exceptional opportunities in process control
DESCRIPTION
Exceptional Opportunities in Process Control presented by Greg McMillan at ISA Boston Section's October-2009 meeting.TRANSCRIPT
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Standards
Certification
Education & Training
Publishing
Conferences & Exhibits
ISA Boston Section Oct 20, 2009
Exceptional Process Control Opportunities
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Welcome
• Gregory K. McMillan – I worked 33 years for Monsanto and its spin-off Solutia Inc first as an
instrument engineer and then as specialist in process modeling and control. I have written humorous and serious technical books for ISA. Good Tuning - a Pocket Guide, Advanced Control Unleashed, and The Funnier Side of Retirement for Engineers and People of the Technical Persuasion received the Raymond D. Malloy award for best selling books. Presently I contract part time as a principal consultant to Emerson Process Management in Austin Texas via CDI Process and Industrial. My latest technical tips are at: http://ModelingandControl.com
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Exceptional Opportunities (Covered Tonight)
• Wireless Measurement and Control• Sample Time • Integrating Process (e.g. Batch) Controller Tuning• Precision Control Valves for pH Control• Open Loop Backup (e.g. Compressor Surge & RCRA pH)• Expertise Retention and Development• Opportunities from Today’s Interviews
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Exceptional Opportunities (Future Entries on http://ModelingandControl.com )
• Batch Profile Control• Adaptive Feedback Control and Linearization• Adaptive Feedforward Control and Linearization• Full Throttle Set Point Response for Batch and Startup• Controller Output Overdrive• Dynamic Reset Limit• Fast and Intermittent Disturbances and Discontinuities• Integration of Loop, Process, and Maintenance Data• Root Cause Analysis• Data Visualization• Virtual Tool for Learning and Exploring Opportunities• Peak Control
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Wireless Opportunities
• Wireless temperatures and differential pressures for packed absorber and distillation column hot spot and flow distribution analysis and control
• Wireless temperatures and differential pressures for fluidized bed reactor hot spot and flow distribution analysis and control
• Wireless pressures to debottleneck piping systems, monitor process filter operation, and track down the direction and source of pressure disturbances
• Wireless temperatures and flows to debottleneck coolant systems
• Wireless instrumentation to increase the mobility, flexibility, and maintainability of skids for process equipment service such as cleaning and sterilization
• Wireless instrumentation to increase the mobility, flexibility, and maintainability of skids for lab and pilot plant unit operations. (Note: skids are platforms of pre-assembled equipment, piping, and automation to perform unit operations)
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Newest Book - The Latest on Smart and Wireless Instrumentation
Royalties are donated to theUniversity of Texas Research Campus for Energy and Environmental Resources for Development of WirelessInstrumentation and Control
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Traditional and Wireless PID (PIDPLUS)
• PID integral mode is restructured to provide integral action to match the process response in the elapsed time (reset time is set equal to process time constant)
• PID derivative mode is modified to compute a rate of change over the elapsed time from the last new measurement value
• PID reset and rate action are only computed when there is a new value
• PID algorithm with enhanced reset and rate action is termed PIDPLUS
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Control Studies of Glucose Sample Time, Feedforward, and Wireless PID Control
Continuous FF-NoStandard PID
Continuous FF-YesStandard PID
11 hr Sample FF-NoStandard PID
11 hr Sample FF-YesStandard PID
11 hr Sample FF-NoWireless PID
11 hr Sample FF-YesWireless PID
Batch 1 Batch 2 Batch 3 Batch 4 Batch 5 Batch 6
Glucose Concentration
Batch 1: Glucose Probe (Continuous - No Delay) + Feed Forward - No + Standard PIDBatch 2: Glucose Probe (Continuous - No Delay) + Feed Forward - Yes + Standard PIDBatch 3: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - No + Standard PIDBatch 4: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - Yes + Standard PIDBatch 5: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - No + Wireless PIDBatch 6: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - Yes + Wireless PID
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Time (seconds)
Process Variable orController Output (%)
CO
PV
pp
Kp = PV CO
PV
%CO
%PV
dead time
process time constant
Self-regulating process gain (%/%)
Self-Regulating Process Response
pf Lambda (closed loop time constant) is defined in terms of a Lambda factor (f):
Most continuous processes have a self-regulating response (PV lines out in manual)
Response to change in controller output with controller in manual
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CO
PVK p %
%
)( ppfp
ic K
TK
piT
Self-Regulation Process Gain:
Controller Gain
Controller Integral Time
Self-Regulating Process Tuning
p
pi
KK
“Near Integrating” Gain Approximation
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Time (seconds)p
Ki = { [ PV2 t2 ] PV1 t1 ] } CO
CO
ramp rate isPV1 t1
ramp rate isPV2 t2
%CO
%PV
dead time
Integrating process gain (%/sec/%)
Integrating Process Response
Process Variable orController Output (%)
Lambda (closed loop arrest time) is defined in terms of a Lambda factor (f):
if K/
Most batch processes have an integrating response (PV ramps in manual)
Response to change in controller output with controller in manual
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2])/[( pifi
ic KK
TK
pifi KT )/(2
CO
tPVtPVKi %
/%/% 1122
iic KTK
4
The above tuning automatically insures the following inequality is satisfiedto prevent slow rolling oscillations from too low of a gain or integral time.
Integrating Process Gain:
Controller Gain
Controller Integral Time
Integrating Process Tuning
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Process Output (Y)& Process Input (X)
X
p
Kp = Y X(Runaway Process Gain)
YX
Y
ProcessDead Time
Runaway Process Time Constant
Time (t)p’
Y
Noise Band
Acceleration
Exothermic reactors, strong acid-base pH systems, and compressor surge can exhibit a runaway response (PV accelerates in manual)
Runaway Process ResponseRunaway Process Response
Response to change in controller output with controller in manual
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Studies of Reset Factor & Wireless PID for Self-Regulating Process
Wireless PID Wireless PID Wireless PID
Standard PID Standard PID Standard PID
Reset Factor = 0.5 Reset Factor = 1.0 Reset Factor = 2.0
Reset Factor = 0.5 Reset Factor = 1.0 Reset Factor = 2.0
Improvement in stability and control is dramatic for any self-regulating process with analyzer delay
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Studies of Lambda Factor & Wireless PID for Self-Regulating Process
Wireless PID Wireless PID Wireless PID
Standard PID Standard PID Standard PID
Lambda Factor = 1.5 Lambda Factor = 2.0 Lambda Factor = 2.5
Lambda Factor = 1.5 Lambda Factor = 2.0 Lambda Factor = 2.5
Improvement in stability and control is dramatic for any self-regulating process with analyzer delay
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Studies of Reset Factor & Wireless PID for Integrating Process
Reset Factor = 0.5
Wireless PID Wireless PID Wireless PID
Standard PID Standard PID Standard PID
Reset Factor = 1.0 Reset Factor = 2.0
Reset Factor = 0.5 Reset Factor = 1.0 Reset Factor = 2.0
Improvement in stability is significant for any integrating process with analyzer delay
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Studies of Lambda Factor & Wireless PID for Integrating Process
Lambda Factor = 1.5
Wireless PID Wireless PID Wireless PID
Standard PID Standard PID Standard PID
Lambda Factor = 2.0 Lambda Factor = 2.5
Lambda Factor = 1.5 Lambda Factor = 2.0 Lambda Factor = 2.5
Improvement in stability is significant for any integrating process with analyzer delay
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Wireless Portable Bioreactor with a Lab Optimized DCS (Courtesy of Broadley-James)
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Wireless pH Performance on Bioreactor
Wired pH ground noise spike
Temperature compensated wireless pH controlling at 6.9 pH set point
Incredibly tight pH control via 0.001 pH wireless resolution
setting still reduced the number of communications by 60%
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Wireless SUB Temperature Loop Test ResultsWireless SUB Temperature Loop Test Results
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Wireless SUB pH Loop Test ResultsWireless SUB pH Loop Test Results
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Wireless PID Control Conclusions
• Wireless PID and new communication rules can increase battery life• Wireless pH eliminates spikes form ground noise• Wireless PID provides tight control for set point changes• Feedforward of formation rate improves glucose control but does not eliminate
instability for large at-line analyzer sample time• Wireless PIDPLUS dramatically improves the control and stability of any self-
regulating process with large measurement delay (sample delay). The wireless PID is a technological breakthrough for the use at-line analyzers for control
– The Wireless PIDPLUS set point overshoot is negligible for self-regulating processes with large sample delays if controller gain is less than the inverse of process gain
• Wireless PIDPLUS is stable for self-regulating process with large sample delay if controller gain is less than twice the inverse of the process gain
– As the analyzer sample time decreases and approaches the module execution time, it is expected that the wireless PID behaves more like a standard PID
• Wireless PIDPLUS significantly reduces the oscillations of integrating processes but the improvement is not as dramatic as for self-regulating processes
• Integrating processes are much more sensitive than self-regulating processes to increases in sample time, decreases in reset time, and increases in gain
• Detuned controllers (large Lambda Factors), makes loops less sensitive to sample time (see Advanced Application Note 005 “Effect of Sample Time ….”)
• If the controller gain is increased or the wireless resolution setting is made finer, the PIDPLUS can provide tighter control. For a loss of communication, the PIDPLUS offers significantly better performance than a wired traditional PID particularly when rate action and actuator feedback (readback) is used
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Sample Time Guidelines Table
Type of Process Loop Process Deadtime Process Time Constant Practical Sample Time Ultimate Sample Time
Liquid Flow 0.05 - 0.5 sec 0.5 - 5 sec 2 sec 0.1 sec
Gas Flow 0.1 - 0.5 sec 1 - 10 sec 1 sec 0.1 sec
Liquid Pressure* 0.05 - 0.5 sec 0.2 - 1 sec 0.1 sec 0.02 sec
Column Pressure! 1 - 10 sec 10 - 100 sec 10 sec 2 sec
Furnace Pressure* 0.1 - 0.5 sec 0.2 - 20 sec 0.1 sec 0.02 sec
Vessel Pressure! 0.2 - 1 sec 10 - 100 sec 10 sec 1 sec
Surge Control 0.05 - 0.5 sec 0.2 - 10 sec 0.1 sec 0.02 sec
Liquid Level! 0.05 - 0.5 sec 10 - 100000 min 300 sec 60 sec
Exchanger Temperature 0.2 - 2 min 0.5 - 5 min 10 sec 2 sec
Batch Temperature! 1 - 10 min 5 - 100000 min 150 sec 30 sec
Runaway Temperature!! 0.5 - 5 min 1 - 100 min 10 sec 5 sec
Column Temperature 2 - 100 min 10 - 1000 min 300 sec 60 sec
Furnace Temperature 0.2 - 2 min 0.5 - 5 min 10 sec 2 sec
Vessel Temperature 1 - 10 min 5 - 50 min 150 sec 30 sec
Column Composition 1 - 50 min 10 - 1000 min 300 sec 60 sec
Furnace Oxygen 0.2 - 1 min 0.2 - 1 min 10 sec 2 sec
Vessel Composition 0.5 - 5 min 5 - 50 min 150 sec 30 sec
Inline (Static Mixer) pH 2 - 10 sec 2 - 10 sec 2 sec 0.5 sec
Vessel pH 0.5 - 5 min 1 - 50 min 30 sec 5 sec
Practical and Ultimate sample times are for conservative and aggressive tuning, respectively
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Sample Time Guideline Notes
• The term “sample time” is used in the broadest sense as the time between updates in sampled data from digital measurements and controllers and from analyzers The table should be useful for determining whether DCS scan or module execution times, wireless communication time intervals, model predictive control execution time, and at-line analyzer cycle time will affect control system performance.
• * - denotes loop uses a variable speed drive with a negligible dead time, deadband, and resolution limit as the final element. If a control valve or damper is used for these loops, you can multiply the sample times for asterisked items by a factor of 5.
• ! - denotes an integrating response whose integrating process gain is the inverse of the process time constant shown
• !! - denotes a runaway response that can accelerate and reach a point of no return
• For surge control, it assumed that a volume booster has been added to the each of the positioner outputs to reduce the pre-stroke dead time to less than 0.2 seconds. A valve with excessive sticktion and backlash will add significant deadtime to the response to unmeasured disturbances that deteriorates the ultimate limit to possible performance.
• For inline (static mixer) pH control, the largest time constant comes from the sensor lag or the process variable filter time with a nominal value of 5 seconds.
• For the vessel pH control it is assumed the mixing time is less than 30 sec and the reagent delivery time delay is negligible by injection of the reagent into a recirculation line just before it enters the vessel. The lower value for the time constant is for a set point on a steep titration curve that cause the pH to move much faster than for a linear response. The response can look like a runaway as the pH accelerates through the neutral region.
• For level control set point changes, the deadtime observed is usually about 10 times larger than the actual process deadtime due to level measurement sensitivity limits and noise. For unmeasured disturbances the deadtime observed is often about 20 times larger than the actual process deadtime because of the amount of time it takes the controller output to work through the resolution limit and deadband of the control valve.
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Adaptive Controller Tuning of Integrating Process (Batch Temperature)
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Adaptive Controller Models of Integrating Process (Batch Temperature)
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Adaptive Controller Learning Setup of Integrating Process (Batch Temperature)
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Adaptive ControllerGain 40 Reset 500
Output comes off high limit at 36.8 oC
0.30 oC overshoot
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Adaptive ControllerGain 40 Reset 5000
Output comes off high limit at 35.9 oC
0.12 oC overshoot
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Adaptive ControllerGain 40 Reset 10000
0.13 oC overshoot
Output comes off high limit at 36.1 oC
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0.20 oC overshoot
Output comes off high limit at 36.4 oC
Adaptive ControllerGain 40 Reset 15000
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0.11 oC overshoot
Output comes off high limit at 36.1 oC
Adaptive ControllerGain 80 Reset 15000
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Integrating and Runaway Process Tuning
• It is difficult to prevent overshoot in processes without self-regulation• Controller gain adds self-regulation via closed loop response• Examples of integrating processes (ramping response) are
– Liquid and solids level – furnace, column, or vessel pressure – batch composition, pH, or temperature
• Examples of runaway processes (accelerating response) are – exothermic reactor temperature– strong acid - strong base pH– exponential growth phase biomass– compressor speed during surge
• An over drive of the controller output beyond its resting value is needed to reach a set point or compensate for a disturbance
• The maximum allowable controller gain for many integrating processes is well beyond the comfort level of most users. Measurement noise and resolution often sets the practical high limit to the controller gain rather than process dynamics
• Too much reset action (too small of a reset time) cause severe overshoot• A higher controller gain creates more overdrive for small setpoint changes and gets
controller off it’s output limit sooner for large setpoint changes• There is a window of allowable controller gains.
– Instability from too high of a controller gain (not likely for industrial processes)– Slow rolling oscillations from too low of a controller gain (common case) that slowly decay for
integrating processes but can grow for runaway processes till it hits physical limits
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Fundamentals - Effect of Step Size on Small Valve Response
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Control Valve Watch-outs
dead band
Deadband
Stick-Slip is worse near closed position
Signal (%)
0
Stroke (%) Digital positioner
will force valve shut at 0% signal
Pneumatic positionerrequires a negative % signal to close valve
The dead band and stick-slip is greatest near the closed position
Deadband is 5% - 50%without a positioner !
Plugging and laminar flow can occur for low Cv requirements and throttling near the seat
Consider going to reagent dilution. If this is not possible checkout out a laminar flow valve for an extremely low Cv
and pulse width modulation for low lifts
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Fundamentals - Limit Cycle in Flow Loop from Valve Stick-Slip
Controller Output (%)Saw Tooth Oscillation
Process Variable (kpph)Square Wave Oscillation
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Fundamentals - Limit Cycle in Level Loop from Valve Deadband
Manipulated Flow (kpph)Clipped Oscillation
Controller Output (%)Rounded Oscillation
Level (%)
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Nonlinearity - Graphical Deception
0.00000000
2.00000000
4.00000000
6.00000000
8.00000000
10.00000000
12.00000000
14.00000000
0.00000000 0.00050000 0.00100000 0.00150000 0.00200000
3.00000000
4.00000000
5.00000000
6.00000000
7.00000000
8.00000000
9.00000000
10.00000000
11.00000000
0.00099995 0.00099996 0.00099997 0.00099998 0.00099999 0.00100000 0.00100001 0.00100002 0.00100003 0.00100004 0.00100005
14
12
10
8
6
4
2
0
pH
Reagent Influent Ratio
11
10
9
8
7
6
5
4
3
pH
Reagent Influent Ratio
Despite appearances there are no straight lines in a titration curve (zoom in reveals another curve if there are enough data points - a big “IF” in neutral region)
For a strong acid and base the pKa are off-scale and the slope continually changes by a factor of ten for each pH unit deviationfrom neutrality (7 pH at 25 oC)
Yet titration curves are essential for every aspect of pH systemdesign but you must get numerical values and avoid mistakessuch as insufficient data points in the area around the set point
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Effect of Acid and Base Type
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
0.000 0.500 1.000 1.500 2.000
Reagent / Influent
pH Calculated pH
Weak Acid and Strong Base
pka = 4
Figure 3-1d: Weak Acid Titrated with a Weak Base
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
0.000 0.500 1.000 1.500 2.000
Reagent / Influent
pH
Weak Acid and Weak Base
pka = 4
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
0.000 0.500 1.000 1.500 2.000
Reagent / Influent
pH
Strong Acid and Weak Base
pka = 10
Figure 3-1e: Weak 2-Ion Acid Titrated with a Weak 2-Ion Base
0.00
2.00
4.00
6.00
8.00
10.00
12.00
14.00
0.000 0.500 1.000 1.500 2.000
Reagent / Influent
pH
Multiple Weak Acids and Weak Bases
pka = 3
pka = 5
pka = 9
Slope moderatednear each pKa !
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Effect of Mixing Uniformity and Valve Resolution
pH
Reagent to Feed Flow Ratio
4
10
6
8
pH Set Point
Fluctuations or OscillationsIn Flows or Concentrations
Control valve resolution (stick-slip) andmixing uniformity requirements areextraordinary on the steepest slope
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Control Valve Size and Resolution
pH
Reagent FlowInfluent Flow
6
8
Influent pH
B
A
Control BandSet point
BEr =100% Fimax Frmax
Frmax =A Fimax
BEr =100% A
Ss = 0.5 Er
A = distance of center of reagent error band on abscissa from originB = width of allowable reagent error band on abscissa for control band Er = allowable reagent error (%)
Frmax = maximum reagent valve capacity (kg per minute)
Fimax = maximum influent flow (kg per minute)
Ss = allowable stick-slip (resolution limit) (%)
Most reagent control valves are oversized, which increases the limit cycle amplitudefrom stick-slip (resolution) and deadband(integrating processes and cascade loops)
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Demineralized Water pH Titration Curve
Slope
pH
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Demineralized Water pH Control System
Signal characterizers linearize loop via reagent demand control
AY 1-4
AC 1-1
AY 1-3
splitter
AT 1-3
AT 1-2
AT 1-1
AY 1-1
AY 1-2
middlesignal
selector
signalcharacterizer
signalcharacterizer
pH set point
Eductors
FT 1-1
FT 1-2
NaOH Acid
LT 1-5
Tank
Static Mixer
Feed
To other Tank
Downstream system
LC 1-5
From other Tank
To other Tank
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Demineralized Water pH Loop Performance
Start of Step 2(Regeneration)
Start of Step 4(Slow Rinses)
One of many spikes of recirculation pH spikes from stick-slip of water valve
Tank 1 pH for Reagent Demand Control
Tank 1 pH for Conventional pH Control
Influent pH
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Best Practices to Improve Valve Performance
Actuator, valve, and positioner package from a control valve manufacturer Digital positioner tuned for valve package and application Diaphragm actuators where application permits (large valves and high pressure
drops may require piston actuators) Sliding stem (globe) valves where size and fluid permit (large flows and slurries
may require rotary valves) Low stem packing friction Low sealing and seating friction of the closure components Booster(s) on positioner output(s) for large valves on fast loops (e.g.,
compressor anti-surge control) Valve sizing for a throttle range that provides good linearity [4]:
o 5% to 75% (sliding stem globe), o 10o to 60o (v-ball)o 25o to 45o (conventional butterfly)o 5o to 65o (contoured and toothed butterfly)
Online diagnostics and step response tests for small changes in signal Dynamic reset limiting using digital positioner feedback [2]
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Volume Booster with Integral Bypass(Furnace Pressure and Surge Control)
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Port A
Port B
Supply
ZZ
ZZ
ZZ
Z
Control Signal
Digital Valve Controller
Must be functionally tested
before commissioning!
1:1
Bypass
VolumeBooster
Open bypass justenough to ensurea non-oscillatory fast response
Air Supply
High CapacityFilter Regulator
Increase air line size
Increase connection size
Terminal Box
Booster and Positioner Setup(Furnace Pressure and Surge Control)
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Open Loop Backup Configuration
SP_Rate_DN and SP_RATE_UP used to insure fast getaway and slow approach
Open loop backup used for prevention of compressor surge and RCRA pH violation
Open Loop Backup Configuration
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PID Controller Disturbance Response
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Open Loop Backup Disturbance Response
Open Loop Backup