Controller Design, Tuning

1. Controller Design, Tuning

6. Performance Criteria for Closed-loop systems • Must be stable. • Provide good disturbance rejection---minimizing the effects of disturbance. • Have good set-point tracking---Rapid, smooth responses to set-point changes • Eliminate steady state error (zero offset) • Avoid excessive control action. • Must be robust( or insensitive) to process changes or model inaccuracies.

10. Methods for PID controller settings Classical methods: • By reaction curve for a quarter decay ratio. • By on-line cycling experiment for quarter decay ratio. • By tuning rules using reaction curve and integral performance criteria.

12. Reaction Curve Reaction curve L Manual input y + + + - R

14. Classical methods

15. Classical methods

16. Classical methods

17. Classical methods

18. Relay Feedback

19. Original Z-N settings for PID control Modified Z-N settings for PID control

20. Tyler-Luyben’s Tuning Rule

21. Tyler-Luyben vs Z-N Tuning

25. Model characterization by reaction curve • FOPDT (First Order Plus Dead Time) model • Fit 1

26. Model characterization by reaction curve • FOPDT (First Order Plus Dead Time) model • Fit 2

27. Model characterization by reaction curve • FOPDT (First Order Plus Dead Time) model • Fit 3

28. Model-based tuning rules for QDR

29. Controller P PI PID

30. Original Z-N Tuning (1942) Tyreus-Luyben’s Tuning (1997)

31. Tyreus-Luyben vs Z-N Tuning

33. Hagglund & Astrom’s PI Tuning Rules

34. Integral performance indices • ISE : • IAE: • ITSE: • ITAE:

35. Tuning rules for optimal integral performance measures • Optimal tuning parameters are obtained via simulating a basic loop: • The results apply specifically to set-point change or to disturbance change. GL=GP

36. Tuning rules for optimal integral performance measures • The controller used is considered as of parallel and ideal form; • Parameters are Dimensionless groups, such as : KcKp, tR/t, tD/t;

37. Tuning rules for optimal integral performance measures • The resulted tuning parameters are fitted into the following forms: • The values of a and b are tabularized.

38. Model based tuning rules for optimal integral performance measures ---II • Optimal tuning parameters are obtained via simulating a basic loop: • The results apply specifically to set-point change or to disturbance change. GL=GP

39. Model based tuning rules for optimal integral performance measures ---III • The resulted tuning parameters are fitted into the following forms: • The values of a and b are tabularized.

45. Remarks on tuning rules with integral performance indices: • Remember that conversions between a series PID controller and the parallel PID controller is necessary in order to use the tuning rules. • The tuning parameters for disturbance change will be too aggressive when controlling a set-point change. The reverse happens in using set-point tuning parameters to disturbance regulation. • No significance in difference among rules of different integral criteria.

46. Late methods • Method of Synthesis • Using IMC tuning (internal model control ) or other model based rules • Using ATV test to characterize the process dynamics.

47. Direct synthesis method • Specify desired closed-loop transfer function. • Derive PID controller follows. • Tuning parameters are directly synthesized. • Exactly PID controller form applies to FOPDT or SOPDT processes.

49. r y + Gc(s) Gp(s) - y r Go(s) Specified to meet requirement r y H(s)