This document summarizes an interactive seminar on PID tuning for self-regulating processes. The seminar covered topics like identifying process models for different operating regions, using adaptive and on-demand PID tuning, nonlinear control valve characteristics, and demonstrating adaptive control on liquid flow and pressure loops. It provided details on the presenter and instructions for attending a follow-up seminar on tuning near-integrating processes.

1. Interactive Opportunity Assessment Demo and Seminar (Deminar) Series for Web Labs – PID Tuning for Self-Regulating Processes June 9, 2010 Sponsored by Emerson, Experitec, and Mynah Created by Greg McMillan and Jack Ahlers www.processcontrollab.com Website - Charlie Schliesser (csdesignco.com)

5. Time (seconds) % Controlled Variable (CV) or % Controller Output (CO)  CO  CV  o  p K p =  CV  CO  CV CO CV self-regulating process time constant Self-regulating process gain (%/%) Response to change in controller output with controller in manual observed process deadtime Self-Regulating Process Response

6. Conical Tank in MIT Anna University Lab http://www.controlglobal.com/articles/2010/LevelControl1002.html

7. Gravity discharge flow makes the level response self-regulating (increase in level head increases flow through discharge valve) Increase in cross sectional area with level increases process time constant making process response slower Conical Tank Detail

8. Performance of Linear PID Level Controller for Conical Tank

9. Process Models Automatically Identified for Operating Regions

10. Performance of Adaptive PID Level Controller for Conical Tank

11. Click on magnifying glass to get detail view of limits and tuning Click on Duncan to get DeltaV Insight for “On-Demand” and “Adaptive” tuning Slide

12. Control Valve Flow Characteristics

13. Equal Percentage Flow Characteristic Slide

14. “ On-Demand Tuning” automatically identifies dynamics from relay oscillation introduced click on PID tag and then Tune Slide

15. “ Adaptive Tuning” automatically identifies dynamics from setpoint or manual output change or injected pulse (For More Info See Emerson Exchange 2009 Presentation on DeltaV Insight for Loop Monitoring and Tuning) click on PID tag and then Tune Slide

16. “ Adaptive Control” automatically identifies dynamics in each region Process gain is approximately proportional to flow for equal percentage flow characteristic Slide

17. Identification Out Limit that sets deadzone should be set approximately equal to valve deadband and stick-slip near closed position Learning Setup (triggers, injection, search, process, initialization, and options for model identification ) Slide

18. Simulate to show gain and phase margin and load and setpoint response for tuning settings Slide

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22. QUESTIONS?