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ISA Saint Louis Short Course Dec 6-8, 2010

Exceptional Process Control Opportunities - An Interactive Exploration of Process Control Improvements - Day 2

Welcome

• Gregory K. McMillan – Greg is a retired Senior Fellow from Solutia/Monsanto and an ISA Fellow.

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 Essentials of Modern Measurements and Final Elements for the Process Industry. 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 2010

Block Diagram of “Series”, “Real”, or “Interacting” PID Form

Nearly all analog controllers used the “Series” or “Real” Form

SP

proportional

integral

derivative

Gain

Reset (1 Ti)

Rate

CO

filter

filter

CV filter

Filter Time Rate Time

Improving Controllers

Block Diagram of “Standard”, “Ideal”, or “Non-interacting” PID Form

Nearly all digital controllers have the “standard” or “Ideal” form as the default

SP

proportional

integral

derivative

Gain

Reset (1 Ti)

Rate

CO

filter

filter

CV filter

Filter Time Rate Time


Positive Feedback Implementation of Integral Mode

SP

proportional

derivative

Gain

Rate

CO

filter

filter

CV filterFilter Time Rate Time

filter

Filter Time = Reset Time

ER is external reset(e.g. secondary PV)Dynamic Reset Limit

ER

PositiveFeedback


PID Structure Choices

1. PID action on error (= 1 and = 1)

2. PI action on error, D action on PV (= 1 and = 0)

3. I action on error, PD action on PV (= 0 and = 0)

4. PD action on error (= 1 and = 1) (no I action)

5. P action on error, D action on PV (= 1 and = 0) (no I action)

6. ID action on error ( = 1) (no P action)

7. I action on error, D action on PV ( = 0) (no P action)

8. Two degrees of freedom controller (and adjustable 0 to 1)

The and factors do not affect the load response of a control loop !


PID Controller Forms

PB = 100% Kc

COn = Pn In + Dn + COi

COi = controller output at transition to AUTO, CAS, or RCAS modes (%)COn = controller output at execution n (%)CVn = controlled variable at execution n (%)Dn = contribution from derivative mode for execution n (%)In = contribution from integral mode for execution n (%)Kc = controller gain (dimensionless)Pn = contribution from proportional mode for execution n (%)Ri = reset setting (repeats/minute)PB = controller proportional band (%)SPn = set point at execution n (%)Td = derivative (rate) time setting (seconds)Ti = integral (reset) time setting (seconds/repeat) = rate time factor to set derivative filter time constant (1/8 to 1/10) = set point weight for proportional mode (0 to 1) = set point weight for derivative mode (0 to 1)

Ri = (60 Ti)Conversion of settings:

(Kc Td) SPn – SPn-1) – (CVn CVn-1) ] TdDn-1

Dn = -------------------------------------------------------------------------------

Td t

Pn = Kc SPn – CVn)

In = (Kc Ti) SPn – CVn) t In-1

Standard

Pn = Kc SPn – Dn)

In = (Kc Ti) SPn – Dn) t In-1

Series


PIDPlus Solution - Algorithm 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


Flow Load Response - PIDPlus vs. Traditional PID


Flow Failure Response - PIDPlus vs. Traditional PID


pH Setpoint Response - PIDPlus vs. Traditional PID


pH Load Response - PIDPlus vs. Traditional PID


pH Failure Response - PIDPlus vs. Traditional PID


• 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

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 Wireless PID Benefits

PIDPlus Fast Wireless Loop LabPIDPlus Fast Wireless Loop Lab

• Objective – See how PIDPlus can achieve the ultimate performance limit for a wireless refresh time of 16 sec in a fast secondary loop

• Activities:1. On Main Display, select Restore Labs to Initial State

2. On Main Display, select Cascade Loop Lab02

3. Click on secondary loop AC1-2 PID Faceplate and put PID in Auto

4. Click on magnifying glass icon to get Detail display

5. Click on any block in block diagram

6. In Measurement tab Detail set Refresh = 16 sec (set periodic reporting) and set Sensitivity = 100% (eliminate exception reporting) for secondary measurement

7. Change secondary PID setpoint from 50% to 60%

8. Wait for oscillations to develop

9. In PID tab detail, Enable PIDPlus for secondary loop

10. Wait for oscillations to decay


12. In AC1-2 PID Detail display, change PID gain to 1.0


14. Return Refresh to 0 sec, Sensitivity to 0%, and PID Gain = 0.5 and Disable PIDPlus


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

Improving Valves

Direct Connection Piston ActuatorDirect Connection Piston Actuator

Less backlash but wear of piston O-ring seal from piston pitch is concern

Improving Valves

Significant backlash from link pin points 1 and 2

Link-Arm Connection Piston ActuatorLink-Arm Connection Piston Actuator

Improving Valves

Stick-slip from rack and gear teeth - particularly bad for worn teeth

Rack & Pinion Connection Piston ActuatorRack & Pinion Connection Piston Actuator

Improving Valves

Lots of backlash from slot

Scotch Yoke Connection Piston ActuatorScotch Yoke Connection Piston Actuator

Improving Valves

Port A

Port B

Supply

ZZ

ZZ

ZZ

Z

Control Signal

Digital Valve Controller

Must be functionally testedbefore commissioning!

SV

Terminal Box

Diaphragm Actuator with Solenoid Valves Diaphragm Actuator with Solenoid Valves

Improving Valves

Port A

Port B

Supply


SV

SV

VolumeTank

Must be functionally testedbefore commissioning!

Piston

W

CheckValve

AirSupply

Terminal Box

Piston Actuator with Solenoid Valves Piston Actuator with Solenoid Valves

Improving Valves

Size of Step Determines What you See

Improving Valves

Time (seconds)

0 50 100 150 200 250 300 350 400 450

(%)

35

40

45

50

55

60

65

0.5% Steps 1% Steps 2% Steps 5% Steps 10% Steps

(%)

40

45

50

55

60

65

70

1% Steps 2% Steps0.5% Steps 5% Steps 10% Steps

4" Segmented Ball Valves with Metal Seals,Diaphragm Actuators and Standard Positioners

Fisher V150HD/1052(33)/3610J

Neles R21/QP3C/NP723

Input Signal

Actuator PositionFlow Rate (Filtered)

Maintenance test of 25% or 50% steps will not detect dead band - all valves look good for 10% or larger steps

Effect of Step Size Due to Sensitivity Limit

Improving Valves

Response to Small Steps (No Sensitivity Limit) Response to Small Steps (No Sensitivity Limit)

Improving Valves

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 1 2 3 4 5 6 7 8 9 10

Str

oke

(%)

Time (sec)

0

5

10

15

20

25

30

35

40

45

50

0 1 2 3 4 5 6 7 8 9 10

Time (sec)

Str

oke

(%)

Response to Large Steps (Small Actuator Volume) Response to Large Steps (Small Actuator Volume)

Improving Valves

Installed Characteristic (Linear Trim) Installed Characteristic (Linear Trim)

Improving Valves

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

Inherent Characteristic

Installed Characteristic 1




Valve pressure drop ratio (PR)for installed characteristic:

Characteristic 1: PR 0.5 Characteristic 2: PR 0.25Characteristic 3: PR 0.125Characteristic 4: PR 0.0625

Installed Characteristic (Equal Percentage Trim) Installed Characteristic (Equal Percentage Trim)

Improving Valves

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100








Improving Valves

Installed Characteristic (Modified Parabolic Trim) Installed Characteristic (Modified Parabolic Trim)

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100








Limit Cycle in Flow Loop from Valve Stick-Slip

Controller Output (%)Saw Tooth Oscillation

Process Variable (kpph)Square Wave Oscillation

Improving Valves

Limit Cycle in Level Loop from Valve Deadband

Manipulated Flow (kpph)Clipped Oscillation

Controller Output (%)Rounded Oscillation

Level (%)

Improving Valves

Real Rangeability Real Rangeability

Improving Valves

Minimum fractional flow coefficient for a linear trim and stick-slip:

Minimum fractional flow coefficient for an equal percentage trim and stick-slip:

Minimum controllable fractional flow for installed characteristic and stick-slip:

Cxmin minimum flow coefficient expressed as a fraction of maximum (dimensionless)Pr valve pressure drop ratio (dimensionless) Qxmin minimum flow expressed as a fraction of the maximum (dimensionless)Rv rangeability of control valve (dimensionless) R range of the equal percentage characteristic (e.g. 50)Xvmin maximum valve stroke (%)Sv stick-slip near closed position (%)

maxmin

v

vx X

SC

]1[

minmax

v

vv

X

S

x RC

2min

minmin

)1( xRR

xx

CPP

CQ

min

1

xv QR

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) Next best is Vee-ball or contoured butterfly with rotary digital positioner

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 (Vee-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]

Improving Valves

Volume Booster with Integral Bypass (Furnace Pressure and Surge Control)

Improving Valves

Signal from Positioner

Air Supply fromFilter-Regulator

Air Loadingto Actuator

Adjustable BypassNeedle Valve

Port A

Port B

Supply

ZZ

ZZ

ZZ

Z

Control Signal


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)

Improving Valves

PIDPlus Valve Stick-Slip LabPIDPlus Valve Stick-Slip Lab

• Objective – See how PIDPlus can eliminate limit cycles from stick-slip

• Activities:1. On Main Display, select Cascade Loop Lab02

2. Click on secondary loop AC1-2 PID Faceplate and put PID in Auto


4. Click on magnifying glass icon to get Detail display


6. In Control Valve tab, set stick-slip = 4%


8. Wait for oscillations to develop

9. In PID tab detail, Enable PIDPlus for secondary loop

10. Wait for oscillations to decay

Improving Valves

Top Ten Reasons Why an Automation Engineer Makes a Great Spouse or at Least a Wedding Gift

• (10) Reliable from day one• (9) Always on the job• (8) Low maintenance - minimal grooming, clothing, and entertainment costs• (7) Many programmable features• (6) Stable• (5) Short settling time• (4) No frills or extraneous features• (3) Relies on feedback• (2) Good response to commands and amenable to real time optimization• (1) Readily tuned

Advances in Smart Measurements Advances in Smart Measurements

Improving 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 d/p has improved to 0.025% accuracy for a smart microprocessor based DP. Furthermore, the analog d/p 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 d/p 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


Time (seconds)

TheoreticalTransmitter Response

ActualTransmitter Response

TrueProcess Variable

m

m

deadtime

measurementtime constant

Pro

cess

Var

iab

le

and

Mea

sure

men

t

Dynamic Response to Step Dynamic Response to Step


Dynamic Response to Ramp Dynamic Response to Ramp

Time (seconds)

ActualTransmitter Response

TrueProcess Variable

m m

Pro

cess

Var

iab

le

and

Mea

sure

men

t


f

oof

TAA

2*

Attenuation of Oscillation Amplitude by Transmitter Damping or Signal Filters:

When a measurement or signal filter time (f) becomes the largest timeconstant in the loop, the above equation can be solved for (Ao) to get the Amplitude of the original process variability from the filtered amplitude (Af)


Effect of Transmitter Damping and Signal Filters Effect of Transmitter Damping and Signal Filters

m m

m

m

Effect of Transmitter Damping or Filter for Surge Effect of Transmitter Damping or Filter for Surge


• What you really want most often is a mass flow measurement. However this depends upon the density of the mixture. The fluid density variation not only depends upon temperature and pressure but also composition. The effect of composition can be estimated based on the pure component densities and concentrations via Amagat's law, which works well for liquid mixtures despite being technically based on ideal gas partial volumes. The Coriolis meter uses Amagat's law for two components to provide a relatively accurate inferential measurement of fluid composition. Thus, the mass flow measurement provided by pressure and temperature compensation of a differential head, magmeter, or vortex meter can have an unknown error due to variations in process composition. Many users probably don't realize that even the volumetric flow measurement by a differential head meter is affected by fluid density, and thus composition.

• Everyone is probably cognizant of the effect of velocity profile and hence the upstream piping system and know not to put a control valve upstream of a flowmeter. Swirl is particularly detrimental. Less known is that variations of a percent or more in the discharge or meter coefficient can occur from changes in Reynold's number and orifice edge wear. A transition to laminar flow is disastrous. The tolerance of inside pipe diameter and surface roughness can introduce several percent uncertainty. Flow conditioners, honed meter runs, flow nozzles, and venturi tubes and smart transmitters help considerably.

• Upstream piping and changes in kinematic viscosity affect the vortex meter coefficient. The effects of installation on Coriolis meters are typically negligible. The noise from vibration and dissolved gas has been essentially eliminated by new Coriolis designs.

Flow Measurement


Amagat’s Law (4 components)XXXX]

• Changes in process pressure and temperature can introduce an error of several percent in 1980s and earlier vintage instrumentation DP transmitters used for level measurement.

• Changes in ambient temperature can affect capillary and diaphragm seals. Solutions are equal length capillary with the same sun exposure on the high and low side or separate smart transmitters mounted on the equipment or piping with digital computation of the differential pressure. Reducing diaphragm seal and capillary diameter reduces this error but reduces measurement sensitivity and increases response time.

• Often not recognized are the transient errors in DP measurements that use bubblers and purged lines from the changes in process pressure that cause changes in the purge gas compression. The bubbler tip can get coated from the drying action of the purge gas.

• For DP level measurements, fluid density and bubbles and hence the composition besides the temperature and pressure of the process affect the measurement. For ultrasonic level measurements, changes in the velocity of sound and scattering cause errors. Thus changes in vapor composition and temperature, entrainment of liquid droplets, and foam can be a problem. For radar, if the dielectric constant is large enough and geometry for the vessel and source installation is defined properly, the installation and process effects are typically negligible.

Level Measurement


See Nov-Dec 2010 Control Talk for information useful for Instrument Upgrade Projectshttp://www.controlglobal.com/articles/2010/RetrofitProjects1011.html

• New pH electrode designs are much less sensitive to sodium ion error, contamination, plugging and the loss of efficiency and response time from premature aging of the glass from high temperature. New high temperature designs has doubled the life expectancy of the electrode and returned the response time from an hour or more to a matter of seconds. I didn't know the response time could get so bizarrely slow at temperatures above 50 degrees centigrade until new technology solved the problem. Similarly I did not know a drift of several tenths of a pH could occur after sterilization until an electrode design essentially eliminated the drift. Smart transmitters now have process temperature compensation built in to account for the changes in solution pH from changes in the dissociation constants with temperature. Most users only know about the standard electrode temperature compensation for the changes in the millivolt potential developed by the glass electrode per the Nernst equation. Velocity errors are still largely unknown and the error introduced by changes in the activity of the hydrogen ion with ionic strength is largely ignored but quantified in Chapter 2 of Advanced pH Measurement and Control - 3rd Edition.

• For temperature measurements, there are thermal errors from heat conduction from the thermowell tip to the flanged or threaded process connection, dynamic error from thermowell lags, nonlinearity error (solved by sensor matching and smart transmitters), lead wire errors, insulation errors, radiation errors in furnaces, velocity errors in high flow gas streams, and sensor de-calibration errors as detailed in Chapter 2 of Advanced Temperature Measurement and Control - 2nd Edition.

• For pH and temperature, non ideal mixing introduces significant process measurement errors. The concentrations and temperatures in a vessel or over the cross section of a pipe are not uniform. Very little attention is paid to this. The effect is thought to be more significant for highly viscous flows. The significant effect of composition and viscosity on temperature profile has been studied for extruders.

• The effect of coatings is sketchy. We know it can be profound for pH electrodes where an almost imperceptible coating can increase the response time from 12 to 120 seconds. Similar but not as dramatic effects should occur for coatings on thermowells depending upon the conductivity of the coating. Low velocities increase the response time for both pH and temperature besides increasing the likelihood and rate of coating formation.

pH and Temperature Measurement


Temperature Sensor Performance

0.420.4Minimum Diameter (mm)

8 x 10-14 x 10-21.6 x 10-7Power (watts at 100 ohm)

1 - 31 - 60 - 0.06Signal Output (volts)

100 - 300 200 - 850 200 - 2000Temperature Range (oC)

0.00010.0010.05Sensitivity (oC)

0.01 - 0.10.01 - 0.11 - 20Drift (oC/year)

0.1 - 10.02 - 0.51 - 8Repeatability (oC)

ThermistorPlatinum RTDThermocoupleCriteria

0.420.4Minimum Diameter (mm)

8 x 10-14 x 10-21.6 x 10-7Power (watts at 100 ohm)

1 - 31 - 60 - 0.06Signal Output (volts)

100 - 300 200 - 850 200 - 2000Temperature Range (oC)

0.00010.0010.05Sensitivity (oC)

0.01 - 0.10.01 - 0.11 - 20Drift (oC/year)

0.1 - 10.02 - 0.51 - 8Repeatability (oC)

ThermistorPlatinum RTDThermocoupleCriteria


Temperature Sensor Lag

Time Constant

(seconds)

Bare Sensing Element Type

8.0Dual Element RTD 1/4 inch

5.5Single Element RTD 1/4 inch


4.5Thermocouple 1/4 inch sheathed and insulated

1.7Thermocouple 1/4 inch sheathed and grounded


Time Constant

(seconds)

Bare Sensing Element Type

8.0Dual Element RTD 1/4 inch



4.5Thermocouple 1/4 inch sheathed and insulated




Thermowell Lags

17 and 8Air0.005150Gas


22 and 7Oil0.04150Gas

4 and 1Air0.00510Liquid


7 and 2Oil0.0110Liquid



32 and 10Air0.010.1Liquid





Time Constants

(seconds)

Annular Fill

Type

Annular Clearance

(inches)

Fluid Velocity

(feet per second)

Process Fluid Type



22 and 7Oil0.04150Gas



7 and 2Oil0.0110Liquid








Time Constants

(seconds)

Annular Fill

Type

Annular Clearance

(inches)

Fluid Velocity

(feet per second)

Process Fluid Type


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%


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 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 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


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


Measurement Lag LabMeasurement Lag Lab

• Objective – Understand relative effects of large measurement lag

• Activities:1. Go to Main Display, select Single Loop Lab01,

2. Click on AC1-1 PID Faceplate and Click on magnifying glass icon to get Detail display

3. Click on Duncan icon for “Tune with Insight” and click on top tab “On Demand Tuning”

4. Set Step Size = 10% and click on “Test” for “On Demand Tuning”

5. Note ultimate period and “Ziegler-Nichols - PI” tuning settings

6. Update PID tuning settings

7. Set Desired Run Time to 300 sec and change mode from Explore to Run


9. In Measurement detail, set Primary Measurement Lag = 100 sec

10. Set Step Size = 10% and click on “Test” for “On Demand Tuning”

11. Note ultimate period and “Ziegler-Nichols - PI” tuning settings

12. Update PID tuning settings and change mode from Explore to Run


Cascade Loop Block Diagram

p1 p2 p2 Kp2p1

m2 m2Km2c2 f2

Kc2 Ti2 Td2

PrimaryProcess

Kvvv

KL2L2L2

Primary Load Upset

CVp

COp

MVPVp2

Delay Lag

Delay Delay Delay

Delay

Delay

Lag Lag Lag

LagLag

Gain

Gain

Gain

Gain

LocalSet Point

DVp2

%

%

%

Delay <=> Dead TimeLag <=>Time ConstantKL1L1L1

Delay Lag Gain

DVp1

Secondary Load Upset

Kc1 Ti1 Td1

COs

SecondaryPID

CascadeSet Point

%

%

Kp1

Gain

CVs

m2 m2Km2

Delay

LagGain

c2 f2

Delay Lag

SecondaryProcess

PrimaryPID

Primary: o2v p1 p2 m2 c2

f2vp1Secondary: o1v p1 m1 c1 f1v

Improving Loops - Part 1

io

io

io

iinner loop process time constant

oouter loop process time constant

iinner loop process deadtime

oouter loop process deadtime

Cascade Control Benefit (self-regulating process)






io

io

io

Cascade Control Benefit (integrating process)


io

io

io





Cascade Control Benefit (runaway process)


Secondary loop slowed down by a factor of 5

Secondary SP

Secondary CO

Primary PV

Secondary SP

Primary PV

Secondary CO

Effect of Slow Secondary Tuning (cascade control)


ControlValve

AOPIDPID

AI AI

FlowMeter

Process

ProcessSensor

Secondary (Inner) Loop Feedback

Primary (Outer) Loop Feedback

ProcessSP

FlowSP Out

PV PV

RelayPID*

Position Loop Feedback

DCS Valve Positioner

Position (Valve Travel)

I/P

Drive Signal

* most positioners use proportional only

Triple Cascade Loop Block Diagram


Feedforward Applications• Feedforward is the most common advanced control technique used - often the

feedforward signal is a flow or speed for ratio control that is corrected by a feedback process controller (Flow is the predominant process input that is manipulated to set production rate and to control process outputs (e.g. temperature and composition))

– Blend composition control - additive/feed (flow/flow) ratio– Column temperature control - distillate/feed, reflux/feed, stm/feed, and bttms/feed (flow/flow) ratio– Combustion temperature control - air/fuel (flow/flow) ratio – Drum level control - feedwater/steam (flow/flow) ratio– Extruder quality control - extruder/mixer (power/power) ratio – Heat exchanger temperature control - coolant/feed (flow/flow) ratio– Neutralizer pH control - reagent/feed (flow/flow) ratio– Reactor reaction rate control - catalyst/reactant (speed/flow) ratio– Reactor composition control - reactant/reactant (flow/flow) ratio– Sheet, web, and film line machine direction (MD) gage control - roller/pump (speed/speed) ratio– Slaker conductivity control - lime/liquor (speed/flow) ratio – Spin line fiber diameter gage control - winder/pump (speed/speed) ratio

• Feedforward is most effective if the loop deadtime is large, disturbance speed is fast and size is large, feedforward gain is well known, feedforward measurement and dynamic compensation are accurate

• Setpoint feedforward is most effective if the loop deadtime exceeds the process time constant and the process gain is well known

For more discussion of Feedforward see May 2008 Control Talkhttp://www.controlglobal.com/articles/2008/171.html


Feedforward Implementation - 1• Feedforward gain can be computed from a material or energy balance ODE * &

explored for different setpoints and conditions from a plot of the controlled variable (e.g. composition, conductivity, pH, temperature, or gage) vs. ratio of manipulated variable to independent variable (e.g. feed) but is most often simply based on operating experience

– * http://www.modelingandcontrol.com/repository/AdvancedApplicationNote004.pdf

– Plots are based on an assumed composition, pressure, temperature, and/or quality

– For concentration and pH control, the flow/flow ratio is valid if the changes in the composition of both the manipulated and feed flow are negligible.

– For column and reactor temperature control, the flow/flow ratio is valid if the changes in the composition and temperature of both the manipulated and feed flow are negligible.

– For reactor reaction rate control, the speed/flow is valid if changes in catalyst quality and void fraction and reactant composition are negligible.

– For heat exchanger control, the flow/flow ratio is valid if changes in temperatures of coolant and feed flow are negligible.

– For reactor temperature control, the flow/flow ratio is valid if changes in temperatures of coolant and feed flow are negligible.

– For slaker conductivity (effective alkali) control, the speed/flow ratio is valid if changes in lime quality and void fraction and liquor composition are negligible.

– For spin or sheet line gage control, the speed/speed ratio is valid only if changes in the pump pressure and the polymer melt quality are negligible.

• Dynamic compensation is used to insure the feedforward signal arrives at same point at same time in process as upset

– Compensation of a delay in the feedforward path > delay in upset path is not possible


• Feedback correction is essential in industrial processes– While technically, the correction should be a multiplier for a change in slope and a bias for a change

in the intercept in a plot of the manipulated variable versus independent variable (independent from this loop but possibly set by another PID or MPC), a multiplier creates scaling problems for the user, consequently the correction of most feedforward signal is done via a bias.

– The bias correction must have sufficient positive and negative range for worst case.– Model predictive control (MPC) and PID loops get into a severe nonlinearity by creating a controlled

variable that is the ratio. It is important that the independent variable be multiplied by the ratio and the result be corrected by a feedback loop with the process variable (composition, conductivity, gage, temperature, or pH) as the controlled variable.

• Feedforward gain is a ratio for most load upsets.• Feedforward gain is the inverse of the process gain for setpoint feedforward.

– Process gain is the open loop gain seen by the PID (product of manipulated variable, process variable, and measurement variable gain) that is dimensionless.

• Feedforward action must be in the same direction as feedback action for upset. • Feedforward action is the opposite of the control action for setpoint feedforward.• Feedforward delay and lag adjusted to match any additional delay and lag,

respectively in path of upset so feedforward correction does not arrive too soon. • Feedforward lead is adjusted to compensate for any additional lag in the path of

the manipulated variable so the feedforward correction does not arrive too late.• The actual and desired feedforward ratio should be displayed along with the bias

correction by the process controller. This is often best done by the use of a ratio block and a bias/gain block instead of the internal PID feedforward calculation.

Feedforward Implementation - 2


Bias Correction of Ratio ControlFor information on Ratio Control, see April 7, 2009 Post on website

http://www.modelingandcontrol.com/2009/04/what_have_i_learned_-_ratio_co_1.html


Feedforward Lab 1Feedforward Lab 1

• Objective – Show the effect of a feedforward correction arriving too early

• Activities:1. Go to Main Display, select Feedforward Loop Lab03, and click on any block

2. In Measurements detail set primary feedforward gain = 1.0 and delay = 0 sec

3. Change Lab03 Run time to 300 sec and change mode from Explore to Run

4. Go to Main Display, select Cascade Loop Lab02, and click on any block

5. Click on Trend icon next to faceplate icon and open Lab02 & Lab03 charts


7. Compare the results of Lab02 & Lab03 trend charts

8. In Lab02 note peak error & IAE



• Objective – Show the effect of a feedforward correction arriving too late

• Activities:1. In Lab03 Measurements detail set primary feedforward delay = 40 sec



4. Compare the results of Lab02 & Lab03 charts



Feedforward Lab 2Feedforward Lab 2
