RE/ Process Control Loop Analysis Loop-Tag

Saturday, April 20, 2019

Company name

Company address

RE/ Process control loop analysis Loop-Tag

Dear Sir,

We submit this report on the loop Loop-Tag. This analysis should help you improve the performance, organize maintenance and update your information.

Please call us with questions.

Regards,

ExperTune Inc.

LoopReport.docPage 1 of 1

Legend

Initial Tests

Automatic Mode
Manual mode
Notes:

Hysteresis Check

Found / Acceptable values
Hysteresis / 0.528 % / less than 1%
from 1 % to 2%
more than 3% / ideal
acceptable
to be checked
Gain / 0.822 / less than 0.5
from 0.5 to 2
more than 3 / too small
ideal
too high
Noise / 0.873 % / less than 3% / acceptable
Valve: /
Note: / Enter your valve recommendations here.

If your hysteresis is more than 1% for valves with positioners or 3% for valves without positioners you should consider repairing or changing equipment to reduce hysteresis and improve control. Often, the addition of a valve positioner will correct the problem.

With a sticky valve, the air signal to the valve will have to change by an amount equal to the hysteresis before the valve stem will move. Once the valve has begun to move in one direction it will continue to move if the air signal keeps moving in the same direction. When the air signal reverses direction, the valve will not move until the air signal has changed in the new direction by an amount equal to the hysteresis.

Hysteresis is not limited to valves, it is also present in mechanical linkages, and can have other sources, but valves are the most typical sources.

Stiction Check

Found / Acceptable values
Stiction / Stiction is less than 1% / less than .2%
more than .3% / ideal
to be checked
CO High / 61
CO Low / 60
Valve: /
Note: / Enter your valve recommendations here.

In many processes, 0.5 % of stiction is too much. Stiction guarantees cycling and variability. Stiction is much more harmful than the other valve problems. For example, hysteresis is undesirable, but usually not really a problem. Another example is the valve characteristic, which can be compensated by a non-linear function inserted in the controller output or in the positioner.

Linearity

Linearity /
Notes / Loop requires characterization or MUST be detuned. The process gain GP varies from 0.283 to 1.96; the ratio of these values is 6.92. This ratio should be under 2 and the process gain values should be between .5 and 3.

Many control loops are difficult to tune because they are non-linear. This means that the process gain changes as a function of the measurement or controller output. Without any linearization, the controller will need to be tuned for the condition when the process gain is the highest. This results in sluggish tuning everywhere else.

Linearizing these loops will improve control since the controller will be better tuned over the complete operating range. With a characterizer, you may be able to get uniform performance across the entire range of your process - so you can run your production at its optimum rather than de-tuning for oscillations.

Asymmetry

Process Model With Increasing PV
/ Process Model With Decreasing PV

Asymmetry /
Notes: / Enter Your Asymmetry Description Here

Compare PID tuning or models identified with the ExperTune Process Modeler. Does the process respond differently in the up direction versus the down? If so, can you reduce or eliminate the discrepancy? If not, then you must use the more conservative tuning.

To determine the tuning parameters and the appropriate filter, use the worst case: least aggressive tuning or worst model. The worst model is one with the largest dead time and a highest process gain.

Test Chosen To Compute Tuning Parameters tsampling : 0.5sec

Note: This part of the test must represent the worst situation to ensure the loop stability. The worst case is a high process gain GP, a long dead time Tdand a small time constant Tc.

Bode Plot

Tuning Parameters

Tuning Parameters, Performance, And Robustness

Process model found
/ Old and new tuning parameters
(fastest response)
Current / New
P / 50 / 220
I / 35 / 4.6
D / 0 / .52
F / 0 / .026
RRT / 17 / 49
Robustness / Performance Indices (From current to new)
/ Performance Increase / 73%
Robustness Increase / 294%
Valve Travel Index (based on noise simulation) / 118%
Valve Reversal Index (based on noise simulation) / -4.59%
Response of the loop to a set-point change / Response of the loop to a disturbance or a load change
Parameters /
Notes / Initial battery of tests
Loop Summary Table
Notes

Performance Indices

Performance Increase: The Performance Increase shows how much better your plant responds to upsets with the new tuning. Usually the Performance Increase is directly proportional to the money you can save using the new tuning. With poor tuning, an upset in the direction towards expensive results causes you to give away product. Or, a load causes off-spec product. With better tuning you can give away less expensive ingredients while staying on spec.

Robustness Increase: This is the percent that the robustness improves with the new tuning. It is based on comparing the new and current tuning. If the loop is less robust with the new tuning, then the Robustness Increase will be negative. You can use the Robustness Increase as a quick and rough way of assigning a numerical value to the change in robustness from current to new settings. If either loop is unstable, the Robustness Increase will show N/A.

Valve travel and reversal indices: Use these values to predict valve wear by comparing current to new. The less controller output travel and direction changes, the less valve wear. The Valve Travel Index is the percent improvement in controller output travel from current to new. If the new PID tuning parameters (and filter) result in more travel than the current ones, the Valve Travel Index will be negative. The Valve Reversal Index is the percent improvement in controller output reversals from current to new. If the new PID tuning parameters (and filter) result in more reversals than the current ones, the Valve Reversal Index will be negative.

Robustness Plot

There is always a trade-off between tuning the loop tightly, and robustness or sensitivity to the process changing. If tuned too fast, a small change in the process could cause the loop to be unstable. Use the robustness plot to assess this tradeoff. Robustness plots graphically show the tradeoff between tight tuning and stability

The two axis of the plot are process gain and dead time. The plot has a region of stability and a region of instability. The solid (red and blue) lines on the robustness plot are the limit of stability. To the right and above the solid lines (higher gains and dead times) the closed loop process is unstable. To the left and below the solid lines, the closed loop system is stable. There is a cross in the center of the blue line trapezoidal-like figure. This cross is at the actual process gain and dead time. On the graph, moving away from the cross shows what happens when gain and dead time changes. Process gain and controller gain changes have the same effect on closed loop system stability.

The blue line is for the current PID tuning. The red line is for the new PID parameters. Generally, a safety factor or divisor of 2 is "reasonable" for a loop. These points are represented by the vertices of the blue line "box" in the robustness plot. Use it as a design aid. For practical system stability keep the limit of stability line outside the "box". The vertices are connected by lines that are straight on a log log plot.

Time Line Analysis

Time Line Analysis
Notes
Time Line Items / Values
Sample Interval / 0.5
Filter Time / 0.054
Derivative Time / 1.1
Dead Time / 3
Equivalent Dead Time / 5.3
Integral Time / 4.1
Lag Time / 2.3
Relative Response Time (RRT) / 43
Evaluation Ratios / Values
Dead Time / Sample Interval / 6
Filter Time / Derivative / 0.049
Controller Integral / Derivative / 3.7
Filter / Dead Time / 0.01
Evaluated Time Items / Evaluations
Sample Interval to Process Dead Time / Caution: Better if range greater than 9
PV Filter to Controller Derivative / Excellent
Controller Derivative to Controller Integral / OK
PV Filter to Process Dead Time / OK

Performance Evaluation

Performance Evaluation
Notes

Closed Loop Before and After

Before / After

Set point change

Statistical analysis

Histogram
Note :
Power Spectral - Before
Note :
Power Spectral - After
Note :
Auto or Cross Correlation - Before
Note :
Auto or Cross Correlation - After
Note :

Conclusions And Recommendations

Enter your conclusions here.

To Do

Valve / / Hysteresis / X.X % / Gain / X.X
Enter your valve recommendations here.
Linearity / / Linearity description. .
Asymmetry / / Enter Your Asymmetry Description Here.
PID parameters / / Your Loop Notes are copied here.

Conclusions And Recommendations

Enter your conclusions here.

OK / Equipment performing well
CF / Values configured at the plant
MO / To be modified
VM / Should be checked and analyzed more
RL / Should be repaired in the plant
RA / To be repaired (during next shut-down)
N/A / Not applicable

ExperTune Inc.

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