The document summarizes Gregory McMillan's presentation on exceptional process control opportunities, including wireless measurement and control, adaptive control, and tuning techniques. Some key areas discussed are using wireless PID control to improve stability for processes with long sample times, adaptive control of integrating processes like batch temperature, and challenges with nonlinearity, deadbands, and stick-slip in control valves.

1. ISA Boston Section Oct 20, 2009 Exceptional Process Control Opportunities

2. 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

3. 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

4. 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

5. 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)

6. 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

7. 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

8. 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

9. 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

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

11. 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

12. 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

13. 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

14. 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

15. 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

16. 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

17. 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

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

19. 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%

20. Wireless SUB Temperature Loop Test Results

21. Wireless SUB pH Loop Test Results

22. 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

23. 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

24. 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.

25. Adaptive Controller Tuning of Integrating Process (Batch Temperature)

26. Adaptive Controller Models of Integrating Process (Batch Temperature)

27. Adaptive Controller Learning Setup of Integrating Process (Batch Temperature)

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

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

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

31. Adaptive Controller Gain 40 Reset 15000 0.20 o C overshoot Output comes off high limit at 36.4 o C

32. Adaptive Controller Gain 80 Reset 15000 0.11 o C overshoot Output comes off high limit at 36.1 o C

33. 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

34. Fundamentals - Effect of Step Size on Small Valve Response

35. 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

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

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

38. 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

39. 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

40. 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

41. 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)

42. Demineralized Water pH Titration Curve Slope pH

43. 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

44. 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

45. 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]

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

47. 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

48. 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

49. PID Controller Disturbance Response

50. Open Loop Backup Disturbance Response Open Loop Backup