© ABB Corporate Research Insert image here Control Performance Monitoring Alf Isaksson, Alexander...

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© ABB Corporate Research Insert image here Insert image here Insert image here Control Performance Monitoring Alf Isaksson, Alexander Horch ABB Corporate Research PROST Seminar 22 January 2002

Transcript of © ABB Corporate Research Insert image here Control Performance Monitoring Alf Isaksson, Alexander...

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Control Performance Monitoring

Alf Isaksson, Alexander Horch

ABB Corporate Research

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 auto-correlation function.

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Stattin index: Compare areas between zero crossings

A0 A1

B0

B1

t0 t1 t2 t3 t4

e(t)

0 1

0 1

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Oscillation index

0.88 0.25Controller re-tuned

0 = no oscillation, 1 = perfect osc.

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Oscillation index trend plot

days

index

Valve IP converter replaced

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Major advantage: correlation analysis

0 0.2 0.4 0.6 0.8 1

0

0.2

0.4

0.6

0.8

1

osci

llatio

n lo

op 2

oscillation loop 1

Conclusion:Conclusion:

The loops The loops interact. One of interact. One of them is likely to them is likely to cause both cause both oscillations oscillations

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Potential causes are...

F

FC

static friction

cycling load

tight tuning

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If the cause is stiction...

process output

control signalcross-correlation

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If the cause is NOT stiction...

process output

control signalcross correlation

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Stiction diagnosis

New method by Horch (1999) which utilizes that

when stiction in valve, process variable and control signal have odd cross-correlation

when ”not stiction” the signals are such that the cross-correlation is even (due to negative feedback)

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Example: two coupled loops

F

FC

Q

QC

water

pulp

Stiction

O.K.

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Example cont’dda

ta

concentration loop flow loop

cros

s-co

rr.

Diagnosis: stiction no stiction

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Important assumptions

Cross-correlation

method O.K.

O

Oscillation detectedSelf-regulating process

dtte )(

Integral action

No compressible media

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Example II: integrating plant

no stictionno stiction

two different level control loops

no stictionno stictionstictionstiction

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CCF-method useless for integrating plants!

Integration destroys the specific correlation in the stiction case.

CCF is even, no matter if stiction or not.

Re-calculation (differentiation) does not solve the problem

level control loop

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Idea!

Look for discontinuities in the data!

...

...‘Second derivative is infinite’

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1.) Differentiate the process output!

stiction

Y

dy

dt

d2ydt2

no stiction

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3a.) Histogram (ideally)

no stiction

d2y

dt2

stiction

d2y

dt2

)(

122 xA

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3b.) Histogram (noise & filter)

no stiction

d2y

dt2

stiction

d2y

dt2

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Level control with stiction

MSE: 0.97 2.01

d2y

dt2

y(t)

stiction

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Level control without stiction

MSE: 1.17 0.46

y(t) d2y

dt2

no stiction

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Use Camel method also for self-regulating processes!

stiction no stiction

Y

dy

dt

d2ydt2

Y

Y’

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Detect too large variance (too large 2-sigma)

Is this good or bad?

Basic problem: 2σ

-2σ

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Performance index

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)

• Introduce a control performance measure:

Current varianceTheoretically opt

variance

Ip =

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Before:

After:

Modified Index:

2.11

1.07

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Commercial tools / suppliers ...

LoopMD

KCL-CoPA

ABB

LoopAnalyst PROTUNER™

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LATTS – Loop Auditing and Tuning Tool Suite

Process model identification

PID controller tuning

Loop auditing

Part of ABB Industrial IT concept and uses the new Aspect Integrator Platform (AIP).

Consists of three Aspects:

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Process Model Identification Aspect

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PID Controller Tuning Aspect

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Auditing Aspect

Computes 21 different quantities/indices. For example:

Control error standard deviation

Oscillation index

Stiction diagnosis (correlation)

Stiction diagnosis (histogram)

Modified Harris index

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Auditing Aspect cont’d

Combines these indices to test a number of hypotheses, such as

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

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Conclusions

New ABB Product LATTS under Beta testing right now. Product release approximately June 2002.

Methods exist for non-invasive

Oscillation detection

Stiction diagnosis

Minimum variance benchmark

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Future work (industrial as well as academic)

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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