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Review
of
Feedback Control System
Transfer Function for a PID Controller
Ideal PID :
Real PID :
Derivative Kick:
To avoid sudden jump of output due to setpoint
change, sensor output is used in place of error term,
i.e,
0
0
( )
1
( ) ( ) ( )
t
s
c D
I
dy t
c t c K e t e d
dt
  

 
   
 
 

Direct / Reverse acting controller
• What will be the sign of the controller gain?
Fout
Fin
L
LC
LT
Guidelines for Selecting Direct and Reverse
Acting PID’s
• Consider a direct acting final control element to be
positive and reverse to be negative.
• If the sign of the product of the final control
element and the process gain is positive, use the
reverse acting PID algorithm.
• If the sign of the product is negative, use the direct
acting PID algorithm
• If control signal goes to a control valve with a valve
positioner, the actuator is considered direct acting.
Level Control Example
• Process gain is positive
because when flow in is
increased, the level
increases.
• If the final control
element is direct acting,
use reverse acting PID.
• For reverse acting final
control element, use
direct acting PID.
Fout
Fin
L
LC
LT
Level Control Example
Fout
Fin
L
LC
LT
• Process gain is negative
because when flow out is
increased, the level
decreases.
• If the final control
element is direct acting,
use direct acting PID.
• For reverse acting final
control element, use
reverse acting PID.
General Feedback Control Loop
GP(s)
Ga(s)
GC(s)
KS
GS(s)
Gd(s)
d(s)
ysp(s)
+
-
+
+
u(s) y(s)
c(s)
e(s)
yS(s)
1
)
(
)
(
)
(
)
(
1
)
(
)
(
)
(
)
(
)
(
)
(
)
(
)
(
)
(




s
G
s
G
s
G
s
G
s
G
s
G
s
G
s
G
s
G
s
G
s
G
K
s
y
s
y
c
c
s
c
a
p
c
a
p
S
sp
Characteristic Polynomial : 1 + GOL = 0 or
Controller actions on feedback dynamics
Process G(s) : Controller : Proportional, ;
Matlab:
s=tf(‘s’); g=1/(s+1)^3;
step(g); hold on
for kc=[0.5:0.5:2],
gcl=feedback(kc*g,1);
step(gcl);
end
Proportional Control
Important points:
• proportional feedback does not change the order of the system
• started with a first order process
• closed-loop process also first order
• order of characteristic polynomial is invariant under proportional
feedback
• speed of response of closed-loop process is directly affected
by controller gain
• increasing controller gain reduces the closed-loop time constant
• In general, proportional feedback
• reduces (does not eliminate) offset
• speeds up response
• for oscillatory processes, makes closed-loop process more oscillatory
Controller actions on feedback dynamics
Process G(s) : Controller : PI (I varying) ;
Matlab:
figure; hold on; kc=2;
for Ti=[2:1:5],
gc=tf(kc*[1,1/Ti],[1,0]);
gcl=feedback(gc*g,1);
step(gcl);
end
Proporional - Integral Control
Important points:
• integral action increases order of the system in closed-loop
• integral action eliminates offset
• integral action
• should be small compared to proportional action
• tuned to slowly eliminate offset
• can increase or cause oscillation
• can be de-stabilizing
• PI controller has two tuning parameters that can
independently affect
• speed of response
• Nature of response (oscillation)
• PI is the most widely used controller in industry
• optimal structure for first order processes
Controller actions on feedback dynamics
Process G(s) : Controller : PD, ;
Matlab:
figure; hold on; kc=2;
for Td=[0:0.2:0.8],
gc=tf(kc*[Td,1],[1]);
gcl=feedback(gc*g,1);
step(gcl); end
Proportional Derivative
Important Points:
• derivative action does not increase the order of the system
• Used to compensate for trends in output
• measure of speed of error signal change
• provides predictive or anticipatory action
• adding derivative action affects the period of oscillation
of the process
• good for disturbance rejection
• poor for tracking
• derivative action
• should be small compared to integral action
• has a stabilizing influence
• difficult to use for noisy signals
• usually modified in practical implementation
PID control (Setpoint Tracking or Servo Control)
Disturbance Rejection: Input dynamics
Closed-loop Stability
Every control problem involves a consideration of closed-
loop stability
General concepts:
BIBO Stability:
“ An (unconstrained) linear system is said to be stable if the
output response is bounded for all bounded inputs.
Otherwise it is unstable.”
Comments:
• Stability is much easier to prove than instability
• This is just one type of stability
Closed-loop Stability
General Stability criterion:
“ A closed-loop feedback control system is stable if and only
if all roots of the characteristic polynomial (1+ GOL=0) are
negative or have negative real parts. Otherwise, the system
is unstable.”
• Unstable region is the right half plane of the complex plane.
• Valid for any linear systems.
• Underlying system is almost always nonlinear so stability
holds only locally. Moving away from the point of
linearization may cause instability
Stability Analysis Methods
Problem reduces to finding roots of a polynomial
Traditional:
1. Routh array:
• Test for positivity of roots of a polynomial
2. Direct substitution
• Complex axis separates stable and unstable regions
• Find controller gain that yields purely complex roots
3. Root locus diagram
• Vary location of poles as controller gain is varied
• Of limited use
• Bode stability criteria
• Niquist Stability criteria
Closed-loop stability
Routh array for a polynomial equation
is
where
Elements of left column must be positive to have roots with negative real parts
a s a s a s a
n
n
n
n
    


1
1
1 0 0

a a a
a a a
b b b
c c
z
n n n
n n n
 
  
2 4
1 3 5
1 2 3
1 2
1





1
2
3
4
1

n 
b
a a a a
a
b
a a a a
a
c
b a b a
b
c
b a b a
b
n n n n
n
n n n n
n
n n n n
1
1 2 3
1
2
1 4 5
1
1
1 3 2 1
1
2
1 5 3 1
1








  

  

   
, ,
, ,


Example: Routh Array
Characteristic polynomial
Polynomial Coefficients
Routh Array
• Closed-loop system is unstable
2 36 1 49 0 58 1 21 0 42 0 78 0
5 4 3 2
. . . . . .
s s s s s
     
a a a
a a a
b b b
c c
d d
e
5 3 1
4 2 0
1 2 3
1 2
1 2
1
2 36 0 58 0 42
1 49 1 21 0 78
2 50 0 82 0
0 72 0 78
1 89 0
0 78
( . ) ( . ) ( . )
( . ) ( . ) ( . )
( . ) ( . ) ( )
( . ) ( . )
( . ) ( )
( . )

 
a a a a a a
5 4 3 2 1 0
2 36 1 49 0 58 1 21 0 42 0 78
      
. , . , . , . , . , .
1
2
3
4
5
6
Direct Substitution
• Technique to find gain value that de-stabilizes the system.
• Observation:
Process becomes unstable when poles appear on right half plane
Find value of Kc that yields purely complex poles
• Strategy:
• Start with characteristic polynomial
• Write characteristic equation:
• Substitute for complex pole (s=jw)
• Solve for Kc and w
q j K r j
c
( ) ( )
 
 0
 
( )
1 ( ) ( ) ( ) 1
c a p s c
r s
K G s G s G s K
q s
  
q s K r s
c
( ) ( )
 0
Example: Direct Substitution
Characteristic equation
Substitution for s=jw
Real Part : Complex Part:
• System is unstable if
1
1
0 5 0 5 0 75
0
0 5 0 5 0 75 0
0 5 0 5 0 75 0
3 2
3 2
3 2


  

     
     
K
s
s s s
s s s K s K
s s K s K
c
c c
c c
. . .
. . .
. ( . ) ( . )
( ) . ( ) ( . ) ( . )
. ( . ) ( . )
j j K j K
j K j K
c c
c c
  
  
3 2
3 2
0 5 0 5 0 75 0
0 5 0 5 0 75 0
     
      
   
0 5 0 75 0
2
. .
 Kc ( . )
Kc   
0 5 0
3
 
       
   
  
K
K
c
c
0 5 0 75 0 5 0 75 0 5 0
0 5 0 25 0
2 2 1
2 2 3
2
. . ( . . . )
. .
/ ,
   


Kc 1
Root Locus Diagram
• Old method that consists in plotting roots of characteristic
polynomial (closed loop poles) as controller gain is changed.
Matlab
s=tf(‘s’);
G1=1/(s+1);
G2=1/(s+2);
G3=1/(s+3);
G=G1*G2*G3;
rlocus(G);
rlocfind(G);
Frequency Response
Process
𝑢=𝐴𝑠𝑖𝑛𝜔𝑡 𝑦=^
𝐴 sin⁡(𝜔𝑡+𝜙)
0 20 40 60 80 100
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
Sinusoidal Response
Time (seconds)
Amplitude
A
Â
t
Amplitude Ratio (AR) = Â/A
Phase lag ( = -t/P*180
The process acts as a “filter”
or “amplifier” that attenuates
or amplifies the input at
frequency .
The frequency response of a
process G(s) at a specific
frequency is a complex
number and can be obtained
by substituting
P
Frequency Response
• Two ways of representing the frequency response
• Bode Plot
• Log-Log plot of AR vs and semi-log plot vs
• Nyquist Plot
• Plot of Re() vs Im() for various values of .
• Frequency does not appear explicitly in this plot.
Bode Plot
10
-5
10
0
Magnitude
(abs)
10
-2
10
-1
10
0
10
1
10
2
-360
-315
-270
-225
-180
-135
-90
-45
0
Phase
(deg)
Bode Diagram
Frequency (rad/s)
Crossover
Frequency
Corner Frequency
Meeting pt of LFA and HFA
Steady state gain:
Bandwidth, , defines
the highest
frequency at which
the process displays
no attenuation. It is
calculated based on
the frequency when
amplitude reaches
0.707 K.
Roll-off is slope of
decaying AR at high
frequencies.
𝜔=0
Crossover
AR(
𝜙(𝜔)
Bode Stability Criterion
Consider open-loop control system
1. Introduce sinusoidal input in setpoint (D(s)=0) and observe sinusoidal output
2. Fix gain such AR=1 and input frequency such that =-180
3. At same time, connect close the loop and set YSP(s)=0
Q: What happens if AR <1, 1 and >1?
Open-loop Response to YSP(s)
Gp
Gc
Gs
D(s)
Y(s)
Ys(s)
YSP(s) U(s)
+
-
+
+
Bode Stability Criterion
A closed-loop system is unstable if the frequency of the response
of the open-loop GOL has an amplitude ratio greater than one at
the critical frequency. Otherwise it is stable.
Strategy:
1. Solve for w in
2. Calculate AR
arg( ( ))
G j
OL  
 
AR G j
OL
 ( )

Bode Stability Criterion
To check for stability:
1. Compute open-loop transfer function
2. Solve for w in f=-p
3. Evaluate AR at w
4. If AR>1 then process is unstable
Find ultimate gain:
1. Compute open-loop transfer function without controller gain
2. Solve for w in f=-p
3. Evaluate AR at w
4. Let K
AR
cu 
1
Bode Criterion
Consider the transfer function and controller
- Open-loop transfer function
- Amplitude ratio and phase shift
- At f=-p, w=1.4128, AR=6.746
G s
e
s s
s
( )
( )( . )
.

 

5
1 0 5 1
0 1
G s
s
c ( ) .
.
 






0 4 1
1
0 1
G s
e
s s s
OL
s
( )
( )( . )
.
.
.

 








5
1 0 5 1
0 4 1
1
0 1
0 1
AR 
 

     





  
5
1
1
1 0 25
0 4 1
1
0 01
0 1 0 5
1
0 1
2 2 2
1 1 1
  
   

.
.
.
. tan ( ) tan ( . ) tan
.
Bode Stability
• Phase Crossover frequency (is the frequency at which
phase lag is 1800
.
• Gain Crossover frequency () is the frequency at which
AR = 1
• Gain Margin (GM) is the amount of gain required for
the AR to reach 1 at phase crossover frequency.
GM=1/ARC , where ARC is the Amplitude ratio at gain
crossover frequency.
• Phase Margin (PM) is the amount of phase difference
required for phase lag to reach 1800
at gain crossover
frequency. PM=180+ where is phase lag at phase
crossover frequency.
Gain Margin and Phase Margin
dB=20 log10AR
Wcg is the
frequency where
the gain margin is
measured, which
is a -180° phase
crossing
frequency.
Wcp is the
frequency where
the phase margin
is measured,
which is a 0-dB
gain crossing
frequency.
Nyquist Stability Criterion
If N is the number of times that the Nyquist plot encircles the
point (-1,0) in the complex plane in the clockwise direction, and
P is the number of open-loop poles of GOL that lie in the right-
half plane, then Z=N+P is the number of unstable roots of the
closed-loop characteristic equation.
Strategy
1. Substitute s=jw in GOL(s)
2. Plot GOL(jw) in the complex plane
3. Count encirclements of (-1,0) in the clockwise direction
Nyquist Criterion
Consider the transfer function
and the P controller
G s
e
s s
s
( )
( )( . )
.

 

5
1 0 5 1
0 1
( ) 3.2
c
G s 

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pc-lec4.1.pptx pid controller presentation

  • 2. Transfer Function for a PID Controller Ideal PID : Real PID : Derivative Kick: To avoid sudden jump of output due to setpoint change, sensor output is used in place of error term, i.e, 0 0 ( ) 1 ( ) ( ) ( ) t s c D I dy t c t c K e t e d dt               
  • 3. Direct / Reverse acting controller • What will be the sign of the controller gain? Fout Fin L LC LT
  • 4. Guidelines for Selecting Direct and Reverse Acting PID’s • Consider a direct acting final control element to be positive and reverse to be negative. • If the sign of the product of the final control element and the process gain is positive, use the reverse acting PID algorithm. • If the sign of the product is negative, use the direct acting PID algorithm • If control signal goes to a control valve with a valve positioner, the actuator is considered direct acting.
  • 5. Level Control Example • Process gain is positive because when flow in is increased, the level increases. • If the final control element is direct acting, use reverse acting PID. • For reverse acting final control element, use direct acting PID. Fout Fin L LC LT
  • 6. Level Control Example Fout Fin L LC LT • Process gain is negative because when flow out is increased, the level decreases. • If the final control element is direct acting, use direct acting PID. • For reverse acting final control element, use reverse acting PID.
  • 7. General Feedback Control Loop GP(s) Ga(s) GC(s) KS GS(s) Gd(s) d(s) ysp(s) + - + + u(s) y(s) c(s) e(s) yS(s) 1 ) ( ) ( ) ( ) ( 1 ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) (     s G s G s G s G s G s G s G s G s G s G s G K s y s y c c s c a p c a p S sp Characteristic Polynomial : 1 + GOL = 0 or
  • 8. Controller actions on feedback dynamics Process G(s) : Controller : Proportional, ; Matlab: s=tf(‘s’); g=1/(s+1)^3; step(g); hold on for kc=[0.5:0.5:2], gcl=feedback(kc*g,1); step(gcl); end
  • 9. Proportional Control Important points: • proportional feedback does not change the order of the system • started with a first order process • closed-loop process also first order • order of characteristic polynomial is invariant under proportional feedback • speed of response of closed-loop process is directly affected by controller gain • increasing controller gain reduces the closed-loop time constant • In general, proportional feedback • reduces (does not eliminate) offset • speeds up response • for oscillatory processes, makes closed-loop process more oscillatory
  • 10. Controller actions on feedback dynamics Process G(s) : Controller : PI (I varying) ; Matlab: figure; hold on; kc=2; for Ti=[2:1:5], gc=tf(kc*[1,1/Ti],[1,0]); gcl=feedback(gc*g,1); step(gcl); end
  • 11. Proporional - Integral Control Important points: • integral action increases order of the system in closed-loop • integral action eliminates offset • integral action • should be small compared to proportional action • tuned to slowly eliminate offset • can increase or cause oscillation • can be de-stabilizing • PI controller has two tuning parameters that can independently affect • speed of response • Nature of response (oscillation) • PI is the most widely used controller in industry • optimal structure for first order processes
  • 12. Controller actions on feedback dynamics Process G(s) : Controller : PD, ; Matlab: figure; hold on; kc=2; for Td=[0:0.2:0.8], gc=tf(kc*[Td,1],[1]); gcl=feedback(gc*g,1); step(gcl); end
  • 13. Proportional Derivative Important Points: • derivative action does not increase the order of the system • Used to compensate for trends in output • measure of speed of error signal change • provides predictive or anticipatory action • adding derivative action affects the period of oscillation of the process • good for disturbance rejection • poor for tracking • derivative action • should be small compared to integral action • has a stabilizing influence • difficult to use for noisy signals • usually modified in practical implementation
  • 14. PID control (Setpoint Tracking or Servo Control)
  • 16. Closed-loop Stability Every control problem involves a consideration of closed- loop stability General concepts: BIBO Stability: “ An (unconstrained) linear system is said to be stable if the output response is bounded for all bounded inputs. Otherwise it is unstable.” Comments: • Stability is much easier to prove than instability • This is just one type of stability
  • 17. Closed-loop Stability General Stability criterion: “ A closed-loop feedback control system is stable if and only if all roots of the characteristic polynomial (1+ GOL=0) are negative or have negative real parts. Otherwise, the system is unstable.” • Unstable region is the right half plane of the complex plane. • Valid for any linear systems. • Underlying system is almost always nonlinear so stability holds only locally. Moving away from the point of linearization may cause instability
  • 18. Stability Analysis Methods Problem reduces to finding roots of a polynomial Traditional: 1. Routh array: • Test for positivity of roots of a polynomial 2. Direct substitution • Complex axis separates stable and unstable regions • Find controller gain that yields purely complex roots 3. Root locus diagram • Vary location of poles as controller gain is varied • Of limited use • Bode stability criteria • Niquist Stability criteria
  • 19. Closed-loop stability Routh array for a polynomial equation is where Elements of left column must be positive to have roots with negative real parts a s a s a s a n n n n        1 1 1 0 0  a a a a a a b b b c c z n n n n n n      2 4 1 3 5 1 2 3 1 2 1      1 2 3 4 1  n  b a a a a a b a a a a a c b a b a b c b a b a b n n n n n n n n n n n n n n 1 1 2 3 1 2 1 4 5 1 1 1 3 2 1 1 2 1 5 3 1 1                     , , , ,  
  • 20. Example: Routh Array Characteristic polynomial Polynomial Coefficients Routh Array • Closed-loop system is unstable 2 36 1 49 0 58 1 21 0 42 0 78 0 5 4 3 2 . . . . . . s s s s s       a a a a a a b b b c c d d e 5 3 1 4 2 0 1 2 3 1 2 1 2 1 2 36 0 58 0 42 1 49 1 21 0 78 2 50 0 82 0 0 72 0 78 1 89 0 0 78 ( . ) ( . ) ( . ) ( . ) ( . ) ( . ) ( . ) ( . ) ( ) ( . ) ( . ) ( . ) ( ) ( . )    a a a a a a 5 4 3 2 1 0 2 36 1 49 0 58 1 21 0 42 0 78        . , . , . , . , . , . 1 2 3 4 5 6
  • 21. Direct Substitution • Technique to find gain value that de-stabilizes the system. • Observation: Process becomes unstable when poles appear on right half plane Find value of Kc that yields purely complex poles • Strategy: • Start with characteristic polynomial • Write characteristic equation: • Substitute for complex pole (s=jw) • Solve for Kc and w q j K r j c ( ) ( )    0   ( ) 1 ( ) ( ) ( ) 1 c a p s c r s K G s G s G s K q s    q s K r s c ( ) ( )  0
  • 22. Example: Direct Substitution Characteristic equation Substitution for s=jw Real Part : Complex Part: • System is unstable if 1 1 0 5 0 5 0 75 0 0 5 0 5 0 75 0 0 5 0 5 0 75 0 3 2 3 2 3 2                   K s s s s s s s K s K s s K s K c c c c c . . . . . . . ( . ) ( . ) ( ) . ( ) ( . ) ( . ) . ( . ) ( . ) j j K j K j K j K c c c c       3 2 3 2 0 5 0 5 0 75 0 0 5 0 5 0 75 0                  0 5 0 75 0 2 . .  Kc ( . ) Kc    0 5 0 3                  K K c c 0 5 0 75 0 5 0 75 0 5 0 0 5 0 25 0 2 2 1 2 2 3 2 . . ( . . . ) . . / ,       Kc 1
  • 23. Root Locus Diagram • Old method that consists in plotting roots of characteristic polynomial (closed loop poles) as controller gain is changed. Matlab s=tf(‘s’); G1=1/(s+1); G2=1/(s+2); G3=1/(s+3); G=G1*G2*G3; rlocus(G); rlocfind(G);
  • 24. Frequency Response Process 𝑢=𝐴𝑠𝑖𝑛𝜔𝑡 𝑦=^ 𝐴 sin⁡(𝜔𝑡+𝜙) 0 20 40 60 80 100 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 Sinusoidal Response Time (seconds) Amplitude A Â t Amplitude Ratio (AR) = Â/A Phase lag ( = -t/P*180 The process acts as a “filter” or “amplifier” that attenuates or amplifies the input at frequency . The frequency response of a process G(s) at a specific frequency is a complex number and can be obtained by substituting P
  • 25. Frequency Response • Two ways of representing the frequency response • Bode Plot • Log-Log plot of AR vs and semi-log plot vs • Nyquist Plot • Plot of Re() vs Im() for various values of . • Frequency does not appear explicitly in this plot.
  • 26. Bode Plot 10 -5 10 0 Magnitude (abs) 10 -2 10 -1 10 0 10 1 10 2 -360 -315 -270 -225 -180 -135 -90 -45 0 Phase (deg) Bode Diagram Frequency (rad/s) Crossover Frequency Corner Frequency Meeting pt of LFA and HFA Steady state gain: Bandwidth, , defines the highest frequency at which the process displays no attenuation. It is calculated based on the frequency when amplitude reaches 0.707 K. Roll-off is slope of decaying AR at high frequencies.
  • 28. Bode Stability Criterion Consider open-loop control system 1. Introduce sinusoidal input in setpoint (D(s)=0) and observe sinusoidal output 2. Fix gain such AR=1 and input frequency such that =-180 3. At same time, connect close the loop and set YSP(s)=0 Q: What happens if AR <1, 1 and >1? Open-loop Response to YSP(s) Gp Gc Gs D(s) Y(s) Ys(s) YSP(s) U(s) + - + +
  • 29. Bode Stability Criterion A closed-loop system is unstable if the frequency of the response of the open-loop GOL has an amplitude ratio greater than one at the critical frequency. Otherwise it is stable. Strategy: 1. Solve for w in 2. Calculate AR arg( ( )) G j OL     AR G j OL  ( ) 
  • 30. Bode Stability Criterion To check for stability: 1. Compute open-loop transfer function 2. Solve for w in f=-p 3. Evaluate AR at w 4. If AR>1 then process is unstable Find ultimate gain: 1. Compute open-loop transfer function without controller gain 2. Solve for w in f=-p 3. Evaluate AR at w 4. Let K AR cu  1
  • 31. Bode Criterion Consider the transfer function and controller - Open-loop transfer function - Amplitude ratio and phase shift - At f=-p, w=1.4128, AR=6.746 G s e s s s ( ) ( )( . ) .     5 1 0 5 1 0 1 G s s c ( ) . .         0 4 1 1 0 1 G s e s s s OL s ( ) ( )( . ) . . .            5 1 0 5 1 0 4 1 1 0 1 0 1 AR                   5 1 1 1 0 25 0 4 1 1 0 01 0 1 0 5 1 0 1 2 2 2 1 1 1         . . . . tan ( ) tan ( . ) tan .
  • 32. Bode Stability • Phase Crossover frequency (is the frequency at which phase lag is 1800 . • Gain Crossover frequency () is the frequency at which AR = 1 • Gain Margin (GM) is the amount of gain required for the AR to reach 1 at phase crossover frequency. GM=1/ARC , where ARC is the Amplitude ratio at gain crossover frequency. • Phase Margin (PM) is the amount of phase difference required for phase lag to reach 1800 at gain crossover frequency. PM=180+ where is phase lag at phase crossover frequency.
  • 33. Gain Margin and Phase Margin dB=20 log10AR Wcg is the frequency where the gain margin is measured, which is a -180° phase crossing frequency. Wcp is the frequency where the phase margin is measured, which is a 0-dB gain crossing frequency.
  • 34. Nyquist Stability Criterion If N is the number of times that the Nyquist plot encircles the point (-1,0) in the complex plane in the clockwise direction, and P is the number of open-loop poles of GOL that lie in the right- half plane, then Z=N+P is the number of unstable roots of the closed-loop characteristic equation. Strategy 1. Substitute s=jw in GOL(s) 2. Plot GOL(jw) in the complex plane 3. Count encirclements of (-1,0) in the clockwise direction
  • 35. Nyquist Criterion Consider the transfer function and the P controller G s e s s s ( ) ( )( . ) .     5 1 0 5 1 0 1 ( ) 3.2 c G s 