che / met 433
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ChE / MET 433. 4 Apr 12. Feedback Controller Tuning: (General Approaches). Simple criteria; i.e QAD via ZN I, t r , etc e asy, simple, do on existing process multiple solutions Time integral performance criteria ISEintegral square error IAEintegral absolute value error - PowerPoint PPT PresentationTRANSCRIPT
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ChE / MET 433
4 Apr 12
Feedback Controller Tuning: (General Approaches)
1) Simple criteria; i.e QAD via ZN I, tr, etc• easy, simple, do on existing process• multiple solutions
2) Time integral performance criteria• ISE integral square error• IAE integral absolute value error• ITAE integral time weighted average error
3) Semi-empirical rules• FOPDT (ZN II)• Cohen-Coon
4) ATV, or Autotuning5) Trial and error6) Rules of thumb
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• Select the tuning criterion for the control loop.• Apply filtering to the sensor reading• Determine if the control system is fast or slow
responding.– For fast responding, field tune (trail-and-error)– For slow responding, apply ATV-based tuning
Trial and Error (field tuning)*
* J.B. Riggs, & M.N. Karim Chemical and Bio-Process Control, 3rd ed. (2006)
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• Turn off integral and derivative action.• Make initial estimate of Kc based on process knowledge.• Using setpoint changes, increase Kc until tuning criterion
is met
Time
y s
a b
c
• Decrease Kc by 10%.• Make initial estimate of tI (i.e., tI=5tp).• Reduce tI until offset is eliminated• Check that proper amount of Kc and tI are used.
Time
y s
a
b
c
4
Trial and Error (field tuning)*
* J.B. Riggs, & M.N. Karim Chemical and Bio-Process Control, 3rd ed. (2006)
Kc
tI
5
Kc and tI levels good?
Feedback Controller Tuning: (General Approaches)
1) Simple criteria; i.e QAD via ZN I, tr, etc• easy, simple, do on existing process• multiple solutions
2) Time integral performance criteria• ISE integral square error• IAE integral absolute value error• ITAE integral time weighted average error
3) Semi-empirical rules• FOPDT (ZN II)• Cohen-Coon
4) ATV, or Autotuning5) Trial and error6) Rules of thumb
6
7
Rules of Thumb
• Flow Loops: typically PI controllers; PB ~ 150;• Level Loops: PI for tight control; P for multiple tanks in series;• Pressure Loops: can be fast or slow (like P control by controlling
condenser)• Temperature Loops: typically moderately slow; typically might use PID
controller; PB fairly low (depends on gains); integral time on order of process time constant, with faster process derivative time ~ ¼ the process time constant.
* D.A.Coggan, ed., Fundamentals of Industrial Control, 2nd ed., ISA, NC (2005)
*
smallerbecanIt
min1.0It
** W.L.Luyben, Process Modeling, Simulation and Control for Chemical Engineers, 2nd ed., McGraw-Hill (1990)
**
sec sec
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Higher Order Process
Feedback Controller Tuning: (General Approaches)
1) Simple criteria; i.e QAD via ZN I, tr, etc• easy, simple, do on existing process• multiple solutions
2) Time integral performance criteria• ISE integral square error• IAE integral absolute value error• ITAE integral time weighted average error
3) Semi-empirical rules• FOPDT (ZN II)• Cohen-Coon
4) ATV, or Autotuning5) Trial and error6) Rules of thumb
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Feedback Control• Design
Disturbances:• Load• Setpoint
Questions:• Type of controller to use?• How select best adjustable parameters?• Performance criteria?
Guidelines:• Define performance.• Obtain “best” parameters, for• Select controller with “best” performance.
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DICK tt ,,
Feed Back Control• PID controllersProportional:• Accelerates response• Offset
Integral:• Eliminates offset• Sluggish responses• If increase Kc, more oscillations -> unstable?
Derivative:• “Anticipates” future error• Stabilizing effect• Noise problem
Controller with “best” performance.• P – only if can• PI – eliminate offset• PID – speed up response of sluggish
systems (T, comp, control; multi-capacity systems)
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Examples:
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13
14
15
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Controllers:P-Only:
sMcG
sE
)()( tctrKmtm c cKsEsM
)(
P-I Controller:
sK
sEsM
Ic t
11)(
dtteKteKmtmI
cc )()(
t
P-I-D Controller:
ss
KsEsM
DI
c tt
11)(
dt
teddtteteKmtm DI
c)()(1)( t
t
Dt Derivative (rate) time [=] time
Chapter 5 ~ p 183
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Derivative Action:
P-I-D Controller:
dt
teddtteteKmtm DI
c)()(1)( t
t
t
)(tR
)(tC
A
dttCdslope )(
t
)(tR
)()(tCte
A
dttedslope )(
)(te
)(tC
dt
tCddtteteKmtm DI
c)()(1)( t
t
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Derivative Action:
Another potential problem: noise
t
)(tR
)()(tCte
A
slope
)(te
)(tC1s
sfilterD
D
tt
2.005.0 small
Derivative action:
PID
• Reduces overshoot• Reduces oscillations• Recommended for slow/sluggish processes (speed up
control)
Advantages:
• Susceptible to noise• Filtering (or averaging PV) introduces delay• 3rd tuning parameter
Disadvantages:
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PID ControlPID Tuning• Tune for PI• Derivative:• Add in tD • Minimum response time• tD initial = Tu/8• Adjust Kc and tI by same factor (%)• Check response has correct level of integral action
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PS: Try PID for HE process on Loop Pro Developer
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Rules of Thumb
• Flow Loops: typically PI controllers; PB ~ 150;• Level Loops: PI for tight control; P for multiple tanks in series;• Pressure Loops: can be fast or slow (like P control by controlling
condenser)• Temperature Loops: typically moderately slow; typically might use PID
controller; PB fairly low (depends on gains); integral time on order of process time constant, with faster process derivative time ~ ¼ the process time constant.
* D.A.Coggan, ed., Fundamentals of Industrial Control, 2nd ed., ISA, NC (2005)
*
smallerbecanIt
min1.0It
** W.L.Luyben, Process Modeling, Simulation and Control for Chemical Engineers, 2nd ed., McGraw-Hill (1990)
**
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ChE / MET 433