The self-organizing network and automatic reporting of alerts makes it easy to maintain and revise a control system for flexibility and adaptability to changing experimental conditions and requirements in the dynamic environment of a process development lab.
Battery Life is extended by using exception reporting (signal is transmitted only when it exceeds the resolution setting) unless the elapsed time since the last transmission exceeds the refresh time, which can be set to large value.
ISA Saint Louis Short Course Dec 6-8, 2010 Exceptional Process Control Opportunities - An Interactive Exploration of Process Control Improvements - Day 2
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 T i ) 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 Improving Controllers SP proportional integral derivative Gain Reset (1 T i ) Rate CO filter filter CV filter Filter Time Rate Time
Positive Feedback Implementation of Integral Mode Improving Controllers SP proportional derivative Gain Rate CO filter filter CV filter Filter Time Rate Time filter Filter Time = Reset Time ER is external reset (e.g. secondary PV) Dynamic Reset Limit ER Positive Feedback
PI action on error, D action on PV ( = 1 and = 0)
I action on error, PD action on PV ( = 0 and = 0)
PD action on error ( = 1 and = 1) (no I action)
P action on error, D action on PV ( = 1 and = 0) (no I action)
ID action on error ( = 1) (no P action)
I action on error, D action on PV ( = 0) (no P action)
Two degrees of freedom controller ( and adjustable 0 to 1)
The and factors do not affect the load response of a control loop ! Improving Controllers
PID Controller Forms PB = 100% K c CO n = P n I n + D n + CO i CO i = controller output at transition to AUTO, CAS, or RCAS modes (%) CO n = controller output at execution n (%) CV n = controlled variable at execution n (%) D n = contribution from derivative mode for execution n (%) I n = contribution from integral mode for execution n (%) K c = controller gain (dimensionless) P n = contribution from proportional mode for execution n (%) R i = reset setting (repeats/minute) PB = controller proportional band (%) SP n = set point at execution n (%) T d = derivative (rate) time setting (seconds) T i = 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) R i = (60 T i ) Conversion of settings: Improving Controllers (K c T d ) SP n – SP n-1 ) – (CV n CV n-1 ) ] T d D n-1 D n = ------------------------------------------------------------------------------- T d t P n = K c SP n – CV n ) I n = (K c T i ) SP n – CV n ) t I n-1 Standard P n = K c SP n – D n ) I n = (K c T i ) SP n – D n ) t I n-1 Series
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
http://www2.emersonprocess.com/siteadmincenter/PM%20DeltaV%20Documents/ Whitepapers/WP_DeltaV%20PID%20Enhancements%20for%20Wireless.pdf Improving Controllers Link to PIDPlus White Paper + + + + Elapsed Time Elapsed Time T D K c K c T D
Flow Setpoint Response - PIDPlus vs. Traditional PID Improving Controllers
Flow Load Response - PIDPlus vs. Traditional PID Improving Controllers
Flow Failure Response - PIDPlus vs. Traditional PID Improving Controllers
pH Setpoint Response - PIDPlus vs. Traditional PID Improving Controllers
pH Load Response - PIDPlus vs. Traditional PID Improving Controllers
pH Failure Response - PIDPlus vs. Traditional PID Improving Controllers
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:
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 Improving Controllers 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
Objective – See how PIDPlus can achieve the ultimate performance limit for a wireless refresh time of 16 sec in a fast secondary loop
On Main Display, select Restore Labs to Initial State
On Main Display, select Cascade Loop Lab02
Click on secondary loop AC1-2 PID Faceplate and put PID in Auto
Click on magnifying glass icon to get Detail display
Click on any block in block diagram
In Measurement tab Detail set Refresh = 16 sec (set periodic reporting) and set Sensitivity = 100% (eliminate exception reporting) for secondary measurement
Change secondary PID setpoint from 50% to 60%
Wait for oscillations to develop
In PID tab detail, Enable PIDPlus for secondary loop
Wait for oscillations to decay
Change secondary PID setpoint from 60% to 50%
In AC1-2 PID Detail display, change PID gain to 1.0
Change secondary PID setpoint from 50% to 60%
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 positioner requires 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 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 Actuator Improving Valves
Stick-slip from rack and gear teeth - particularly bad for worn teeth Rack & Pinion Connection Piston Actuator Improving Valves
Lots of backlash from slot Scotch Yoke Connection Piston Actuator Improving Valves
Diaphragm Actuator with Solenoid Valves Improving Valves Port A Port B Supply ZZZZZZZ Control Signal Digital Valve Controller Must be functionally tested before commissioning! SV Terminal Box
Piston Actuator with Solenoid Valves Improving Valves Port A Port B Supply Digital Valve Controller SV SV Volume Tank Must be functionally tested before commissioning! Piston W Check Valve Air Supply Terminal Box
Size of Step Determines What you See Improving Valves 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) Improving Valves Stroke (%) Time (sec)
Response to Large Steps (Small Actuator Volume) Improving Valves Time (sec) Stroke (%)
Installed Characteristic (Linear Trim) Improving Valves Valve pressure drop ratio ( P R ) for installed characteristic: Characteristic 1: P R 0.5 Characteristic 2: P R 0.25 Characteristic 3: P R 0.125 Characteristic 4: P R 0.0625
Installed Characteristic (Equal Percentage Trim) Improving Valves Valve pressure drop ratio ( P R ) for installed characteristic: Characteristic 1: P R 0.5 Characteristic 2: P R 0.25 Characteristic 3: P R 0.125 Characteristic 4: P R 0.0625
Improving Valves Installed Characteristic (Modified Parabolic Trim) Valve pressure drop ratio ( P R ) for installed characteristic: Characteristic 1: P R 0.5 Characteristic 2: P R 0.25 Characteristic 3: P R 0.125 Characteristic 4: P R 0.0625
Limit Cycle in Flow Loop from Valve Stick-Slip Improving Valves Controller Output (%) Saw Tooth Oscillation Process Variable (kpph) Square Wave Oscillation
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: C xmin minimum flow coefficient expressed as a fraction of maximum (dimensionless) P r valve pressure drop ratio (dimensionless) Q xmin minimum flow expressed as a fraction of the maximum (dimensionless) R v rangeability of control valve (dimensionless) R range of the equal percentage characteristic (e.g. 50) X vmin maximum valve stroke (%) S v stick-slip near closed position (%)
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 :
5% to 75% (sliding stem globe),
10 o to 60 o (Vee-ball)
25 o to 45 o (conventional butterfly)
5 o to 65 o (contoured and toothed butterfly)
Online diagnostics and step response tests for small changes in signal
Dynamic reset limiting using digital positioner feedback 
Volume Booster with Integral Bypass (Furnace Pressure and Surge Control) Improving Valves Signal from Positioner Air Supply from Filter-Regulator Air Loading to Actuator Adjustable Bypass Needle Valve
Booster and Positioner Setup (Furnace Pressure and Surge Control) Improving Valves Port A Port B Supply ZZZZZZZ Control Signal Digital Valve Controller Must be functionally tested before commissioning! 1:1 Bypass Volume Booster Open bypass just enough to ensure a non-oscillatory fast response Air Supply High Capacity Filter Regulator Increase air line size Increase connection size Terminal Box
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
Advances in Smart Measurements Improving Measurements 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 . 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.
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.
“ Fix Now” and “Fix Soon” alerts are provided along with common causes and recommended actions
Dynamic Response to Step Improving Measurements Time (seconds) Theoretical Transmitter Response Actual Transmitter Response True Process Variable m m deadtime measurement time constant Process Variable and Measurement
Dynamic Response to Ramp Improving Measurements Time (seconds) Actual Transmitter Response True Process Variable m m Process Variable and Measurement
Attenuation of Oscillation Amplitude by Transmitter Damping or Signal Filters: When a measurement or signal filter time ( f ) becomes the largest time constant in the loop, the above equation can be solved for (A o ) to get the Amplitude of the original process variability from the filtered amplitude (A f ) Improving Measurements Effect of Transmitter Damping and Signal Filters
Effect of Transmitter Damping or Filter for Surge Improving Measurements m m m m
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 Improving Measurements Amagat’s Law (4 components) X X X X ]
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 Improving Measurements See Nov-Dec 2010 Control Talk for information useful for Instrument Upgrade Projects http://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 Improving Measurements
Temperature Sensor Performance Improving Measurements
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 Improving Measurements 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 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
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.
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 CO 2 weight percent since pH changes with the concentration of carbonic acid.
Density measurements by Micromotion meters provide an accurate inference of CO 2 weight percent.
Effect of MEA Solvent on pH Improving Measurements
Effect of PZ Solvent on pH Improving Measurements
Objective – Understand relative effects of large measurement lag
Go to Main Display, select Single Loop Lab01,
Click on AC1-1 PID Faceplate and Click on magnifying glass icon to get Detail display
Click on Duncan icon for “Tune with Insight” and click on top tab “On Demand Tuning”
Set Step Size = 10% and click on “Test” for “On Demand Tuning”
Note ultimate period and “ Ziegler-Nichols - PI” tuning settings
Update PID tuning settings
Set Desired Run Time to 300 sec and change mode from Explore to Run
Click on any block in block diagram
In Measurement detail, set Primary Measurement Lag = 100 sec
Set Step Size = 10% and click on “Test” for “On Demand Tuning”
Note ultimate period and “ Ziegler-Nichols - PI” tuning settings
Update PID tuning settings and change mode from Explore to Run
Cascade Loop Block Diagram p1 p2 p2 K p2 p1 m2 m2 K m2 c2 f2 Primary Process K v v v K L2 L2 L2 Primary Load Upset CV p CO p MV PV p2 Delay Lag Delay Delay Delay Delay Delay Lag Lag Lag Lag Lag Gain Gain Gain Gain Local Set Point DV p2 % % % Delay <=> Dead Time Lag <=>Time Constant K L1 L1 L1 Delay Lag Gain DV p1 Secondary Load Upset CO s Secondary PID Cascade Set Point % % K p1 Gain CV s m2 m2 K m2 Delay Lag Gain c2 f2 Delay Lag Secondary Process Primary PID Primary: o2 v p1 p2 m2 c2 f2 v p1 Secondary: o1 v p1 m1 c1 f1 v Improving Loops - Part 1 K c2 T i2 T d2 K c1 T i1 T d1
Cascade Control Benefit (self-regulating process) Improving Loops - Part 1 i o i o i o i inner loop process time constant o outer loop process time constant i inner loop process deadtime o outer loop process deadtime
Cascade Control Benefit (integrating process) Improving Loops - Part 1 i inner loop process time constant o outer loop process time constant i inner loop process deadtime o outer loop process deadtime i o i o i o
Cascade Control Benefit (runaway process) Improving Loops - Part 1 i o i o i o i inner loop process time constant o outer loop process time constant i inner loop process deadtime o outer loop process deadtime
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) Improving Loops - Part 1
Triple Cascade Loop Block Diagram Improving Loops - Part 1 Control Valve AO PID PID AI AI Flow Meter Process Process Sensor Secondary (Inner) Loop Feedback Primary (Outer) Loop Feedback Process SP Flow SP Out PV PV Relay PID * Position Loop Feedback DCS Valve Positioner Position (Valve Travel) I/P Drive Signal * most positioners use proportional only
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 Talk http://www.controlglobal.com/articles/2008/171.html Improving Loops - Part 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
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 Improving Loops - Part 1
Bias Correction of Ratio Control For 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 Improving Loops - Part 1