Interactive Opportunity Assessment Demo and Seminar (Deminar) Series  for Web Labs – Process Control Improvement Primer Se...
Welcome <ul><li>Gregory K. McMillan  </li></ul><ul><ul><li>Greg is a retired Senior Fellow from Solutia/Monsanto and an IS...
“ Top Ten Things You Don’t Want to Hear During Startup” Courtesy of Hunter Vegas (October 2010 Control Talk) <ul><li>(10) ...
“ Top Ten Things You Don’t Want to  Hear  During Startup” Courtesy of Hunter Vegas (October 2010 Control Talk) <ul><li>(1)...
Introduction <ul><li>There is no clear picture of what is the potential source and size of a process control improvement  ...
Unifying Concepts <ul><li>“ It is all about management of change” </li></ul><ul><ul><li>90% of process control improvement...
Delay <ul><li>“ Without deadtime I would be out of a job” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>A more desc...
Speed (Rate of Change) <ul><li>“ Speed kills - (high speed processes and disturbances and low speed control systems can ki...
Gain <ul><li>“ All is lost if nothing is gained” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>Gain is the change i...
Sensitivity-Resolution  <ul><li>“ You cannot control what you cannot see” </li></ul><ul><li>Fundamentals </li></ul><ul><ul...
Backlash-Deadband <ul><li>“ No problem if you don’t ever change direction” </li></ul><ul><li>Fundamentals </li></ul><ul><u...
Nonlinearity <ul><li>“ Not a problem if the process is constant, but then again if the process is constant, you do not nee...
Noise <ul><li>“ The best thing you can do is not react to noise” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>Extr...
Oscillations <ul><li>“ Oscillations are best kept in control theory textbooks” </li></ul><ul><li>Fundamentals </li></ul><u...
Resonance <ul><li>“ Don’t make things worse than they already are” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>Os...
Attenuation <ul><li>“ If you had a blend tank big enough you would not need control” </li></ul><ul><li>Fundamentals </li><...
Optimum <ul><li>“ Most setpoints are not at their optimum” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>The primar...
Time (seconds) % Controlled Variable (CV)  or % Controller Output (CO)  CO  CV  o  p2 K p  =   CV   CO   CV ...
Integrating Process  Open Loop Response Maximum speed in 4 deadtimes is critical speed Time (seconds)  o K i  =  { [ CV 2...
Runaway Process  Open Loop Response Response to change in controller output with controller in manual  o Noise Band Accel...
Loop Block Diagram (First Order Approximation)  p1  p2  p2 K pv  p1  c1  m2  m2  m1  m1 K cv  c  c2 Valve Proce...
<ul><li> CV    change in controlled variable (%) </li></ul><ul><li> CO    change in controller output (%) </li></ul><u...
Impact of Fast and Slow Disturbances <ul><li>Objective  – Show the effect of disturbance speed </li></ul><ul><li>Activitie...
Practical Limit to Loop Performance Peak error decreases as the controller gain increases but is essentially the  open loo...
Ultimate Limit to Loop Performance Peak error is proportional to the ratio of loop deadtime to 63% response time Integrate...
Disturbance Speed and Attenuation Effect of load disturbance lag (  L ) can be estimated by replacing the open loop error...
Implied Deadtime from Slow Tuning Slow tuning (large Lambda) creates an implied deadtime where the loop performs about the...
Effect of Implied Deadtime on Allowable Digital or Analyzer Delay In this self-regulating process the original process del...
Fastest Practical PID Tuning Settings (Practical Limit to Loop Performance)  For runaway processes: For self-regulating pr...
Effect of Tuning Speed  on Oscillatory Disturbance 1 Ultimate Period 1 1 Faster Tuning Log of Ratio of closed loop amplitu...
Visit  http://www.processcontrollab.com/   to Create Valuable New Skills <ul><li>Free State of the Art Virtual Plant </li>...
Help Us Improve These Deminars! WouldYouRecommend.Us/105679s21/
Join Us Oct 13, Wednesday  10:00 am  CDT <ul><li>PID Deadtime Compensation  (How to setup and tune a PID for deadtime comp...
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Process Control Improvement Primer - Greg McMillan Deminar

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Process Control Improvement Primer - Greg McMillan Deminar

  1. 1. Interactive Opportunity Assessment Demo and Seminar (Deminar) Series for Web Labs – Process Control Improvement Primer Sept 8, 2010 Sponsored by Emerson, Experitec, and Mynah Created by Greg McMillan and Jack Ahlers www.processcontrollab.com Website - Charlie Schliesser (csdesignco.com)
  2. 2. Welcome <ul><li>Gregory K. McMillan </li></ul><ul><ul><li>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/ </li></ul></ul>
  3. 3. “ Top Ten Things You Don’t Want to Hear During Startup” Courtesy of Hunter Vegas (October 2010 Control Talk) <ul><li>(10) We never really could figure out what the old system was doing. </li></ul><ul><li>(9) Do I have a system backup?!? I thought YOU were making backups! </li></ul><ul><li>(8) They want to make our startup into a reality show. </li></ul><ul><li>(7) The displays are fine and dandy but where are the panel boards? </li></ul><ul><li>(6) We have changed our mind – we want the old system back. </li></ul><ul><li>(5) Can you reprogram it so the wrong valve still works? </li></ul><ul><li>(4) Didn’t you get the revised batch sheets? </li></ul><ul><li>(3) Is a blue screen bad?? </li></ul><ul><li>(2) What is that burning smell? </li></ul><ul><li>And the Number 1 thing you don’t want to hear : </li></ul>
  4. 4. “ Top Ten Things You Don’t Want to Hear During Startup” Courtesy of Hunter Vegas (October 2010 Control Talk) <ul><li>(1) We are out of coffee! </li></ul>
  5. 5. Introduction <ul><li>There is no clear picture of what is the potential source and size of a process control improvement </li></ul><ul><li>Practical process control knowledge is detailed, fragmented, and experience driven </li></ul><ul><li>This seminar will attempt to provide a unified approach and understanding of the impact of the PID, final control element (e.g. valve or variable speed drive), process, disturbance, and measurement on loop performance </li></ul>
  6. 6. Unifying Concepts <ul><li>“ It is all about management of change” </li></ul><ul><ul><li>90% of process control improvements involve the following concepts: </li></ul></ul><ul><ul><li>Delay </li></ul></ul><ul><ul><li>Speed </li></ul></ul><ul><ul><li>Gain </li></ul></ul><ul><ul><li>Sensitivity-Resolution </li></ul></ul><ul><ul><li>Backlash-Deadband </li></ul></ul><ul><ul><li>Nonlinearity </li></ul></ul><ul><ul><li>Noise </li></ul></ul><ul><ul><li>Oscillations </li></ul></ul><ul><ul><li>Resonance </li></ul></ul><ul><ul><li>Attenuation </li></ul></ul><ul><ul><li>Optimum </li></ul></ul>Delay, speed, and gain are the most prevalent limiting concepts
  7. 7. Delay <ul><li>“ Without deadtime I would be out of a job” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>A more descriptive name would be total loop deadtime . The loop deadtime is the amount of time for the start of a change to completely circle the control loop and end up at the point of origin. For example, an unmeasured disturbance cannot be corrected until the change is seen and the correction arrives in the process at the same point as the disturbance. </li></ul></ul><ul><ul><li>While process deadtime offers a continuous train of values whereas digital devices and analyzers offer non continuous data values at discrete intervals, these delays add a phase shift and increase the ultimate period (decrease natural frequency) like process deadtime. </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Minimize delay (the loop cannot do anything until it sees and enacts change) </li></ul></ul><ul><li>Sources </li></ul><ul><ul><li>Pure delay from deadtimes and discontinuous updates </li></ul></ul><ul><ul><ul><li>Piping, duct, plug flow reactor, conveyor, extruder, spin-line, and sheet transportation delays </li></ul></ul></ul><ul><ul><ul><li>Digital devices - scan, update, reporting, and execution times (0.5  T) </li></ul></ul></ul><ul><ul><ul><li>Analyzers - sample processing and analysis cycle time (1.5  T) </li></ul></ul></ul><ul><ul><ul><li>Sensitivity-resolution limits </li></ul></ul></ul><ul><ul><ul><li>Backlash-deadband </li></ul></ul></ul><ul><ul><li>Equivalent delay from lags </li></ul></ul><ul><ul><ul><li>Mixing </li></ul></ul></ul><ul><ul><ul><li>Column trays </li></ul></ul></ul><ul><ul><ul><li>Heat transfer surfaces </li></ul></ul></ul><ul><ul><ul><li>Thermowells </li></ul></ul></ul><ul><ul><ul><li>Electrodes </li></ul></ul></ul><ul><ul><ul><li>Transmitter damping </li></ul></ul></ul><ul><ul><ul><li>Signal filters </li></ul></ul></ul>
  8. 8. Speed (Rate of Change) <ul><li>“ Speed kills - (high speed processes and disturbances and low speed control systems can kill performance)” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>The rate of change in 4 deadtime intervals is most important. By the end of 4 deadtimes, the control loop should have completed most of its correction. Thus, the short cut tuning method (Deminar #6) is consistent with performance objectives. </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Make control systems faster and make processes and disturbances slower </li></ul></ul><ul><li>Sources </li></ul><ul><ul><li>Control system </li></ul></ul><ul><ul><ul><li>PID tuning settings (gain, reset, and rate) </li></ul></ul></ul><ul><ul><ul><li>Slewing rate of control valves and velocity limits of variable speed drives </li></ul></ul></ul><ul><ul><li>Disturbances </li></ul></ul><ul><ul><ul><li>Steps - Batch operations, on-off control, manual actions, SIS, startups, and shutdowns </li></ul></ul></ul><ul><ul><ul><li>Oscillations - limit cycles, interactions, and excessively fast PID tuning </li></ul></ul></ul><ul><ul><ul><li>Ramps - reset action in PID </li></ul></ul></ul><ul><ul><li>Process </li></ul></ul><ul><ul><ul><li>Mixing in volumes due to agitation, boiling, mass transfer, diffusion, and migration </li></ul></ul></ul>
  9. 9. Gain <ul><li>“ All is lost if nothing is gained” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>Gain is the change in output for a change in input to any part of the control system. Thus there is a gain for the PID, valve, disturbance, process, and measurement. Knowing the disturbance gain (e.g. change in manipulated flow per change in disturbance) is important for sizing valves and feedforward control. </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Maximize control system gains (maximize control system reaction to change) and minimize process and disturbance gains (minimize process reaction to change). </li></ul></ul><ul><li>Sources </li></ul><ul><ul><li>PID controller gain </li></ul></ul><ul><ul><li>Inferential measurements (e.g. temperature change for composition change in distillation column) </li></ul></ul><ul><ul><li>Slope of control valve or variable speed drive installed characteristic (inherent characteristic & system loss curve) </li></ul></ul><ul><ul><li>Measurement calibration (100% / span). Important where accuracy is % of span </li></ul></ul><ul><ul><li>Process design </li></ul></ul><ul><ul><li>Attenuation by volumes (can be estimated) </li></ul></ul><ul><ul><li>Attenuation by PID (transfer of variability from controlled to manipulated variables) </li></ul></ul>
  10. 10. Sensitivity-Resolution <ul><li>“ You cannot control what you cannot see” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>Minimum change measured or manipulated - once past sensitivity limit full change is seen or used but resolution limit will quantize the change (stair step where the step size is the resolution limit). Both will cause a limit cycle if there is an integrator in the process or control system. </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Improve sensitivity and resolution </li></ul></ul><ul><li>Sources </li></ul><ul><ul><li>In measurements, minimum change detected and communicated (e.g. sensor threshold and wireless update trigger level) and quantized change (A/D & D/A) </li></ul></ul><ul><ul><li>Minimum change that can be manipulated (e.g. valve stick-slip sensitivity and speed resolution) </li></ul></ul>
  11. 11. Backlash-Deadband <ul><li>“ No problem if you don’t ever change direction” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>Minimum change measured or manipulated once the direction is changed - once past backlash-deadband limit full change is seen or used. Both will cause a limit cycle if there are 2 or more integrators in the process or control system. </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Minimize backlash and deadband </li></ul></ul><ul><li>Sources </li></ul><ul><ul><li>Pneumatic instrument flappers, links, and levers (hopefully these are long gone) </li></ul></ul><ul><ul><li>Rotary valve and damper links, connections, and shaft windup </li></ul></ul><ul><ul><li>Variable speed drive setup parameter to eliminate hunting and chasing noise </li></ul></ul>
  12. 12. Nonlinearity <ul><li>“ Not a problem if the process is constant, but then again if the process is constant, you do not need a control system” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>While normally associated with a process gain that is not constant, in a broader concept, a nonlinear system occurs if a gain, time constant, or delay changes anywhere in the loop. All process control systems are nonlinear to some degree. </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Minimize nonlinearity </li></ul></ul><ul><li>Sources </li></ul><ul><ul><li>Control valve and variable speed drive installed characteristics (flat at high flows) </li></ul></ul><ul><ul><li>Process transportation delays (inversely proportional to flow) </li></ul></ul><ul><ul><li>Digital and analyzer delays (loop delay depends upon when change arrives in discontinuous data value update interval) </li></ul></ul><ul><ul><li>Inferred measurement (conductivity or temperature vs. composition plot is a curve) </li></ul></ul><ul><ul><li>Logarithmic relationship (glass pH electrode and zirconium oxide oxygen probe) </li></ul></ul><ul><ul><li>Process time constants (proportional to volume and density) </li></ul></ul>
  13. 13. Noise <ul><li>“ The best thing you can do is not react to noise” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>Extraneous fluctuations in measured or manipulated variables </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Minimize size and frequency of noise and do not transfer noise to process </li></ul></ul><ul><li>Sources </li></ul><ul><ul><li>Bubbles </li></ul></ul><ul><ul><li>Concentration and temperature non-uniformity from imperfect mixing </li></ul></ul><ul><ul><li>Electromagnetic interference (EMI) </li></ul></ul><ul><ul><li>Ground loops </li></ul></ul><ul><ul><li>Interferences (e.g. sodium ion on pH electrode) </li></ul></ul><ul><ul><li>Velocity profile non-uniformity </li></ul></ul><ul><ul><li>Velocity impact on pressure sensors </li></ul></ul>
  14. 14. Oscillations <ul><li>“ Oscillations are best kept in control theory textbooks” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>Sine wave, square wave, and saw-tooth periodic disturbances perpetually upset a system and can get amplified by resonance. </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Minimize source and attenuate by controller tuning and process design </li></ul></ul><ul><li>Sources </li></ul><ul><ul><li>Limit cycles from sensitivity-resolution and backlash-deadband </li></ul></ul><ul><ul><li>On-off control (common for sump level control by switches) </li></ul></ul><ul><ul><li>Aggressive tuning (common for reactor temperature control) </li></ul></ul><ul><ul><li>Excessive reset action (common for level and other integrating processes) </li></ul></ul>
  15. 15. Resonance <ul><li>“ Don’t make things worse than they already are” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>Oscillation period close to ultimate period can be amplified by feedback control. </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Make oscillation period slower or control loop faster </li></ul></ul><ul><li>Sources </li></ul><ul><ul><li>Control loops in series with similar loop deadtimes (e.g. multiple stage pH control) </li></ul></ul><ul><ul><li>Control loops in series with similar tuning and valve sticktion and backlash </li></ul></ul><ul><ul><li>Day to night ambient changes to slow loops (e.g. column temperature control) </li></ul></ul>
  16. 16. Attenuation <ul><li>“ If you had a blend tank big enough you would not need control” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>Attenuation increases as the volume of the blend tank increases and the ultimate period of the control loop decreases. </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Maximize attenuation by increasing volume and mixing and making loops faster </li></ul></ul><ul><li>Sources </li></ul><ul><ul><li>Mixed volume size and degree of mixing </li></ul></ul><ul><ul><li>Control loop speed </li></ul></ul>
  17. 17. Optimum <ul><li>“ Most setpoints are not at their optimum” </li></ul><ul><li>Fundamentals </li></ul><ul><ul><li>The primary loop setpoint is offset from the optimum temperature, pressure, or concentration. </li></ul></ul><ul><li>Goals </li></ul><ul><ul><li>Minimize offset from optimum </li></ul></ul><ul><li>Sources (of non-optimum operation) </li></ul><ul><ul><li>Process variability </li></ul></ul><ul><ul><li>Measurement error </li></ul></ul><ul><ul><li>Sensitivity-resolution </li></ul></ul><ul><ul><li>Backlash-deadband </li></ul></ul><ul><ul><li>Lack of process knowledge </li></ul></ul><ul><ul><li>Process nonlinearity (e.g. catalyst degradation and production rate changes) </li></ul></ul><ul><ul><li>Operator preference (e.g. sweet spots) </li></ul></ul><ul><ul><li>Incorrect SIS settings </li></ul></ul>
  18. 18. Time (seconds) % Controlled Variable (CV) or % Controller Output (CO)  CO  CV  o  p2 K p =  CV  CO  CV CO CV Self-regulating process open loop negative feedback time constant Self-regulating process gain (%/%) Response to change in controller output with controller in manual observed total loop deadtime Self-Regulating Process Open Loop Response  o or Maximum speed in 4 deadtimes is critical speed
  19. 19. Integrating Process Open Loop Response Maximum speed in 4 deadtimes is critical speed Time (seconds)  o K i = { [ CV 2  t 2 ]  CV 1  t 1 ] }  CO  CO ramp rate is  CV 1  t 1 ramp rate is  CV 2  t 2 CO CV Integrating process gain (%/sec/%) Response to change in controller output with controller in manual % Controlled Variable (CV) or % Controller Output (CO) observed total loop deadtime
  20. 20. Runaway Process Open Loop Response Response to change in controller output with controller in manual  o Noise Band Acceleration  CV  CO  CV K p =  CV  CO Runaway process gain (%/%) % Controlled Variable (CV) or % Controller Output (CO) Time (seconds) observed total loop deadtime runaway process open loop positive feedback time constant For safety reasons, tests are terminated after 4 deadtimes or Maximum speed in 4 deadtimes is critical speed  ’ p2  ’ o
  21. 21. Loop Block Diagram (First Order Approximation)  p1  p2  p2 K pv  p1  c1  m2  m2  m1  m1 K cv  c  c2 Valve Process Controller Measurement K mv  v  v K L  L  L Load Upset  CV  CO  MV  PV PID Delay Lag Delay Delay Delay Delay Delay Delay Lag Lag Lag Lag Lag Lag Lag Gain Gain Gain Gain Local Set Point  DV First Order Approximation :  o  v  p1  p2  m1  m2  c  v  p1  m1  m2  c1  c2 % % % Delay => Dead Time Lag =>Time Constant K i = K mv  (K pv /  p2 )  K cv 100% / span K c T i T d
  22. 22. <ul><li> CV  change in controlled variable (%) </li></ul><ul><li> CO  change in controller output (%) </li></ul><ul><li>K c  controller gain (dimensionless) </li></ul><ul><li>K i  integrating process gain (%/sec/% or 1/sec) </li></ul><ul><li>K p  process gain (dimensionless) also known as open loop gain </li></ul><ul><li>MV  manipulated variable (engineering units) </li></ul><ul><li>PV  process variable (engineering units) </li></ul><ul><li> t  change in time (sec) </li></ul><ul><li> t s  sample time (sec) </li></ul><ul><li> o  total loop dead time (sec) </li></ul><ul><li> f  filter time constant (sec) </li></ul><ul><li> m  measurement time constant (sec) </li></ul><ul><li> p2  primary (large) self-regulating process time constant (sec) </li></ul><ul><li> ’ p2  primary (large) runaway process time constant (sec) </li></ul><ul><li> p1  secondary (small) process time constant (sec) </li></ul><ul><li>T i  integral (reset) time setting (sec/repeat) </li></ul><ul><li>T d  derivative (rate) time setting (sec) </li></ul><ul><li>T o  oscillation period (sec) </li></ul><ul><li>  Lambda (closed loop time constant or arrest time) (sec) </li></ul><ul><li> f   Lambda factor (ratio of closed to open loop time constant or arrest time) </li></ul>Nomenclature
  23. 23. Impact of Fast and Slow Disturbances <ul><li>Objective – Show the effect of disturbance speed </li></ul><ul><li>Activities: </li></ul><ul><ul><li>For Single Self-Regulating Loop: </li></ul></ul><ul><ul><ul><li>Review fast upset test (primary upset lag and reset time = 6 seconds) </li></ul></ul></ul><ul><ul><ul><li>Increase primary upset lag to 60 seconds </li></ul></ul></ul><ul><ul><ul><li>After about 5 minutes review slow load upset test results </li></ul></ul></ul>
  24. 24. Practical Limit to Loop Performance Peak error decreases as the controller gain increases but is essentially the open loop error for systems when total deadtime >> process time constant Integrated error decreases as the controller gain increases and reset time decreases but is essentially the open loop error multiplied by the reset time plus signal delays and lags for systems when total deadtime >> process time constant Peak and integrated errors cannot be better than ultimate limit - The errors predicted by these equations for the PIDPlus and deadtime compensators cannot be better than the ultimate limit set by the loop deadtime and process time constant
  25. 25. Ultimate Limit to Loop Performance Peak error is proportional to the ratio of loop deadtime to 63% response time Integrated error is proportional to the ratio of loop deadtime squared to 63% response time For a sensor lag (e.g. electrode or thermowell lag) or signal filter that is much larger than the process time constant, the unfiltered actual process variable error can be found from the equation for attenuation
  26. 26. Disturbance Speed and Attenuation Effect of load disturbance lag (  L ) can be estimated by replacing the open loop error with the exponential response of the disturbance during the loop deadtime The attenuation of oscillations van be estimated from the expression of the Bode plot equation for the attenuation of oscillations slower than the break frequency where (  f ) is the filter time constant, electrode or thermowell lag, or a mixed volume residence time
  27. 27. Implied Deadtime from Slow Tuning Slow tuning (large Lambda) creates an implied deadtime where the loop performs about the same as a loop with fast tuning and an actual deadtime equal to the implied deadtime (  i )
  28. 28. Effect of Implied Deadtime on Allowable Digital or Analyzer Delay In this self-regulating process the original process delay (dead time) was 10 sec. Lambda was 20 sec and the sample time was set at 0, 5, 10, 20, 30, and 80 sec (Loops 1 - 6) The loop integrated error increased slightly by 1%*sec for a sample time of 10 sec which corresponded to a total deadtime (original process deadtime + 1/2 sample time) equal to the implied deadtime of 15 seconds. http://www.modelingandcontrol.com/repository/AdvancedApplicationNote005.pdf sample time = 0 sec sample time = 5 sec sample time = 10 sec sample time = 20 sec sample time = 30 sec sample time = 80 sec Effect depends on tuning, which leads to miss-guided generalities based on process dynamics
  29. 29. Fastest Practical PID Tuning Settings (Practical Limit to Loop Performance) For runaway processes: For self-regulating processes: For integrating processes: short cut tuning method (near integrator approximation) short cut tuning method (near integrator approximation)
  30. 30. Effect of Tuning Speed on Oscillatory Disturbance 1 Ultimate Period 1 1 Faster Tuning Log of Ratio of closed loop amplitude to open loop amplitude Log of ratio of disturbance period to ultimate period no attenuation of disturbances resonance (amplification) of disturbances amplitude ratio is proportional to ratio of break frequency lag to disturbance period 1 no better than manual worse than manual improving control
  31. 31. Visit http://www.processcontrollab.com/ to Create Valuable New Skills <ul><li>Free State of the Art Virtual Plant </li></ul><ul><li>Independent Interactive Study </li></ul><ul><li>Learn in 10 minutes rather than 10 years </li></ul><ul><li>Online Performance Metrics </li></ul><ul><li>Standard Operator Graphics & Historian </li></ul><ul><li>Control Room Type Environment </li></ul><ul><li>No Modeling Expertise Needed </li></ul><ul><li>No Configuration Expertise Needed </li></ul><ul><li>Rapid Risk-Free Plant Experimentation </li></ul><ul><li>Deeper Understanding of Concepts </li></ul><ul><li>Process Control Improvement Demos </li></ul><ul><li>Sample Lessons (Recorded Deminars) </li></ul>
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