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6.003: Signals and Systems
CT Frequency Response and Bode Plots
March 9, 2010
(
Last Time
Complex exponentials are eigenfunctions of LTI systems.
H(s)es0t H(s0) es0t
H(s0) can be determined graphically using vectorial analysis. (s0 − z0)(s0 − z1)(s0 − z2) · · ·
H(s0) = K (s0 − p0)(s0 − p1)(s0 − p2) · · ·
z0 z0
s0 − z0 s0
s-planes0
Response of an LTI system to an eternal cosine is an eternal cosine:
same frequency, but scaled and shifted.
H(s)cos(ω0t) |H(jω0)| cos ω0t + ∠H(jω0))
Frequency Response: H(s)|s←jω
|H(jω)|H(s) = s − z1 5
ω 5 s-plane
−5 0 5
∠H(jω)
5 σ
π/2−5
−5 5
−5 −π/2
Frequency Response: H(s)|s←jω
|H(jω)|9 H(s) = 5
s − p1
ω 5 s-plane
−5 0 5
∠H(jω)
5 σ
π/2−5
−5 5
−5 −π/2
Frequency Response: H(s)|s←jω
H(s) = 3 s − z1 |H
5(jω)|
s − p1
ω 5 s-plane
−5 0 5
∠H(jω)
5 σ
π/2−5
−5 5
−5 −π/2
Poles and Zeros
Thinking about systems as collections of poles and zeros is an im
portant design concept.
• simple: just a few numbers characterize entire system
• powerful: complete information about frequency response
Today: poles, zeros, frequency responses, and Bode plots.
Asymptotic Behavior: Isolated Zero
The magnitude response is simple at low and high frequencies.
|H(jω)|H(jω) = jω − z1 5
ω 5
−5 0 5
∠H(jω)
5 σ
π/2−5
−5 5
−5 −π/2
Asymptotic Behavior: Isolated Zero
The magnitude response is simple at low and high frequencies.
|H(jω)|H(jω) = jω − z1 5
ω 5 z1
−5 0 5
∠H(jω)
5 σ
π/2−5
−5 5
−5 −π/2
Asymptotic Behavior: Isolated Zero
The magnitude response is simple at low and high frequencies.
|H(jω)|H(jω) = jω − z1 5
ω
ω 5 z1
−5 0 5
∠H(jω)
5 σ
π/2−5
−5 5
−5 −π/2
Asymptotic Behavior: Isolated Zero
Two asymptotes provide a good approxmation on log-log axes.
H(s) = s − z1
log |H(jω)|
|H(jω)| z12 5
1 1
0 log ω
−5 0 5 −2 −1 0 1 2 z1
lim |H(jω)| = z1 ω→0
lim |H(jω)| = ω ω→∞
Asymptotic Behavior: Isolated Pole
The magnitude response is simple at low and high frequencies.
H(s) = 9
ω 9
|H5(jω)|
s − p1 9
ω p15
−5 0 5
∠H(jω)
5 σ
π/2−5
−5 5
−5 −π/2
Asymptotic Behavior: Isolated Pole
Two asymptotes provide a good approxmation on log-log axes.
9 H(s) =
s − p1
log |H
9( /p
jω)| 1 |H(jω)| 0
5
−1
−2
−1
log ω
−5 0 5 −2 −1 0 1 2 p1
9lim |H(jω)| = ω→0 p1
9lim |H(jω)| = ω→∞ ω
Check Yourself
Compare log-log plots of the frequency-response magnitudes of
the following system functions:
H1(s) = 1 s + 1
and H2(s) = 1 s + 10
The former can be transformed into the latter by
1. shifting horizontally
2. shifting and scaling horizontally
3. shifting both horizontally and vertically
4. shifting and scaling both horizontally and vertically
5. none of the above
Check Yourself
Compare log-log plots of the frequency-response magnitudes of the
following system functions:
1 1 H1(s) = and H2(s) =
s + 1 s + 10
log |H(jω)| 0 |H1(jω)|
−1 |H2(jω)|−1
−2 log ω
−2 −1 0 1 2
Check Yourself
Compare log-log plots of the frequency-response magnitudes of
the following system functions:
H1(s) = 1 s + 1
and H2(s) = 1 s + 10
The former can be transformed into the latter by 3
1. shifting horizontally
2. shifting and scaling horizontally
3. shifting both horizontally and vertically
4. shifting and scaling both horizontally and vertically
5. none of the above
no scaling in either vertical or horizontal directions !
Asymptotic Behavior of More Complicated Systems
Constructing H(s0).
Q
H(s0) = K
∏
∏
q=1
P
p=1
(s0 − zq)
(s0 − pp)
s0 − z1
z1
← product of vectors for zeros
← product of vectors for poles
ω s-planes0
s0 − p1
σ p1
∣ ∣ ∣ ∣
∣ ∣ ∣ ∣ ∣ ∣
∏ ∏
∏ ∏
∣ ∣
Asymptotic Behavior of More Complicated Systems
The magnitude of a product is the product of the magnitudes.
∣ Q ∣ Q ∣ (s0 − zq) ∣ ∣ s0 − zq
∣ ∣ ∣ ∣ ∣|H(s0)| = ∣ K
q=1 ∣ = |K| q=1 ∣ P ∣ P ∣ (s0 − pp) ∣ ∣s0 − pp ∣ ∣ p=1 ∣ p=1
ω s-planes0
s 0−z 1
s0 −p1
σ z1 p1
∣ ∣ ∣ ∣
∣ ∣ ∣ ∣ ∣ ∣
∏ ∏
∏ ∏
∣ ∣ ∣ ∣
∑ ∑
Bode Plot
The log of the magnitude is a sum of logs.
∣ Q ∣ Q ∣ (s0 − zq) ∣ ∣ s0 − zq
∣ ∣ ∣ ∣ ∣|H(s0)| = K
q=1 = |K| q=1 ∣ P ∣ P ∣ (s0 − pp) ∣ ∣s0 − pp ∣ ∣ p=1 ∣ p=1
Q P ∣ ∣log |H(jω)| = log |K| + log ∣∣jω − zq
∣ − log ∣∣jω − pp
∣ q=1 p=1
log∣∣∣∣ jω
(jω + 1)(jω + 10)
∣∣∣∣
∣ ∣ ∣ ∣
∣ ∣ ∣ ∣
Bode Plot: Adding Instead of Multiplying
H(s) = (s + 1)( s
s + 10) 0
ω −1 10
s-plane −2
log |jω|
log ω −2 −1 0 1 2 3
0 ∣ 1 ∣ σ log ∣jω + 1 ∣ −10 10 −1 log ω
−2 −1 0 1 2 3 −1 ∣ 1 ∣
−10 log ∣jω + 10 ∣ −2 log ω
−2 −1 0 1 2 3
log∣∣∣∣ jω
(jω + 1)(jω + 10)
∣∣∣∣
∣ ∣ ∣ ∣
Bode Plot: Adding Instead of Multiplying ∣ ∣ ∣ ∣log ∣∣ jωjω + 1 ∣∣
s H(s) = (s + 1)(s + 10)
0
ω −1 10
s-plane −2 log ω
−2 −1 0 1 2 3
σ −10 10
−1 log ∣ 1 ∣
−10 ∣jω + 10 ∣ −2 log ω
−2 −1 0 1 2 3
−2 −1 0 1 2 3
−1
−2 logω
log∣∣∣∣ 1jω + 10
∣∣∣∣
∣ ∣ Bode Plot: Adding Instead of Multiplying ∣ ∣
log ∣∣ (jω + 1)( jω
jω + 10) ∣∣
H(s) = (s + 1)( s
s + 10) −1
ω −2 10
s-plane −3 log ω
−2 −1 0 1 2 3
σ −10 10
−10
−2 −1 0 1 2 3
−1
−2 logω
log∣∣∣∣ 1jω + 10
∣∣∣∣
∣ ∣ Bode Plot: Adding Instead of Multiplying ∣ ∣
log ∣∣ (jω + 1)( jω
jω + 10) ∣∣
H(s) = (s + 1)( s
s + 10) −1
ω −2 10
s-plane −3 log ω
−2 −1 0 1 2 3
σ −10 10
−10
Asymptotic Behavior: Isolated Zero
The angle response is simple at low and high frequencies.
|H(jω)|H(s) = s − z1 5
ω 5 s-plane
−5 0 5
∠H(jω)
5 σ
π/2−5
−5 5
−5 −π/2
Asymptotic Behavior: Isolated Zero
Three straight lines provide a good approxmation versus log ω.
H(s) = s − z1
∠H(jω) ∠H(jω)
π/2
−5 5
−π/2
π 2
π 4
0 log ω
−2 −1 0 1 2 |z1|
lim ∠H(jω) = 0 ω→0
lim ∠H(jω) = π/2 ω→∞
Asymptotic Behavior: Isolated Pole
The angle response is simple at low and high frequencies.
|H(jω)|9 H(s) = 5
s − p1
ω 5 s-plane
−5 0 5
∠H(jω) σ
π/2−5 5
−5 5
−5 −π/2
Asymptotic Behavior: Isolated Pole
Three straight lines provide a good approxmation versus log ω.
9 H(s) =
s − p1
∠H(jω) ∠H(jω)
π/2
−π −5 5
−π−π/2
0
4
2 log ω
−2 −1 0 1 2 p1
lim ∠H(jω) = 0 ω→0
lim ∠H(jω) = −π/2ω→∞
∏
∏
∑ ∑
Bode Plot
The angle of a product is the sum of the angles. ⎛ ⎞ Q ⎜ (s0 − zq) ⎟⎜ ⎟ Q P ⎜ q=1 ⎟ ( ) ( ) ⎜ ⎟∠H(s0) = ∠ ⎜ K ⎟ = ∠K + ∠ s0 − zq − ∠ s0 − ppP ⎜ ⎟ ⎝ (s0 − pp) ⎠ q=1 p=1
p=1
ω
z1 p1
∠(s0 − z1) ∠(s0 − p1) σ
s-planes0
The angle of K can be 0 or π for systems described by linear differ
ential equations with constant, real-valued coefficients.
log∣∣∣∣ s
(s+ 1)(s+ 10)
∣∣∣∣Bode Plot
∠jω
H(s) = (s + 1)( s
s + 10) π/2
ω 0 10
s-plane −π/2 log ω
−2 −1 0 1 2 3 0 1∠σ
jω + 1−10 10 −π/2 log ω −2 −1 0 1 2 3
0 1∠−10 jω + 10 −π/2 log ω
−2 −1 0 1 2 3
log∣∣∣∣ s
(s+ 1)(s+ 10)
∣∣∣∣Bode Plot
H(s) = s
(s + 1)(s + 10) π/2
ω 0 10
s-plane −π/2
σ −10 10
0 −10
−π/2
∠ jω jω + 1
log ω −2 −1 0 1 2 3
1∠ jω + 10
log ω −2 −1 0 1 2 3
log∣∣∣∣ s
(s+ 1)(s+ 10)
∣∣∣∣
−2 −1 0 1 2 3
0
−π/2 logω
∠ 1jω + 10
Bode Plot
∠ jω
(jω + 1)(jω + 10) H(s) = (s + 1)(
s
s + 10) π/2
ω 0 10
s-plane −π/2 log ω
−2 −1 0 1 2 3
σ −10 10
−10
log∣∣∣∣ s
(s+ 1)(s+ 10)
∣∣∣∣
−2 −1 0 1 2 3
0
−π/2 logω
∠ 1jω + 10
Bode Plot
∠ jω
(jω + 1)(jω + 10) H(s) = (s + 1)(
s
s + 10) π/2
ω 0 10
s-plane −π/2 log ω
−2 −1 0 1 2 3
σ −10 10
−10
∏ ∣ ∣
∏ ∣ ∣
∑ ∑ ∣ ∣ ∣ ∣
∑ ∑ ( ) ( )
From Frequency Response to Bode Plot
The magnitude of H(jω) is a product of magnitudes. Q ∣jω − zq ∣
|H(jω)| = |K| q=1
P ∣jω − pp ∣ p=1
The log of the magnitude is a sum of logs. Q P
log |H(jω)| = log |K| + log ∣ jω − zq
∣ − log ∣ jω − pp
∣ q=1 p=1
The angle of H(jω) is a sum of angles. Q P
∠H(jω) = ∠K + ∠ jω − zq − ∠ jω − pp q=1 p=1
Check Yourself
−1 0 1 2 3 4
−2
−3
−4 log ω
log |H(jω)|
Which corresponds to the Bode approximation above?
1. 1
(s + 1)(s + 10)(s + 100) 2.
s + 1 (s + 10)(s + 100)
3. (s + 10)(s + 100)
s + 1 4.
s + 100 (s + 1)(s + 10)
5. none of the above
Check Yourself
−1 0 1 2 3 4
−2
−3
−4 log ω
log |H(jω)|
Which corresponds to the Bode approximation above? 2
1. 1
(s + 1)(s + 10)(s + 100) 2.
s + 1 (s + 10)(s + 100)
3. (s + 10)(s + 100)
s + 1 4.
s + 100 (s + 1)(s + 10)
5. none of the above
ω [log scale]
ω [log scale]
log∣∣∣∣ s
(s+ 1)(s+ 10)
∣∣∣∣
Bode Plot: dB
log |H(jω)| 10s 0
H(s) = (s + 1)(s + 10)
ω −110
s-plane −2
−11
log ω −2 −1 0 1 2 3
σ ∠H(jω)−10 10 π/2
0−10
−π/2 log ω −2 −1 0 1 2 3
ω [log scale]
ω [log scale]
log∣∣∣∣ s
(s+ 1)(s+ 10)
∣∣∣∣
Bode Plot: dB
log |H(jω)| 10s 0
H(s) = (s + 1)(s + 10)
ω −1 10
s-plane −2
−11
ω [log scale] 0.01 0.1 1 10 100 1000
σ ∠H(jω)−10 10 π/2
0 −10
−π/2 ω [log scale] 0.01 0.1 1 10 100 1000
ω [log scale]
ω [log scale]
log∣∣∣∣ s
(s+ 1)(s+ 10)
∣∣∣∣
Bode Plot: dB
|H(jω)|[dB]= 20 log10 |H(jω)| 10s 0
H(s) = (s + 1)(s + 10)
ω −20 10
s-plane −40
−11
ω [log scale] 0.01 0.1 1 10 100 1000
σ ∠H(jω)−10 10 π/2
0 −10
−π/2 ω [log scale] 0.01 0.1 1 10 100 1000
ω [log scale]
ω [log scale]
log∣∣∣∣ s
(s+ 1)(s+ 10)
∣∣∣∣
Bode Plot: dB
|H(jω)|[dB]= 20 log10 |H(jω)| 10s 0
H(s) = (s + 1)(s + 10)
ω −20 20 dB/decade −20 dB/decade10
s-plane −40 ω [log scale]
0.01 0.1 1 10 100 1000
σ ∠H(jω)−10 10 π/2
0 −10
−π/2 ω [log scale] 0.01 0.1 1 10 100 1000
Bode Plot: Accuracy
The straight-line approximations are surprisingly accurate.
1
1 dB 3 dB
1 dB
H(jω) = jω + 1 20 log10 X0 X
√1 0 dB 2 ≈ 3 dB
−10 2 ≈ 6 dB 10 20 dB 100 40 dB
−20 ω [log scale] 0.1 1 10
0
|H(jω
)|[dB]
0.1 rad (6◦)∠H
(jω
)
−π/4
−π/2 ω [log scale] 0.01 0.1 1 10 100
Check Yourself
Could the phase plots of any of these systems be equal to
each other? [caution: this is a trick question]
−1
1
−1 1
2
−1 ( )2
3
−1 ( )2
4
Check Yourself
π
ω1. −1 −π
π
ω2. −1 1 −π
π
2 ω3. −1 −π
π
2 ω4. −1 −π
Check Yourself
π
1. −1 −π
π
2. −1 1 −π
π
3. −1
2
−π π
4. −1
2
−π
ω
ω if K < 0
ω
ω
Check Yourself
Could the phase plots of any of these systems be equal to
each other? [caution: this is a trick question] yes
−1
1
−1 1
2
−1 ( )2
3
−1 ( )2
4
phase of 2 could be same as phase of 3: depends on sign of K
√ (
Frequency Response of a High-Q System
The frequency-response magnitude of a high-Q system is peaked.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
s plane
ω0
−1 1 −2Q
log |H(jω)|
1 − 21 Q
)2 0
−1
√ ( )2−2 − 1 − 2
1 Q
log ω
ω
0−2 −1 0 1 2
√
Frequency Response of a High-Q System
The frequency-response magnitude of a high-Q system is peaked.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
s plane
ω0
−1 1 −2Q
log |H(jω)| ( )21 − 2
1 Q 0
−1
√ −2 log ω
− 1 − (
1 )2
ω02Q −2 −1 0 1 2
√
(
Frequency Response of a High-Q System
The frequency-response magnitude of a high-Q system is peaked.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
log |H(jω)|s plane
ω0 1 − (
1 )2
0
−1 −1 1 −2Q √ −2
log ω
1 )2
1 − ω0
2Q
− 2Q −2 −1 0 1 2
√
√
Frequency Response of a High-Q System
The frequency-response magnitude of a high-Q system is peaked.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
log |H(jω)|s plane
ω0 1 − (
1 )2
0
− 1
2Q
−1 −1
−2 log ω
1 − (
1 )2
ω0
2Q
− 2Q −2 −1 0 1 2
√
√
Frequency Response of a High-Q System
The frequency-response magnitude of a high-Q system is peaked.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
log |H(jω)|s plane
ω0 1 − (
1 )2
0
−1 −1
−2Q 1
−2 log ω
1 − (
1 )2
ω0
2Q
− 2Q −2 −1 0 1 2
Check Yourself
Find dependence of peak magnitude on Q (assume Q > 3).
s ω0
plane
−1 −
1 2Q
√
1 − (
1 2Q
)2
−
√
1 − (
1 2Q
)2
H(s) = 1
1 + 1 Q s ω0
+
( s ω0
)2
−2 −1 0 1 2
0
−1
−2 log ω ω0
log |H(jω)|
Check Yourself
Find dependence of peak magnitude on Q (assume Q > 3).
Analyze with vectors.
low frequencies high frequencies
ω/ω0 ω/ω0
− 1
2Q
σ/ω0 −1 −
1 2Q
1 2Q
σ/ω0−1
× 2 =1× 1 = 1 Q
Peak magnitude increases with Q !
1
√ (
Frequency Response of a High-Q System
As Q increases, the width of the peak narrows.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
s plane
ω0
−1 1 −2Q
log |H(jω)|
1 − 21 Q
)2 0
−1
√ ( )2−2 − 1 − 2
1 Q
log ω
ω
0−2 −1 0 1 2
√
Frequency Response of a High-Q System
As Q increases, the width of the peak narrows.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
s plane
ω0
−1 1 −2Q
log |H(jω)| ( )21 − 2
1 Q 0
−1
√ −2 log ω
− 1 − (
1 )2
ω02Q −2 −1 0 1 2
√
(
Frequency Response of a High-Q System
As Q increases, the width of the peak narrows.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
log |H(jω)|s plane
ω0 1 − (
21 )2
0
−1 −1 1 −2Q √ −2
log ω
1 )2
1 − ω0
Q
− 2Q −2 −1 0 1 2
√
√
Frequency Response of a High-Q System
As Q increases, the width of the peak narrows.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
log |H(jω)|s plane
ω0 1 − (
21 )2
0
− 1
2Q
−1 −1
−2 log ω
1 − (
1 )2
ω0
Q
− 2Q −2 −1 0 1 2
√
√
Frequency Response of a High-Q System
As Q increases, the width of the peak narrows.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
log |H(jω)|s plane
ω0 1 − (
21 )2
0Q
−1 −1
−2Q 1
−2 log ω
1 − (
1 )2
ω0− 2Q −2 −1 0 1 2
Check Yourself
Estimate the “3dB bandwidth” of the peak (assume Q > 3).
Let ωl (or ωh) represent the lowest (or highest) frequency for
which the magnitude is greater than the peak value divided by√2. The 3dB bandwidth is then ωh − ωl.
s ω0
plane
−1 −
1 2Q
√
1 − (
1 2Q
)2
−
√
1 − (
1 2Q
)2
−2 −1 0 1 2
0
−1
−2 log ω ω0
log |H(jω)|
Check Yourself
Estimate the “3dB bandwidth” of the peak (assume Q > 3).
Analyze with vectors.
low frequencies high frequencies
ω/ω0 ω/ω0
−1 −
1 2Q
√2 1
2Q
1− 1
2Q
1
− 1
2Q
1 + 2Q
σ/ω0 σ/ω0−1
√ × 2 = 2 √
221 Q × 2 =
√
Q 2
Q
1 Bandwidth approximately
Q
Frequency Response of a High-Q System
As Q increases, the phase changes more abruptly with ω.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
s plane
ω0
−1
∠ |H(jω)|
0
−π/2
−π log ω
−2 −1 0 1 2 ω0
√ (
√
Frequency Response of a High-Q System
As Q increases, the phase changes more abruptly with ω.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
s plane
ω0
−1 1 −2Q
∠ |H(jω)|
1 − 21 Q
)2 0
−π/2
( )2−π − 1 − 21 Q
log ω
ω
0−2 −1 0 1 2
√
Frequency Response of a High-Q System
As Q increases, the phase changes more abruptly with ω.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
s plane
ω0
−1 1 −2Q
∠ |H(jω)| ( )21 − 2
1 Q 0
−π/2
√ −π log ω
− 1 − (
1 )2
ω02Q −2 −1 0 1 2
√
√
Frequency Response of a High-Q System
As Q increases, the phase changes more abruptly with ω.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
∠ |H(jω)|s plane
ω0 1 − (
1 )2
0
−π/2 −1 1 −2Q −π
log ω
1 − (
1 )2
ω0
2Q
− 2Q −2 −1 0 1 2
√
√
Frequency Response of a High-Q System
As Q increases, the phase changes more abruptly with ω.
1 H(s) = ( )21 s s1 + +
Q ω0 ω0
∠ |H(jω)|s plane
ω0 1 − (
1 )2
0
− 1
2Q
−π/2 −1
−π log ω
1 − (
1 )2
ω0
2Q
− 2Q −2 −1 0 1 2
Check Yourself
Estimate change in phase that occurs over the 3dB bandwidth.
s ω0
plane
−1 −
1 2Q
√
1 − (
1 2Q
)2
−
√
1 − (
1 2Q
)2
H(s) = 1
1 + 1 Q s ω0
+
( s ω0
)2
−2 −1 0 1 2
0
−π/2
−π log ω ω0
∠ |H(jω)|
Check Yourself
Estimate change in phase that occurs over the 3dB bandwidth.
Analyze with vectors.
low frequencies high frequencies
−1 −
1 2Q
π 2 − π
1− 1
2Q
ω/ω0 ω/ω0
− 1
2Q
11 + 2Q
σ/ω0 σ/ω0−1
π π π 3π 4 = 4 2 + 4 = 4
π Change in phase approximately 2 .
Summary
The frequency response of a system can be quickly determined using
Bode plots.
Bode plots are constructed from sections that correspond to single
poles and single zeros.
Responses for each section simply sum when plotted on logarithmic
coordinates.
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6.003 Signals and Systems Spring 2010
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