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CHE 185 – PROCESS CONTROL AND DYNAMICS

CHE 185 – PROCESS CONTROL AND DYNAMICS. CONTROL LOOP ANALYSIS. METHODS TO FIELD TUNE. FAST-RESPONSE CONTROL LOOPS THESE SYSTEMS CAN BE TUNED TO PROPORTIONAL ONLY TO OBTAIN DATA TO OPTIMIZE THE VALUE FOR K c AT QAD (Quarter amplitude damping).

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CHE 185 – PROCESS CONTROL AND DYNAMICS

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  1. CHE 185 – PROCESS CONTROL AND DYNAMICS CONTROL LOOP ANALYSIS

  2. METHODS TO FIELD TUNE • FAST-RESPONSE CONTROL LOOPS • THESE SYSTEMS CAN BE TUNED TO PROPORTIONAL ONLY TO OBTAIN DATA TO OPTIMIZE THE VALUE FOR Kc AT QAD (Quarter amplitude damping). • THE INTEGRAL SETTINGS CAN THEN BE TUNED TO OPTIMIZE THE RESET CAPABILITY • THERE WILL BE A BALANCE BETWEEN THE SPEED OF RESPONSE AND THE SPEED FOR RESET

  3. METHODS TO FIELD TUNE • SLOW-RESPONSE CONTROL LOOPS • THE APPROACH IS TO MAKE SMALL CYCLICAL STEP CHANGES AND USE THE RESPONSES TO CHARACTERIZE THE PROCESS PARAMETERS • SEE AUTOTUNE VARIATION (ATV) METHOD RESULTS IN FIGURE 9.11.1 • CHARACTERIZATION IS BASED ON THE RATIO OF MEASURED AND SETPOINT AMPLITUDES, THE ULTIMATE GAIN AND THE ULTIMATE PERIOD ASSOCIATED WITH THIS TEST IS THE TIME BETWEEN CYCLE PEAKS for proportional only control

  4. METHODS TO FIELD TUNE • THE VALUES FROM THE TESTS ARE THEN USED WITH RECOMMENDED TUNING SCHEMES: • ZIEGLER-NICHOLS • TYREUS AND LUYBEN • FINE TUNING FROM THESE INITIAL VALUES MUST HAVE SIMULTANEOUS ADJUSTMENTS IN Kc AND τI, TYPICALLY USING A TUNING FACTOR F:

  5. Field Tuning Approach • Turn off integral and derivative action. • Make initial estimate of Kc based on process knowledge. • Using setpoint changes, increase Kc until tuning criterion is met

  6. Field Tuning Approach • DecreaseKcby 10%. • Make initial estimate ofτI(i.e.,τI=5τp). • ReduceτIuntil offset is eliminated • Check that proper amount of KcandτIare used.

  7. Example of Inadequate Integral Action • Oscillations not centered about setpoint and slow offset removal indicate inadequate integral action.

  8. AUTOTUNE VARIATION ATV • Identification and Online Tuning • Perform ATV test and determine ultimate gain and ultimate period. • Select tuning method (i.e., ZN or TL settings). • Adjust tuning factor, FT, to meet tuning criterion online using setpoint changes or observing process performance: • Kc=KcZN/FTτI=τIZN×FT

  9. ATV Test • Select h so that process is not unduly upset but an accurate a results. • Controller output is switched when yscrosses y0 • It usually take 3-4 cycles before standing is established and aandPucan be measured.

  10. Applying the ATV Results • Calculate Kufrom ATV results. • ZN settings • TL settings

  11. Comparison of ZN and TL Settings • ZN settings are too aggressive in many cases while TL settings tend to be too conservative. • TL settings use much less integral action compared to the proportional action than ZN settings. As a result, in certain cases when using TL settings, additional integral action is required to remove offset in a timely fashion.

  12. Advantages of ATV Identification • Much faster than open loop test. • As a result, it is less susceptible to disturbances • Does not unduly upset the process.

  13. Online ATV Tuning EXAMPLE • Provides simple one-dimensional tuning which can be applied using setpoint changes or observing controller performance over a period of time.

  14. ATV Test Applied to Composition Mixer

  15. METHODS TO FIELD TUNE • SOME TUNING METHODS HAVE BEEN DEVELOPED FOR SPECIFIC PROCESSES • LEVEL CONTROL - MARLIN RELATIONSHIPS FOR CRITICALLY DAMPED SYSTEMS - SEE EQUATIONS 9.13.1 AND 9.13.2 • INTERFACE WITH DIstributed CONTROL SYSTEMS • CONTROL INTERVAL IS THE SAMPLING TIME FOR A DCS – eqn. 9.14.1 • NEEDS TO BE A FUNCTION OF THE PROCESS DEADTIME AND TIME CONSTANT

  16. Controller Reliability • The ability of a controller to remain in stable operation with acceptable performance in the face of the worst disturbances that the controller is expected to handle.

  17. Controller Reliability • Analysis of the closed loop transfer function for a disturbance shows that the type of dynamic response (i.e., decay ratio) is unaffected by the magnitude to the disturbance.

  18. Controller Reliability • NON-LINEAR EFFECTS – FIGURE 9.6.2 • from industrial experience We know that certain large magnitude disturbance can cause control loops to become unstable. • The explanation of this apparent contradiction is that disturbances can cause significant changes in Kp, τp, and θp which a linear analysis does not consider.

  19. Controller Reliability • Example: CSTR with ΔCA0 Upsets

  20. Controller Reliability • Is determined by the combination of the following factors • Process nonlinearity • Disturbance type • Disturbance magnitude and duration • If process nonlinearity is high but disturbance magnitude is low, reliability is good. • If disturbance magnitude is high but process nonlinearity is low, reliability is good.

  21. Tuning Criterion Selection • EXAMPLE WITH CHOICE BETWEEN FEED RATE OR RECEIVER LEVEL • CONSIDER REACTOR RESIDENCE TIME

  22. Tuning Criterion Selection • EXAMPLE WITH CHOICE BETWEEN FEED RATE OR RECEIVER LEVEL • CONSIDER REACTOR RESIDENCE TIME

  23. Tuning Criterion Selection • EXAMPLE WITH CHOICE BETWEEN REACTOR COMPOSITION AND SEPARATION

  24. Tuning Criterion Selection Procedure • First, based on overall process objectives, evaluate controller performance for the loop in question. • If the control loop should be detuned based on the overall process objectives, the tuning criterion is set. • If the control loop should be tuned aggressively based on the overall process objectives, the tuning criterion is selected based on a compromise between performance and reliability.

  25. Tuning SELECTION Criterion • IS a Compromise between Performance and Reliability • Select the tuning criterion (typically from critically damped to 1/6 decay ratio) based on the process characteristics: • Process nonlinearity • Disturbance types and magnitudes

  26. Effect of Tuning Criterion on Control Performance • The more aggressive the control criterion, the better the control performance, but the more likely the controller can go unstable.

  27. Filtering the Sensor Reading • For most sensor readings, a filter time constant of 3 to 5 s is more than adequate and does not slow down the closed-loop dynamics. • For a noisy sensor, sensor filtering usually slows the closed-loop dynamics. To evaluate compare the filter time constant with the time constants for the acutator, process and sensor.

  28. Recommended Tuning Approach • Select the tuning criterion for the control loop. • Apply filtering to the sensor reading • Determine if the control system is fast or slow responding. • For fast responding, field tune (trail-and-error) • For slow responding, apply ATV-based tuning

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