magnitude plot !gain margin, GM , which isthe gain required to raise themagnitude curve to 0 dB

I Phase marginI Magnitude plot !

!�M = !|G=0dBI At !�M , phase plot ! phase

margin, �M , which is thedi↵erence between the phasevalue and 180�

Figure: Gain and phase margins on theBode diagrams

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 43 / 64

10 FR techniques 10.7 Stability, gain margin, & phase margin via Bode plots

Example, [1, p. 579]

Example (general)

I If K = 200, find the gain andphase margins.

G(s) =k

(s+ 2)(s+ 4)(s+ 5)

Figure: Bode log-magnitude and phasediagrams

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 44 / 64

10 FR techniques 10.8 Relation between CL transient & CL FRs

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 45 / 64

10 FR techniques 10.8 Relation between CL transient & CL FRs

Damping ratio & CL FR, [1, p. 580]

Peak magnitude of the CL FR

Mp =1

2⇣p1� ⇣2

Frequency of the peak magnitude

!p = !n

p1� 2⇣2

Figure: 2nd-order CL system

Figure: CL FR peak vs. %OS for a 2pole system

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10 FR techniques 10.8 Relation between CL transient & CL FRs

Response speed & CL FR, [1, p. 581]

I Bandwidth of a 2-pole system

!BW = !n

q(1� 2⇣2) +

p4⇣4 � 4⇣2 + 2

I !n–Ts relation

!n =

4

Ts⇣

I !n–Tp relation

!n =

Tp

p1� ⇣2

I !n–Tr relationI Found using look-up table

Figure: Representativelog-magnitude plot

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10 FR techniques 10.8 Relation between CL transient & CL FRs

Response speed & CL FR, [1, p. 582]

Figure: Normalized bandwidth vs. damping ratio for:a. Ts, b. Tp; c. Tr

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Page 9: Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR techniques 10.2 Asymptotic approximations: Bode plots Simple Bode plots, [1, p. 542]

10 FR techniques 10.9 Relation between CL & OL FRs

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 49 / 64

10 FR techniques 10.9 Relation between CL & OL FRs

Constant M circles & constant N circles, [1, p. 583]

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10 FR techniques 10.10 Relation between CL transient & OL FRs

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 51 / 64

10 FR techniques 10.10 Relation between CL transient & OL FRs

Damping ratio from M circles, [1, p. 589]

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10 FR techniques 10.10 Relation between CL transient & OL FRs

Damping ratio from phase margin, [1, p. 589]

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10 FR techniques 10.10 Relation between CL transient & OL FRs

Response speed from OL FR, [1, p. 591]

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Page 10: Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR techniques 10.2 Asymptotic approximations: Bode plots Simple Bode plots, [1, p. 542]

10 FR techniques 10.11 Steady-state error characteristics from FR

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 55 / 64

10 FR techniques 10.11 Steady-state error characteristics from FR

Position constant, [1, p. 593]

Type 0 system

G(s) = K

Qni=1(s+ zi)Qmj=1(s+ pj)

Initial log-magnitude value

20 logM = 20 logKp

Position constant

Kp = K

Qni=1 ziQmj=1 pj

Figure: Typical unnormalized andunscaled Bode log-magnitude plotsshowing the value of static errorconstants

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 56 / 64

10 FR techniques 10.11 Steady-state error characteristics from FR

Velocity constant, [1, p. 594]

Type 1 system

G(s) = K

Qni=1(s+ zi)

sQm

j=1(s+ pj)

Initial log-magnitude value

20 logM = 20 log

Kv

!0

Velocity constant

Kv = K

Qni=1 ziQmj=1 pj

Frequency axis intersect

! = Kv

Figure: Typical unnormalized andunscaled Bode log-magnitude plotsshowing the value of static errorconstants

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 57 / 64

10 FR techniques 10.11 Steady-state error characteristics from FR

Acceleration constant, [1, p. 595]

Type 2 system

G(s) = K

Qni=1(s+ zi)

s2Qm

j=1(s+ pj)

Acceleration constant

Ka = K

Qni=1 ziQmj=1 pj

Initial log-magnitude value

20 logM = 20 log

Ka

!20

Frequency axis intersect

! =

pKa

Figure: Typical unnormalized andunscaled Bode log-magnitude plotsshowing the value of static errorconstants

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 58 / 64

10 FR techniques 10.12 System with time delay

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

Bayen (EECS, UCB) Feedback Control Systems September 10, 2013 59 / 64

10 FR techniques 10.12 System with time delay

Modeling time delay, [1, p. 597]

Time delay – delay between thecommanded response and the startof the output response

G0(s) = e�sTG(s)

FR

G0(j!) = e�j!TG(j!)

= |G(j!)|\[�!T + \G(j!)]Figure: E↵ect of delay upon FR

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Page 11: Lecture abstract EE C128 / ME C134 – Feedback Control Systemssojoudi/EEC128-chap10.pdf · 10 FR techniques 10.2 Asymptotic approximations: Bode plots Simple Bode plots, [1, p. 542]

10 FR techniques 10.13 Obtaining TFs experimentally

1 10 Frequency response techniques10.1 Introduction10.2 Asymptotic approximations: Bode plots10.3 Introduction to Nyquist criterion10.4 Sketching the Nyquist diagram10.5 Stability via the Nyquist diagram10.6 Gain margin and phase margin via the Nyquist diagram10.7 Stability, gain margin, and phase margin via Bode plots10.8 Relation between closed-loop transient and closed-loopfrequency responses10.9 Relation between closed- and open-loop frequency responses10.10 Relation between closed-loop transient and open-loopfrequency responses10.11 Steady-state error characteristics from frequency response10.12 System with time delay10.13 Obtaining transfer functions experimentally

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10 FR techniques 10.13 Obtaining TFs experimentally

Obtaining transfer functions experimentally, [1, p. 602]

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10 FR techniques 10.13 Obtaining TFs experimentally

Method

1. Estimate the pole-zero configuration from the Bode diagramsI Initial slope ! system typeI Phase excursions ! #poles & #zeros

2. Look for obvious 1st- & 2nd-order pole or zero FR characteristics

3. Peaking & depressions ! underdamped 2nd-order pole & zero,respectively

4. Extract 1st- & 2nd-order characteristicsI Overlay ±20 or ±40 dB/decade lines on magnitude curve &

±45�/decade lines on the phase curveI Estimate break frequenciesI For 2nd-order poles & zeros, estimate ⇣ & !n

5. Form a TF of unity gain using the poles & zeros foundI Subtract the FR of the model from the measured FR and repeat the

process if necessary

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10 FR techniques 10.13 Obtaining TFs experimentally

Bibliography

Norman S. Nise. Control Systems Engineering, 2011.

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