wireless measurement and control - aiche new orleans
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Wireless Measurement and Control - Opportunities for Diagnostics Process Metrics Inferential Measurements and Eliminating Oscillations Presented by Greg McMillan on March 15, 2011.TRANSCRIPT
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AIChE New Orleans Section Meeting March 15, 2011
Wireless Measurement and Control - Opportunities for Diagnostics, Process Metrics, Inferential Measurements, and Eliminating Oscillations
Welcome• Gregory K. McMillan
– Greg is a retired Senior Fellow from Solutia/Monsanto and an ISA Fellow. Greg was an adjunct professor in the Washington University Saint Louis Chemical Engineering Department 2001-2004. Presently, Greg contracts as a consultant in DeltaV R&D via CDI Process & Industrial. Greg received the ISA “Kermit Fischer Environmental” Award for pH control in 1991, the Control Magazine “Engineer of the Year” Award for the Process Industry in 1994, was inducted into the Control “Process Automation Hall of Fame” in 2001, was honored by InTech Magazine in 2003 as one of the most influential innovators in automation, and received the ISA Life Achievement Award in 2010. Greg is the author of numerous books on process control, his most recent being Advanced Temperature Measurement and Control. Greg has been the monthly “Control Talk” columnist for Control magazine since 2002. Greg’s expertise is available on the web site: http://www.modelingandcontrol.com/
Top Ten Things You Don’t Want to Hear on a Startup
• (10) You need the owner to be a little more patient (supplier expert).• (9) Don’t bother with a checkout - just light it up! What is the worst that
can happen?• (8) We didn’t do any simulation or testing. We decided that would spoil
the adventure.• (7) I don’t understand. It fit fine on the drawing.• (6) Cool - This is my first time in a real plant (supplier expert).• (5) I tried to open the valve and nothing happened. Wait! The same valve
on the other reactor just opened.• (4) Should the Variable Frequency Drive smoke like that?• (3) I don’t understand. I am sure I left all your tools and radios in a box
right here.• (2) The CEO is holding on a phone for you.• (1) Boom!!! WHAT was that?!?!
Source: “Final Word on Instrument Upgrade Projects”, Control Talk, Control, Dec 2010http://www.controlglobal.com/articles/2010/InstrumentProjects1012.html
ISA Automation Week - Oct 17-20
Process Automation Hall of Fame Speakers
Charlie CutlerBela LiptakRuss RhinehartGreg McMillanTerry Tolliver
Advances in Smart Measurements Advances in Smart Measurements
• Technological advances in sensing element technology• Integration of multiple measurements• Compensation of application and installation effects• Online device diagnostics• Digital signals with embedded extensive user selected
information• Wireless communication
The out of the box accuracy of modern industrial instrumentation has improved by an order of magnitude. Consider the most common measurement device, the differential pressure transmitter (DP). The 0.25% accuracy of an analog electronic DP has improved to 0.025% accuracy for a smart microprocessor based DP. Furthermore, the analog DP accuracy often deteriorated to 2% when it was moved from the nice bench top setting to service outdoors in a nasty process with all its non-ideal effects of installation, process, and ambient effects [1][16]. A smart DP with its integrated compensation for non-ideal effects will stay close to its inherent 0.025% accuracy. Additionally a smart DP takes 10 years to drift as much as the analog DP did in 1 year.
Smart Transmitter Auxiliary Variables
• The availability of auxiliary process variables in a smart wireless pH transmitter, provide early indicators of performance problems. The use of these variables by online data analytics tools could detect abnormal conditions and predict sensor life.
Smart Transmitter Diagnostic Messages• “Fix Now” and “Fix Soon” alerts are provided along with common
causes and recommended actions
Wireless Opportunities
• Wireless temperatures and differential pressures for packed absorber and distillation column hot spot and flow distribution analysis and control
• Wireless temperatures for finding the column control point with the largest and most symmetrical change in temperature with reflux/feed or steam/feed ratio
• Wireless temperatures for heat transfer coefficient metrics (fouling and frosting)• Wireless temperatures and flows for measurement and control of reaction rate and
crystallization rate from heat transfer (BTU/hr measurement and control)• Wireless temperatures and differential pressures for fluidized bed reactor hot spot
and flow distribution analysis and control• Wireless temperatures and flows to debottleneck coolant systems• Wireless pressures to debottleneck piping systems, monitor process filter operation,
and track down the direction and source of pressure disturbances• Wireless pressures to compute installed control valve characteristic (flow versus
stroke) and variable speed drive installed characteristic (flow versus speed) • Wireless instrumentation to increase the mobility, flexibility, and maintainability of lab
and pilot plant experiments. • Wireless pH and conductivity measurements for
– (1) Selecting the best sensor technology for a wide range of process conditions(2) Eliminating measurement noise(3) Predicting sensor demise(4) Developing process temperature compensation(5) Developing inferential measurements of process concentrations(6) Finding the optimum sensor location
http://www.isa.org/InTechTemplate.cfm?template=/ContentManagement/ContentDisplay.cfm&ContentID=80886
WirelessHART Network Topology
FieldDevice
FieldDevice
FieldDevice
RouterDevice
RouterDevice
FieldDevice
FieldDevice
FieldDevice
GatewayDevice
Plant Automation Network
Plant Automation Application Host
Wireless HART
Handheld
• Wireless Field Devices– Relatively simple - Obeys Network
Manager– All devices are full-function (e.g., must
route)• Adapters
– Provide access to existing HART-enabled Field Devices
– Fully Documented, well defined requirements
• Gateway and Access Points – Allows access to WirelessHART Network
from the Process Automation Network– Gateways can offer multiple Access
Points for increased Bandwidth and Reliability
– Caches measurement and control values– Directly Supports WirelessHART Adapters– Seamless access from existing HART
Applications• Network Manager
– Manages communication bandwidth and routing
– Redundant Network Managers supported – Often embedded in Gateway– Critical to performance of the network
• Handheld– Supports direct communication to field
device– For security, one hop only communication
WirelessHART Features
• Wireless transmitters provide nonintrusive replacement and diagnostics
• Wireless transmitters automatically communicate alerts based on smart diagnostics without interrogation from an automated maintenance system
• Wireless transmitters eliminate the questions of wiring integrity and termination
• Wireless transmitters eliminate ground loops that are difficult to track down
• Network manager optimizes routing to maximize reliability and performance
• Network manager maximizes signal strength and battery life by minimizing the number of hops and preferably using routers and main (line) powered devices
• Network manager minimizes interference by channel hopping and blacklisting
• The standard WirelessHART capability of exception reporting via a resolution setting helps to increase battery life
• WirelessHART control solution, keeps control execution times fast but a new value is communicated as scheduled only if the change in the measurement exceeds the resolution or the elapsed time exceeds the refresh time
• PIDPLUS and new communication rules can reduce communications by 96%
Broadley-James Corporation Bioreactor Setup
• Hyclone 100 liter Single Use Bioreactor (SUB)
• Rosemount WirelessHART gateway and transmitters for measurement and control of pH and temperature. (pressure monitored)
• BioNet lab optimized control system based on DeltaV
Elimination of Ground Noise by Wireless pH Elimination of Ground Noise by Wireless pH
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%
Wireless Bioreactor Adaptive pH Loop TestWireless Bioreactor Adaptive pH Loop Test
University of Texas Pilot Plant for CO2 Research
The Separations Research Program was established at the J.J. Pickle Research Campus in 1984
This cooperative industry/university program performs fundamental research of interest to chemical, biotechnological, petroleum refining, gas processing, pharmaceutical, and food companies.
CO2 removal from stack gas is a focus project for which WirelessHART transmitters are being installed
Wireless Conductivity and pH Lab Setup
• In the UT lab that supports the pilot plant, solvent concentration and loading were varied and the conductivity and pH were wirelessly communicated to the DCS in the control room
Effect of Ions on Conductivity• Conductivity measures the concentration and mobility of ions. Plots
of conductivity versus ion concentration will increase from zero concentration to a maximum as the number of ions in solution increases. The conductivity then falls off to the right of the maximum as the ions get crowded and start to interact or associate (group) reducing the ion mobility.
Effect of Solvent on Conductivity
• Conductivity in the operating range of 25% to 30% by weight solvent is relatively unaffected by solvent concentration
Conductivity Dependence on Solvent Concentration at Constant CO2 Load
0.000
10.000
20.000
30.000
40.000
50.000
60.000
15% 20% 25% 30% 35% 40% 45%
Solvent Concentration (wt%)
Co
nd
uct
ivit
y (m
illiS
iem
ens/
cm)
20 oC
30 oC
40 oC
Effect of CO2 Load on Conductivity
• Conductivity shows good sensitivity to CO2 loading that can be fitted by a straight line whose slope depends upon temperature above 30 oC
Conductivity Dependence on CO2 Load at Constant Solvent Concentration
0.000
5.000
10.000
15.000
20.000
25.000
30.000
35.000
40.000
45.000
50.000
0.0 0.5 1.0 1.5 2.0
CO2 Molarity (mol/L)
Co
nd
uct
ivit
y (m
illiS
iem
ens/
cm)
20 oC30 oC
40 oC
Effect of Solvent on pH
• pH measures the activity of the hydrogen ion, which is the ion concentration multiplied by an activity coefficient. An increase in solvent concentration increases the pH by a decrease in the activity coefficient and a decrease in the ion concentration from a decrease per the water dissociation constant.
• pH is also affected by CO2 weight percent since pH changes with the concentration of carbonic acid.
• Density measurements by Micromotion meters provide an accurate inference of CO2 weight percent.
Effect of MEA Solvent on pH
Correlation of pH to CO2 Weight Percent in Methyl Ethyl Amine (MEA)
MEA2% =( 0.2573)(pH) - 2.4727R² = 0.9641
MEA6.5% = (0.2047)(pH) - 1.75R² = 0.9445
MEA11% = (0.0598)(pH) - 0.1864R² = 0.9785
0.300
0.320
0.340
0.360
0.380
0.400
0.420
8.00 8.50 9.00 9.50 10.00 10.50 11.00 11.50
pH
MEA
(CO
2 fre
e w
iegh
t %)
2%
6.50%
11%
Correlation of pH to CO2 Weight % in Piperazine (PZ)
PZ10%= (0.1573)(pH) - 1.1783R² = 0.9407
PZ12.5% = (0.118)(pH) - 0.7192R² = 0.9969
PZ15% = (0.0776)(pH) - 0.2664R² = 0.9897
0.35
0.37
0.39
0.41
0.43
0.45
0.47
8 8.5 9 9.5 10 10.5
pH
PZ w
iegh
t % (C
O2 f
ree)
10% CO2
12.5% CO2
15% CO2
Effect of PZ Solvent on pH
Enhanced PID Algorithm for Wireless (PIDPlus) PID integral mode is
restructured to provide integral action to match the process response in the elapsed time (reset time 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
If transmitter damping is set to make noise amplitude less than sensitivity limit, valve packing and battery life is dramatically improved
Enhancement compensates for measurement sample time suppressing oscillations and enabling a smooth recovery from a loss in communications further extending packing -battery life
+
+
+
+
Elapsed Time
Elapsed Time
TD
Kc
Kc
TD
http://www2.emersonprocess.com/siteadmincenter/PM%20DeltaV%20Documents/
Whitepapers/WP_DeltaV%20PID%20Enhancements%20for%20Wireless.pdf
Link to PIDPlus White Paper
Flow Setpoint Response - PIDPlus vs. Traditional PID
Traditional PID Sensor PV
Enhanced PID Sensor PV
Flow Load Response - PIDPlus vs. Traditional PID
Traditional PID Sensor PV
Enhanced PID Sensor PV
Flow Failure Response - PIDPlus vs. Traditional PID
Enhanced PID Sensor PV
Traditional PID Sensor PV
pH Setpoint Response - PIDPlus vs. Traditional PID
Enhanced PID Sensor PV
Traditional PID Sensor PV
pH Load Response - PIDPlus vs. Traditional PID
Traditional PID Sensor PV
Enhanced PID Sensor PV
pH Failure Response - PIDPlus vs. Traditional PID
Traditional PID Sensor PV
Enhanced PID Sensor PV
• The PID enhancement for wireless (PIDPlus) offers an improvement wherever there is an update time in the loop. In the broadest sense, an update time can range from seconds (wireless updates and valve or measurement sensitivity limits) to hours (failures in communication, valve, or measurement). Some of the sources of update time are:– Wireless measurement default update rate for periodic reporting (default update rate)– Wireless measurement trigger level for exception reporting (trigger level)– Wireless communication failure – Broken pH electrode glass or lead wires (failure point is about 7 pH)– Large valve operating on upper part of installed characteristic (low sensitivity)– Valve with backlash (deadband) and stick-slip (resolution and sensitivity limit)– Operating at split range point (discontinuity of no response to abrupt response)– Valve with solids, high temperature, or sticky fluid that causes plugging or seizing – Plugged impulse lines– Analyzer sample processing delay and analysis or multiplex cycle time– Analyzer resolution and sensitivity limit
PIDPlus Benefits Extend Far Beyond Wireless - 1
• The PIDPlus executes when there a change in setpoint, feedforward, or remote output to provide an immediate reaction based on PID structure
• The improvement in control by the PIDPlus is most noticeable as the update time becomes much larger than the 63% process response time (defined in the white paper as the sum of the process deadtime and time constant). When the update time becomes 4 times larger than this 63% process response time that roughly corresponds to the 98% response time frequently cited in the literature, the feedforward and controller gains can be set to provide a complete correction for changes in the measurement and setpoint. – Helps ignore inverse response and errors in feedforward timing– Helps ignore discontinuity (e.g. steam shock) at split range point– Helps extend packing life by reducing oscillations and hence valve travel
• Since the PIDPlus can be set to execute only upon a significant change in user valve position, the PIDPlus as a valve position controller offers less interaction and cycling for optimization of unit operations by increasing reactor feed, column feed or increasing refrigeration unit temperature, or decreasing compressor pressure till feed, vent, coolant, and/or steam, valves are at maximum good throttle position.
PIDPlus Benefits Extend Far Beyond Wireless - 2
http://www.modelingandcontrol.com/2010/08/wireless_pid_benefits_extend_t.html http://www.modelingandcontrol.com/2010/10/enhanced_pid_for_wireless_elim.html
http://www.modelingandcontrol.com/2010/11/a_delay_of_any_sorts.html
Website entries on Enhanced PID Benefits
Enhanced PID Can Eliminate Valve Limit Cycles
PID PV
PID Output
Enhanced PIDTraditional PID
Limit Cycles from Valve Stick-Slip
feed A
feed B
coolantmakeup
CAS
ratio
CAS
reactor
vent
product
maximum productionrate
condenser
CTW
PT
PC-1
TT
TT
TC-2
TC-1
FC-1
FT
FT
FC-2
<
TC-3
RC-1
TT
ZC-1
ZC-2CAS
CAS
CAS
ZC-3 ZC-4<
Valve Position Controllers (VPC)ZC-1,2,3,4 are enhanced PID with
directional output velocity limiting and position noise band set to reduce
interactions and limit cycling
Enhanced PID Can Maximize Production Rate
Time (seconds)
% Controlled Variable (CV) or
% Controller Output (CO)
DCO
DCV
qo tp2
Kp = DCV / DCO
0.63*DCV
CO
CV
Self-regulating processopen loop
negative feedback time constant
Self-regulating process gain (%/%)
Response to change in controller output with controller in manual
observed total loopdeadtime
toor
Maximum speedin 4 deadtimes
is critical speed
Self-Regulating Process Open Loop Response
Time (seconds)qo
Ki = { [ CV2 / Dt2 ] - [ CV1 / Dt1 ] } / DCO
DCO
ramp rate isDCV1 / Dt1
ramp rate isDCV2 / Dt2
CO
CV
Integrating process gain (%/sec/%)
Response to change in controller output with controller in manual% Controlled Variable (CV)
or% Controller Output (CO)
observed total loopdeadtime
Maximum speedin 4 deadtimes
is critical speed
Integrating Process Open Loop Response
Wireless Trigger Level > noise
Wireless DefaultUpdate
Rate
Response to change in controller output with controller in manual
qo t’p2
Noise Band
Acceleration
DCV
DCO
1.72*DCV
Kp = DCV / DCO
Runaway process gain (%/%)
% Controlled Variable (CV) or
% Controller Output (CO)
Time (seconds)observed total loopdeadtime
runaway processopen loop
positive feedback time constant
For safety reasons, tests are terminated after 4 deadtimes
t’oor
Maximum speedin 4 deadtimes
is critical speed
Runaway Process Open Loop Response
tp1 qp2 tp2 Kpvqp1
tc1 tm2 qm2 tm1 qm1Kcvqctc2
Kc Ti Td
Valve Process
Controller Measurement
Kmvtvqv
KLtLqL
Load Upset
CV
CO
MVPV
PID
Delay Lag
Delay Delay Delay
Delay
Delay
Delay
Lag Lag Lag
LagLagLag
Lag
Gain
Gain
Gain
Gain
LocalSet Point
DV
First Order Approximation: qo @ qv + qp1 + qp2 + qm1 + qm2 + qc + tv + tp1 + tm1 + tm2 + tc1 + tc2
(set by automation system design for flow, pressure, level, speed, surge, and static mixer pH control)
%
%
%
Delay <=> Dead TimeLag <=>Time Constant
For integrating processes: Ki = Kmv * (Kpv / tp2 ) * Kcv
100% / span
Loop Block Diagram (First Order Approximation)
Hopefully tp2 is the largest lag in the loop
½ of Wireless Default Update Rate
opo
ox EE
)(
opo
oi EE
)(
2
Peak error is proportional to the ratio of loop deadtime to 63% response time(Important to prevent SIS trips, relief device activation, surge prevention, and RCRA pH violations)
Integrated error is proportional to the ratio of loop deadtime squared to 63% response time(Important to minimize quantity of product off-spec and total energy and raw material use)
Ultimate Limit to Loop Performance
Total loop deadtimethat is often set byautomation design
Largest lag in loopthat is ideally set bylarge process volume
½ of Wireless Default Update Rateis additional deadtime
ocp
x EKK
E
)1(
1
ocp
fxii E
KK
tTE
Peak error decreases as the controller gain increases but is essentially the open loop error for systems when total deadtime >> process time constant
Integrated error decreases as the controller gain increases and reset time decreases but is essentially the open loop error multiplied by the reset time plus signal delays and lags for systems when total deadtime >> process time constant
Practical Limit to Loop Performance
Open loop error forfastest and largestload disturbance
ocffi
r SPKSPCOK
SPT
)|,min(|( max
Rise time (time to reach a new setpoint) is inversely proportional to controller gain
op
pc KK
24.0oiT 4 1d pT
For runaway processes:
For self-regulating processes:
oic KK
15.0
oiT 4 1d pT
oic KK
16.0
oiT 40 1d 2 pT
For integrating processes:
op
pc KK
2'6.0
oic KK
14.0
Near integrator (tp2 >> qo):
oiT 5.0
Near integrator (t’p2 >> qo):
Deadtime dominant (tp2 << qo):
0d Tp
c KK
14.0
Fastest Controller Tuning (reaction curve method*)
These tuning equations provide maximumdisturbance rejection but will cause
some overshoot of setpoint response
* - Ziegler Nichols method closed loop modifiedto be more robust and less oscillatory
1.0 for Enhanced PID if Wireless Default Update Rate > Process Response Time !
DCV = change in controlled variable (%) DCO = change in controller output (%) Kc = controller gain (dimensionless) Ki = integrating process gain (%/sec/% or 1/sec) Kp = process gain (dimensionless) also known as open loop gain DV = disturbance variable (engineering units) MV = manipulated variable (engineering units) PV = process variable (engineering units) DSP = change in setpoint (engineering units) SPff = setpoint feedforward (engineering units) Dt = change in time (sec) Dtx = execution or update time (sec) qo = total loop dead time (sec) tf = filter time constant or well mixed volume residence time (sec) tm = measurement time constant (sec) tp2 = primary (large) self-regulating process time constant (sec) t’p2 = primary (large) runaway process time constant (sec) tp1 = secondary (small) process time constant (sec) Ti = integral (reset) time setting (sec/repeat) Td = derivative (rate) time setting (sec) Tr = rise time for setpoint change (sec) to = oscillation period (sec) l = Lambda (closed loop time constant or arrest time) (sec) lf = Lambda factor (ratio of closed to open loop time constant or arrest time)
Nomenclature