Alf Isaksson, Alexander Horch
Control Performance
Monitoring
ABB Corporate Research
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PROST Seminar 22 January 2002
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Goal: detect and diagnose malfunctioning control loops
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Bad control manifests itself as
oscillation
or too high variance
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Methods needed to

detect oscillations

diagnose oscillations

determine of variance is too large
Since there are hundreds of loops
methods should be automatic
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Oscillation detection

Hägglund (1995). Consider areas between zero
crossings (count if large enough).

Stattin and Forsman (1998). Based on same idea,
easier to use.

Seborg and Miao (1999). Damping ratio of autocorrelation function.
Stattin index: Compare areas between zero crossings
e(t)
0
A0
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t0
B1
B0
0
t1
1
A1
1
t2
t3
t4
Oscillation index
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0 = no oscillation, 1 = perfect osc.
0.88
0.25
Controller re-tuned
Oscillation index trend plot
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index
Valve IP
converter
replaced
days
Major advantage: correlation analysis
oscillation loop 2
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1
Conclusion:
0.8
The loops
interact. One of
them is likely to
cause both
oscillations
0.6
0.4
0.2
0
0
0.2
0.4
0.6
0.8
oscillation loop 1
1
Potential causes are...
cycling load
static friction
F
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FC
tight tuning
If the cause is stiction...
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process output
control signal
cross-correlation
If the cause is NOT stiction...
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process output
cross correlation
control signal
Stiction diagnosis

New method by Horch (1999) which utilizes that

when stiction in valve, process variable and
control signal have odd cross-correlation
”not stiction” the signals are such that
the cross-correlation is even (due to negative
feedback)
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 when
Example: two coupled loops
QC
Stiction
water
Q
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pulp
O.K.
F
FC
Example cont’d
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concentration loop
Diagnosis: stiction
flow loop
no stiction
Important assumptions
O
Self-regulating process
Oscillation detected
Crosscorrelation
method O.K.
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Integral action
No compressible media
e
(
t
)
dt

Example II: integrating plant
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two different level control loops
stiction
no stiction
no stiction
CCF-method useless for integrating plants!
level control loop
Integration destroys the
specific correlation in the
stiction case.
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CCF is even, no matter if
stiction or not.
Re-calculation
(differentiation) does not
solve the problem
Idea!
Look for discontinuities in the data!
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...
...
‘Second derivative is infinite’
1.) Differentiate the process output!
Y
dy
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dt
d2y
dt2
stiction
no stiction
3a.) Histogram (ideally)
d2y
dt2
stiction
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d2y
dt2
no
stiction
1
 ( A2  x 2 )
3b.) Histogram (noise & filter)
d2y
dt2
stiction
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d2y
dt2
no
stiction
Level control with stiction
d2y
y(t)
dt2
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stiction
MSE:
0.97
2.01
Level control without stiction
d2y
y(t)
dt2
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no stiction
MSE:
1.17
0.46
Use Camel method also for self-regulating processes!
Y
Y
dy
dt
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Y’
d2y
dt2
stiction
no stiction
Detect too large variance (too large 2-sigma)
Basic problem:
2σ
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-2σ
Is this good or bad?
Performance index
• Introduce a control performance measure:
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Ip =
Current variance
Theoretically opt variance

Possible to calculate denominator from
normal operating data given knowledge of
process time delay (deadtime).

Proposed by Harris (1989).

Modification presented in Horch and Isaksson
(1999)
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Modified Index:
Before:
2.11
After:
1.07
Commercial tools / suppliers ...
ABB
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KCL-CoPA
LoopAnalyst
PROTUNER™
LoopMD
LATTS – Loop Auditing and Tuning Tool Suite
Part of ABB Industrial IT concept and uses the
new Aspect Integrator Platform (AIP).
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Consists of three Aspects:

Process model identification

PID controller tuning

Loop auditing
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Process Model Identification Aspect
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PID Controller Tuning Aspect
Auditing Aspect
 Computes 21 different quantities/indices. For
example:
 Control error standard deviation

Oscillation index

Stiction diagnosis (correlation)
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 Stiction diagnosis (histogram)
 Modified Harris index
Auditing Aspect cont’d

Combines these indices to test a
number of hypotheses, such as
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 Acceptable
performance

Possible valve problem

Sluggish tuning
The result is summarized in a report, either
as a text file or in Internet Explorer
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Auditing -- Index trend plots
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Auditing -- Report
Conclusions

Methods exist for non-invasive
 Oscillation detection
 Stiction diagnosis
 Minimum variance benchmark
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
New ABB Product LATTS under Beta testing
right now. Product release approximately June
2002.
Future work (industrial as well as academic)


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detection and diagnosis of mill-wide oscillations
distinction of linearly and non-linearly caused
oscillations
 performance assessment based on full process
model (event-triggered estimation)
 application of multivariable performance index
 performance monitoring of MPC loops
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