1 / 62

Chapter 7

Chapter 7. PID Controller Tuning. Controller Tuning. Involves selection of the proper values of K c , t I , and t D . Affects control performance. Affects controller reliability Therefore, controller tuning is, in many cases, a compromise between performance and reliability.

alyssa-mclean
Download Presentation

Chapter 7

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Chapter 7 PID Controller Tuning

  2. Controller Tuning • Involves selection of the proper values of Kc, tI, and tD. • Affects control performance. • Affects controller reliability • Therefore, controller tuning is, in many cases, a compromise between performance and reliability.

  3. Tuning Criteria • Specific criteria • Decay ratio • Minimize settling time • General criteria • Minimize variability • Remain stable for the worst disturbance upset (i.e., reliability) • Avoid excessive variation in the manipulated variable

  4. Decay Ratio for Non-Symmetric Oscillations

  5. Performance Assessment • Performance statistics (IAE, ISE, etc.) which can be used in simulation studies. • Standard deviation from setpoint which is a measure of the variability in the controlled variable. • SPC charts which plot product composition analysis along with its upper and lower limits.

  6. Example of an SPC Chart

  7. P-only Control • For an open loop overdamped process as Kc is increased the process dynamics goes through the following sequence of behavior • overdamped • critically damped • oscillatory • ringing • sustained oscillations • unstable oscillations

  8. Dynamic Changes as Kc is Increased for a FOPDT Process

  9. Root Locus Diagram(Kc increases a to g)

  10. Effect of Kc on Closed-Loop z

  11. Effect of Kc on Closed-Loop tp

  12. P-only Controller Applied to First-Order Process without Deadtime • Without deadtime, the system will not become unstable regardless of how large Kc is. • First-order process model does not consider combined actuator/process/sensor system. • Therefore, first-order process model without deadtime is not a realistic model of a process under feedback control.

  13. PI Control • As Kc is increased or tI is decreased (i.e., more aggressive control), the closed loop dynamics goes through the same sequence of changes as the P-only controller: overdamped, critically damped, oscillatory, ringing, sustained oscillations, and unstable oscillations.

  14. Effect of Variations in Kc Effect of Variations in tI

  15. Analysis of the Effect of Kc and tI • When there is too little proportional action or too little integral action, it is easy to identify. • But it is difficult to differentiate between too much proportional action and too much integral action because both lead to ringing.

  16. Response of a Properly Tuned PI Controller

  17. Response of a PI Controller with Too Much Proportional Action

  18. Response of a PI Controller with Too Much Integral Action

  19. PID Control • Kc and tI have the same general effect as observed for PI control. • Derivative action tends to reduce the oscillatory nature of the response and results in faster settling for systems with larger deadtime to time constant ratios.

  20. Comparison between PI and PID for a Low qp/tp Ratio

  21. Comparison between PI and PID for a Higher qp/tp Ratio

  22. An Example of Too Much Derivative Action

  23. Effect of tD on Closed-Loop z

  24. Controller Tuning by Pole Placement • Based on model of the process • Select the closed-loop dynamic response and calculate the corresponding tuning parameters. • Application of pole placement shows that the closed-loop damping factor and time constant are not independent. • Therefore, the decay ratio is a reasonable tuning criterion.

  25. Controller Design by Pole Placement • A generalized controller (i.e., not PID) can be derived by using pole placement. • Generalized controllers are not generally used in industry because • Process models are not usually available • PID control is a standard function built into DCSs.

  26. Classical Tuning Methods • Examples: Cohen and Coon method, Ziegler-Nichols tuning, Cianione and Marlin tuning, and many others. • Usually based on having a model of the process (e.g., a FOPDT model) and in most cases in the time that it takes to develop the model, the controller could have been tuned several times over using other techniques. • Also, they are based on a preset tuning criterion (e.g., QAD)

  27. 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

  28. 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.

  29. 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.

  30. Controller Reliability • We know from industrial experience 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, tp, and qp which a linear analysis does not consider.

  31. Controller ReliabilityExample: CSTR with DCA0 Upsets

  32. 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.

  33. Tuning Criterion Selection

  34. Tuning Criterion Selection

  35. 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.

  36. Selecting the Tuning Criterion based on 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

  37. 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.

  38. 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.

  39. 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

  40. Field Tuning Approach • Decrease Kc by 10%. • Make initial estimate of tI (i.e., tI=5tp). • Reduce tI until offset is eliminated • Check that proper amount of Kc and tI are used.

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

  42. 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/FTtI=tIZN×FT

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

  44. Applying the ATV Results • Calculate Ku from ATV results. • ZN settings • TL settings

  45. 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.

  46. 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.

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

  48. ATV Test Applied to Composition Mixer

  49. CST Composition Mixer Example • Calculate Ku • Calculate ZN settings • Apply online tuning

  50. Online Tuning for CST Composition Mixer Example • FT=0.75 • FT=0.5

More Related