Exceptional Process Control Opportunities

ISA Boston Section Oct 20, 2009 Exceptional Process Control Opportunities

Welcome
Gregory K. McMillan
I worked 33 years for Monsanto and its spin-off Solutia Inc first as an instrument engineer and then as specialist in process modeling and control. I have written humorous and serious technical books for ISA. Good Tuning - a Pocket Guide , Advanced Control Unleashed , and The Funnier Side of Retirement for Engineers and People of the Technical Persuasion received the Raymond D. Malloy award for best selling books. Presently I contract part time as a principal consultant to Emerson Process Management in Austin Texas via CDI Process and Industrial. My latest technical tips are at: http://ModelingandControl.com

Exceptional Opportunities (Covered Tonight)
Wireless Measurement and Control
Sample Time
Integrating Process (e.g. Batch) Controller Tuning
Precision Control Valves for pH Control
Open Loop Backup (e.g. Compressor Surge & RCRA pH)
Expertise Retention and Development
Opportunities from Today’s Interviews

Exceptional Opportunities (Future Entries on http://ModelingandControl.com )
Batch Profile Control
Adaptive Feedback Control and Linearization
Adaptive Feedforward Control and Linearization
Full Throttle Set Point Response for Batch and Startup
Controller Output Overdrive
Dynamic Reset Limit
Fast and Intermittent Disturbances and Discontinuities
Integration of Loop, Process, and Maintenance Data
Root Cause Analysis
Data Visualization
Virtual Tool for Learning and Exploring Opportunities
Peak Control

Wireless Opportunities
Wireless temperatures and differential pressures for packed absorber and distillation column hot spot and flow distribution analysis and control
Wireless temperatures and differential pressures for fluidized bed reactor hot spot and flow distribution analysis and control
Wireless pressures to debottleneck piping systems, monitor process filter operation, and track down the direction and source of pressure disturbances
Wireless temperatures and flows to debottleneck coolant systems
Wireless instrumentation to increase the mobility, flexibility, and maintainability of skids for process equipment service such as cleaning and sterilization
Wireless instrumentation to increase the mobility, flexibility, and maintainability of skids for lab and pilot plant unit operations. (Note: skids are platforms of pre-assembled equipment, piping, and automation to perform unit operations)

Newest Book - The Latest on Smart and Wireless Instrumentation Royalties are donated to the University of Texas Research Campus for Energy and Environmental Resources for Development of Wireless Instrumentation and Control

Traditional and Wireless PID (PIDPLUS)
PID integral mode is restructured to provide integral action to match the process response in the elapsed time (reset time is set equal to process time constant)
PID derivative mode is modified to compute a rate of change over the elapsed time from the last new measurement value
PID reset and rate action are only computed when there is a new value
PID algorithm with enhanced reset and rate action is termed PIDPLUS

Control Studies of Glucose Sample Time, Feedforward, and Wireless PID Control Batch 1: Glucose Probe (Continuous - No Delay) + Feed Forward - No + Standard PID Batch 2: Glucose Probe (Continuous - No Delay) + Feed Forward - Yes + Standard PID Batch 3: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - No + Standard PID Batch 4: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - Yes + Standard PID Batch 5: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - No + Wireless PID Batch 6: Glucose Analyzer (11 Hr Sample Delay) + Feed Forward - Yes + Wireless PID Continuous FF-No Standard PID Continuous FF-Yes Standard PID 11 hr Sample FF-No Standard PID 11 hr Sample FF-Yes Standard PID 11 hr Sample FF-No Wireless PID 11 hr Sample FF-Yes Wireless PID Batch 1 Batch 2 Batch 3 Batch 4 Batch 5 Batch 6 Glucose Concentration

Time (seconds) Process Variable or Controller Output (%)  CO  PV  p  p K p =  PV  CO  PV %CO %PV dead time process time constant Self-regulating process gain (%/%) Self-Regulating Process Response Lambda (closed loop time constant) is defined in terms of a Lambda factor (  f ): Most continuous processes have a self-regulating response (PV lines out in manual) Response to change in controller output with controller in manual

Self-Regulation Process Gain: Controller Gain Controller Integral Time Self-Regulating Process Tuning “ Near Integrating” Gain Approximation

Time (seconds)  p K i = { [  PV 2  t 2 ]  PV 1  t 1 ] }  CO  CO ramp rate is  PV 1  t 1 ramp rate is  PV 2  t 2 %CO %PV dead time Integrating process gain (%/sec/%) Integrating Process Response Process Variable or Controller Output (%) Lambda (closed loop arrest time) is defined in terms of a Lambda factor (  f ): Most batch processes have an integrating response (PV ramps in manual) Response to change in controller output with controller in manual

The above tuning automatically insures the following inequality is satisfied to prevent slow rolling oscillations from too low of a gain or integral time. Integrating Process Gain: Controller Gain Controller Integral Time Integrating Process Tuning

Exothermic reactors, strong acid-base pH systems, and compressor surge can exhibit a runaway response (PV accelerates in manual) Runaway Process Response Response to change in controller output with controller in manual

Studies of Reset Factor & Wireless PID for Self-Regulating Process Wireless PID Wireless PID Wireless PID Standard PID Standard PID Standard PID Reset Factor = 0.5 Reset Factor = 1.0 Reset Factor = 2.0 Reset Factor = 0.5 Reset Factor = 1.0 Reset Factor = 2.0 Improvement in stability and control is dramatic for any self-regulating process with analyzer delay

Studies of Lambda Factor & Wireless PID for Self-Regulating Process Wireless PID Wireless PID Wireless PID Standard PID Standard PID Standard PID Lambda Factor = 1.5 Lambda Factor = 2.0 Lambda Factor = 2.5 Lambda Factor = 1.5 Lambda Factor = 2.0 Lambda Factor = 2.5 Improvement in stability and control is dramatic for any self-regulating process with analyzer delay

Studies of Reset Factor & Wireless PID for Integrating Process Reset Factor = 0.5 Wireless PID Wireless PID Wireless PID Standard PID Standard PID Standard PID Reset Factor = 1.0 Reset Factor = 2.0 Reset Factor = 0.5 Reset Factor = 1.0 Reset Factor = 2.0 Improvement in stability is significant for any integrating process with analyzer delay

Studies of Lambda Factor & Wireless PID for Integrating Process Lambda Factor = 1.5 Wireless PID Wireless PID Wireless PID Standard PID Standard PID Standard PID Lambda Factor = 2.0 Lambda Factor = 2.5 Lambda Factor = 1.5 Lambda Factor = 2.0 Lambda Factor = 2.5 Improvement in stability is significant for any integrating process with analyzer delay

Wireless Portable Bioreactor with a Lab Optimized DCS (Courtesy of Broadley-James)

Wireless pH Performance on Bioreactor Wired pH ground noise spike Temperature compensated wireless pH controlling at 6.9 pH set point Incredibly tight pH control via 0.001 pH wireless resolution setting still reduced the number of communications by 60%

Wireless SUB Temperature Loop Test Results

Wireless SUB pH Loop Test Results

Wireless PID Control Conclusions
Wireless PID and new communication rules can increase battery life
Wireless pH eliminates spikes form ground noise
Wireless PID provides tight control for set point changes
Feedforward of formation rate improves glucose control but does not eliminate instability for large at-line analyzer sample time
Wireless PIDPLUS dramatically improves the control and stability of any self-regulating process with large measurement delay (sample delay). The wireless PID is a technological breakthrough for the use at-line analyzers for control
The Wireless PIDPLUS set point overshoot is negligible for self-regulating processes with large sample delays if controller gain is less than the inverse of process gain
Wireless PIDPLUS is stable for self-regulating process with large sample delay if controller gain is less than twice the inverse of the process gain
As the analyzer sample time decreases and approaches the module execution time, it is expected that the wireless PID behaves more like a standard PID
Wireless PIDPLUS significantly reduces the oscillations of integrating processes but the improvement is not as dramatic as for self-regulating processes
Integrating processes are much more sensitive than self-regulating processes to increases in sample time, decreases in reset time, and increases in gain
Detuned controllers (large Lambda Factors), makes loops less sensitive to sample time (see Advanced Application Note 005 “Effect of Sample Time ….”)
If the controller gain is increased or the wireless resolution setting is made finer, the PIDPLUS can provide tighter control. For a loss of communication, the PIDPLUS offers significantly better performance than a wired traditional PID particularly when rate action and actuator feedback (readback) is used

Sample Time Guidelines Table Practical and Ultimate sample times are for conservative and aggressive tuning, respectively Type of Process Loop Process Deadtime Process Time Constant Practical Sample Time Ultimate Sample Time Liquid Flow 0.05 - 0.5 sec 0.5 - 5 sec 2 sec 0.1 sec Gas Flow 0.1 - 0.5 sec 1 - 10 sec 1 sec 0.1 sec Liquid Pressure* 0.05 - 0.5 sec 0.2 - 1 sec 0.1 sec 0.02 sec Column Pressure! 1 - 10 sec 10 - 100 sec 10 sec 2 sec Furnace Pressure* 0.1 - 0.5 sec 0.2 - 20 sec 0.1 sec 0.02 sec Vessel Pressure! 0.2 - 1 sec 10 - 100 sec 10 sec 1 sec Surge Control 0.05 - 0.5 sec 0.2 - 10 sec 0.1 sec 0.02 sec Liquid Level! 0.05 - 0.5 sec 10 - 100000 min 300 sec 60 sec Exchanger Temperature 0.2 - 2 min 0.5 - 5 min 10 sec 2 sec Batch Temperature! 1 - 10 min 5 - 100000 min 150 sec 30 sec Runaway Temperature!! 0.5 - 5 min 1 - 100 min 10 sec 5 sec Column Temperature 2 - 100 min 10 - 1000 min 300 sec 60 sec Furnace Temperature 0.2 - 2 min 0.5 - 5 min 10 sec 2 sec Vessel Temperature 1 - 10 min 5 - 50 min 150 sec 30 sec Column Composition 1 - 50 min 10 - 1000 min 300 sec 60 sec Furnace Oxygen 0.2 - 1 min 0.2 - 1 min 10 sec 2 sec Vessel Composition 0.5 - 5 min 5 - 50 min 150 sec 30 sec Inline (Static Mixer) pH 2 - 10 sec 2 - 10 sec 2 sec 0.5 sec Vessel pH 0.5 - 5 min 1 - 50 min 30 sec 5 sec

Sample Time Guideline Notes
The term “sample time” is used in the broadest sense as the time between updates in sampled data from digital measurements and controllers and from analyzers The table should be useful for determining whether DCS scan or module execution times, wireless communication time intervals, model predictive control execution time, and at-line analyzer cycle time will affect control system performance.
* - denotes loop uses a variable speed drive with a negligible dead time, deadband, and resolution limit as the final element. If a control valve or damper is used for these loops, you can multiply the sample times for asterisked items by a factor of 5.
! - denotes an integrating response whose integrating process gain is the inverse of the process time constant shown
!! - denotes a runaway response that can accelerate and reach a point of no return
For surge control, it assumed that a volume booster has been added to the each of the positioner outputs to reduce the pre-stroke dead time to less than 0.2 seconds. A valve with excessive sticktion and backlash will add significant deadtime to the response to unmeasured disturbances that deteriorates the ultimate limit to possible performance.
For inline (static mixer) pH control, the largest time constant comes from the sensor lag or the process variable filter time with a nominal value of 5 seconds.
For the vessel pH control it is assumed the mixing time is less than 30 sec and the reagent delivery time delay is negligible by injection of the reagent into a recirculation line just before it enters the vessel. The lower value for the time constant is for a set point on a steep titration curve that cause the pH to move much faster than for a linear response. The response can look like a runaway as the pH accelerates through the neutral region.
For level control set point changes, the deadtime observed is usually about 10 times larger than the actual process deadtime due to level measurement sensitivity limits and noise. For unmeasured disturbances the deadtime observed is often about 20 times larger than the actual process deadtime because of the amount of time it takes the controller output to work through the resolution limit and deadband of the control valve.

Adaptive Controller Tuning of Integrating Process (Batch Temperature)

Adaptive Controller Models of Integrating Process (Batch Temperature)

Adaptive Controller Learning Setup of Integrating Process (Batch Temperature)

Adaptive Controller Gain 40 Reset 500 Output comes off high limit at 36.8 o C 0.30 o C overshoot

Adaptive Controller Gain 40 Reset 5000 Output comes off high limit at 35.9 o C 0.12 o C overshoot

Adaptive Controller Gain 40 Reset 10000 0.13 o C overshoot Output comes off high limit at 36.1 o C

Integrating and Runaway Process Tuning
It is difficult to prevent overshoot in processes without self-regulation
Controller gain adds self-regulation via closed loop response
Examples of integrating processes (ramping response) are
Liquid and solids level
furnace, column, or vessel pressure
batch composition, pH, or temperature
Examples of runaway processes (accelerating response) are
exothermic reactor temperature
strong acid - strong base pH
exponential growth phase biomass
compressor speed during surge
An over drive of the controller output beyond its resting value is needed to reach a set point or compensate for a disturbance
The maximum allowable controller gain for many integrating processes is well beyond the comfort level of most users. Measurement noise and resolution often sets the practical high limit to the controller gain rather than process dynamics
Too much reset action (too small of a reset time) cause severe overshoot
A higher controller gain creates more overdrive for small setpoint changes and gets controller off it’s output limit sooner for large setpoint changes
There is a window of allowable controller gains.
Instability from too high of a controller gain (not likely for industrial processes)
Slow rolling oscillations from too low of a controller gain (common case) that slowly decay for integrating processes but can grow for runaway processes till it hits physical limits

Fundamentals - Effect of Step Size on Small Valve Response

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

Fundamentals - Limit Cycle in Flow Loop from Valve Stick-Slip Controller Output (%) Saw Tooth Oscillation Process Variable (kpph) Square Wave Oscillation

Fundamentals - Limit Cycle in Level Loop from Valve Deadband Manipulated Flow (kpph) Clipped Oscillation Controller Output (%) Rounded Oscillation Level (%)

Nonlinearity - Graphical Deception Reagent  Influent Ratio Reagent  Influent Ratio Despite appearances there are no straight lines in a titration curve (zoom in reveals another curve if there are enough data points - a big “IF” in neutral region) For a strong acid and base the pK a are off-scale and the slope continually changes by a factor of ten for each pH unit deviation from neutrality (7 pH at 25 o C) Yet titration curves are essential for every aspect of pH system design but you must get numerical values and avoid mistakes such as insufficient data points in the area around the set point 14 12 10 8 6 4 2 0 pH 11 10 9 8 7 6 5 4 3 pH

Effect of Acid and Base Type Slope moderated near each pK a ! Weak Acid and Strong Base pk a = 4 Weak Acid and Weak Base pk a = 4 Strong Acid and Weak Base pk a = 10 Multiple Weak Acids and Weak Bases pk a = 3 pk a = 5 pk a = 9

Effect of Mixing Uniformity and Valve Resolution pH Reagent to Feed Flow Ratio 4 10 6 8 pH Set Point Fluctuations or Oscillations In Flows or Concentrations Control valve resolution (stick-slip) and mixing uniformity requirements are extraordinary on the steepest slope

Control Valve Size and Resolution pH Reagent Flow Influent Flow 6 8 Influent pH B A Control Band Set point B E r =  100%  F imax   F rmax F rmax =  A  F imax B E r =  100%   A S s = 0.5  E r A = distance of center of reagent error band on abscissa from origin B = width of allowable reagent error band on abscissa for control band E r = allowable reagent error (%) F rmax = maximum reagent valve capacity (kg per minute) F imax = maximum influent flow (kg per minute) S s = allowable stick-slip (resolution limit) (%) Most reagent control valves are oversized, which increases the limit cycle amplitude from stick-slip (resolution) and deadband (integrating processes and cascade loops)

Demineralized Water pH Titration Curve Slope pH

Demineralized Water pH Control System Signal characterizers linearize loop via reagent demand control AY 1-4 AC 1-1 AY 1-3 splitter signal characterizer signal characterizer pH set point Eductors LT 1-5 Tank Static Mixer Feed To other Tank Downstream system LC 1-5 From other Tank To other Tank AT 1-3 AT 1-2 AT 1-1 AY 1-1 AY 1-2 middle signal selector FT 1-1 FT 1-2 NaOH Acid

Demineralized Water pH Loop Performance Start of Step 2 (Regeneration) Start of Step 4 (Slow Rinses) One of many spikes of recirculation pH spikes from stick-slip of water valve Tank 1 pH for Reagent Demand Control Tank 1 pH for Conventional pH Control Influent pH

Best Practices to Improve Valve Performance
Actuator, valve, and positioner package from a control valve manufacturer
Digital positioner tuned for valve package and application
Diaphragm actuators where application permits (large valves and high pressure drops may require piston actuators)
Sliding stem (globe) valves where size and fluid permit (large flows and slurries may require rotary valves)
Low stem packing friction
Low sealing and seating friction of the closure components
Booster(s) on positioner output(s) for large valves on fast loops (e.g., compressor anti-surge control)
Valve sizing for a throttle range that provides good linearity [4]:
5% to 75% (sliding stem globe),
10 o to 60 o (v-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 [2]

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

Booster and Positioner Setup (Furnace Pressure and Surge Control) 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

Open Loop Backup Configuration SP_Rate_DN and SP_RATE_UP used to insure fast getaway and slow approach Open loop backup used for prevention of compressor surge and RCRA pH violation Open Loop Backup Configuration

PID Controller Disturbance Response

Open Loop Backup Disturbance Response Open Loop Backup

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Exceptional Process Control Opportunities

by Jim Cahill on Oct 19, 2009

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