Exceptional Opportunities in Process Control presented by Greg McMillan at ISA Boston Section's October-2009 meeting.

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

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

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

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

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

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

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