Effects of Macrocycle Time and Sampling Rates on Control Loop Performance
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Emerson Exchange 2009 presentation by consultants Dan Daugherty, Ferrill Ford, and Mark Coughran.
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Effects of Macrocycle Time and Sampling Rates on Control Loop Performance
- 1. Effects of Macrocycle Time and Sampling Rates on Control Loop Performance Dan Daugherty – Sr. Engineer – Product Engineering Ferrill Ford – Sr. Engineer – Product Engineering Mark Coughran – Sr. Industry Consultant – Industry Solutions Group
- 6. 3 rd Loop – Marshalltown Flow Lab PV PT Disturbance EnTech Toolkit
- 7. Timing – 4-20mA PID D/A Conversion DVC 4-20/HART Pneumatic Actuator DVC dead time and time constant Load Valve Motion Hydraulic Pressure (Process) Change 3051 4-20/HART output 3051C Dead Time and Time Constant A/D Conversion
- 8. Timing – FF CIF FF PID FF AO Pneumatic Actuator DVC dead time and time constant Load Valve Motion Hydraulic Pressure (Process) Change 3051 FF AI 3051C Dead Time and Time Constant FF Compel Data
- 9. Control Response Period by subtraction 4-20 mA / HART 0.05 sec Load Valve Motion Hydraulic Pressure (Process) 3051C Dead Time and Time Constant 3051C 4-20 output PID A/D DVC 4-20 input D/A DVC6000 Dead Time and Time Constant Pneumatic Actuator Fast Reference Pressure Sensor 0-750 psig Fast Reference Pressure Sensor 0-50 psig Control Response Period Typical Customer Spec. 0.07 sec Measured Loop Dead Time In Load Step Test
- 10. Control Response Period by subtraction Foundation Fieldbus Control-In-the-Field (CIF) 0.10 sec Load Valve Motion Hydraulic Pressure (Process) 3051 Dead Time and Time Constant 3051 FF AI FF PID FF Compel Data FF AO DVC6000f Dead Time and Time Constant Pneumatic Actuator Fast Reference Pressure Sensor 0-750 psig Fast Reference Pressure Sensor 0-50 psig Control Response Period Typical Customer Spec. 0.07 sec Measured Loop Dead Time In Load Step Test
- 12. Sample Control Response Period measurement CIC, module execution = 1.0, macrocycle = 0.5 1.37 – 0.10 – 0.07 = 1.20 seconds
- 13. Sample Control Response Period measurement 4-20 mA, module execution = 0.2 0.30 – 0.05 – 0.07 = 0.18 seconds
- 14. Sample histogram from 21 measurements CIC, module execution = 1.0, macrocycle = 0.5 Mean value of raw dead time = 1.39 seconds Corrected value (Control Response Period) = 1.22 seconds
- 15. Control Response Period results overview 4-20 mA, DeltaV Control in DVC (CIF) Control in DeltaV (CIC) 2:1 Control in DeltaV (CIC) 4:1 Control in DeltaV (CIC) 1:1 Ratio for Fieldbus Control in DeltaV is Module Execution : Macrocycle
- 17. Lambda Tuning for self-regulating process sample Manual step 5% on controller output
- 18. Average process dynamics and recommended tuning
- 20. Theoretical setpoint step response
- 21. Theoretical load frequency response
- 23. Load Frequency Response, period 100, CIC, module execution = 1.0, macrocycle = 1.0 AR = 0.41
- 24. Load Frequency Response, period 100, CIC, module execution = 0.5, macrocycle = 0.5 AR = 0.26
- 25. Load Frequency Response, period 100, CIC, module execution = 1.0, macrocycle = 0.5 AR = 0.38
- 26. Load Frequency Response, period 100, CIF, macrocycle = 0.15 AR = 0.18
- 27. What if 8 loops on the FF segment? CIC (DeltaV) theoretical
- 28. What if 8 loops on the FF segment? CIF (DVC) theoretical
- 36. Setpoint step test sample data
- 37. Setpoint step test sample data
- 38. Setpoint step test sample data
Hinweis der Redaktion
- Unlike older tuning methods such as Ziegler-Nichols, Lambda tuning gives a smooth non-oscillatory response. But equally important is the ability to design Lambda for the loop requirements. Lambda can be selected based on the performance requirements of the particular loop to separate the dynamics of interacting loops to establish fast vs. slow for inner vs. outer (slave vs. master) loops The testing that we use to determine the process dynamics, required for Lambda tuning, also identifies problems with the control equipment.
- Unlike older tuning methods such as Ziegler-Nichols, Lambda tuning gives a smooth non-oscillatory response. But equally important is the ability to design Lambda for the loop requirements. Lambda can be selected based on the performance requirements of the particular loop to separate the dynamics of interacting loops to establish fast vs. slow for inner vs. outer (slave vs. master) loops The testing that we use to determine the process dynamics, required for Lambda tuning, also identifies problems with the control equipment.
- Add experimental data to support the Bode plot