1 / 62

Multivariable Control

Multivariable Control. Root Locus . By Kirsten Mølgaard Nielsen. Outline. Root Locus Design Method Root locus definition The phase condition Test points, and sketching a root locus Dynamic Compensation Lead compensation Lag compensation. Introduction.

drago
Download Presentation

Multivariable Control

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. Multivariable Control Root Locus By Kirsten Mølgaard Nielsen

  2. Outline • Root Locus Design Method • Root locus • definition • The phase condition • Test points, and sketching a root locus • Dynamic Compensation • Lead compensation • Lag compensation

  3. Introduction Closed loop transfer function Characteristic equation, roots are poles in T(s)

  4. Introduction • Dynamic features depend on the pole locations. • For example, time constant t, rise time tr, and overshoot Mp (1st order) (2nd order)

  5. Introduction Root locus • Determination of the closed loop pole locations under varying K. • For example, K could be the control gain. The characteristic equation can be written in various ways

  6. Introduction • Root locus of a motor position control (example)

  7. Introduction break-away point

  8. Introduction Some root loci examples (K from zero to infinity)

  9. Sketching a Root Locus • Definition 1 • The root locus is the values of s for which 1+KL(s)=0 is satisfied as K varies from 0 to infinity (pos.). • Definition 2 • The root locus is the points in the s-plane where the phase of L(s) is 180°. • The angle to a point on the root locus from zero number i is yi. • The angle to a point on the root locus from pole number i is fi. • Therefore,

  10. Sketching a Root Locus s0 f1 p y1 f2 p* A root locus can be plotted using Matlab: rlocus(sysL)

  11. Root Locus characteristics • Rule 1 (of 6) • The n branches of the locus start at the poles L(s) and m of these branches end on the zeros of L(s).

  12. Root Locus characteristics • Rule 2 (of 6) • The loci on the real axis (real-axis part) are to the left of an odd number of poles plus zeros. • Notice, if we take a test point s0 on the real axis : • The angle of complex poles cancel each other. • Angles from real poles or zeros are 0° if s0 are to the right. • Angles from real poles or zeros are 180° if s0 are to the left. • Total angle = 180° + 360° l

  13. Root Locus characteristics • Rule 3 (of 6) • For large s and K, n-m branches of the loci are asymptotic to lines at angles fl radiating out from a point s = a on the real axis. fl a For example

  14. Root Locus characteristics n-m=1 n-m=2 n-m=3 n-m=4 For ex., n-m=3

  15. Root Locus 3 poles: q = 3 • Rule 4: The angles of departure (arrival) of a branch of the locus from a pole (zero) of multiplicity q. f1,dep = 60 deg. f2,dep = 180 deg. f3,dep = 300 deg.

  16. Root Locus characteristics • Rule 5 (of 6) • The locus crosses the jw axis at points where the Routh criterion shows a transition from roots in the left half-plane to roots in the right half-plane. • Routh: A system is stable if and only if all the elements in the first column of the Routh array are positive.

  17. Root Locus characteristics • Rule 6 (of 6) • The locus will have multiplicative roots of q at points on the locus where (1) applies. • The branches will approach a point of q roots at angles separated by (2) and will depart at angles with the same separation. Characteristic equation

  18. Example Root locus for double integrator with P-control Rule 1: The locus has two branches that starts in s=0. There are no zeros. Thus, the branches do not end at zeros. Rule 3: Two branches have asymptotes for s going to infinity. We get

  19. Rule 2: No branches that the real axis. Rule 4: Same argument and conclusion as rule 3. Rule 5: The loci remain on the imaginary axis. Thus, no crossings of the jw-axis. Rule 6: Easy to see, no further multiple poles. Verification:

  20. Example Root locus for satellite attitude control with PD-control

  21. Selecting the Parameter Value • The (positive) root locus • A plot of all possible locations of roots to the equation 1+KL(s)=0 for some real positive value of K. • The purpose of design is to select a particular value of K that will meet the specifications for static and dynamic characteristics. • For a given root locus we have (1). Thus, for some desired pole locations it is possible to find K.

  22. Selecting the Parameter Value Example Selection of K using Matlab: [K,p]=rlocfind(sysL)

  23. Dynamic Compensation • Some facts • We are able to determine the roots of the characteristic equation (closed loop poles) for a varying parameter K. • The location of the roots determine the dynamic characteristics (performance) of the closed loop system. • It might not be possible to achieve the desired performance with D(s) = K. • Controller design using root locus • Lead compensation (similar to PD control) • overshoot, rise time requirements • Lag compensation (similar to PI control) • steady state requirements

  24. Dynamic Compensation PD Lead PI Lag

  25. Lead Compensation PD P Lower damping ratio with PD !

  26. Lead Compensation • PD control • Pure differentiation • Output noise has a great effect on u(t) • Solution: Insert a pole at a higher frequency r(t) e(t) controller D(s) u(t) plant G(s) y(t) + - + + noise

  27. Lead Compensation

  28. Lead Compensation • Selecting p and z • Usually, trial and error • The placement of the zero is determined by dynamic requirements (rise time, overshoot). • The exact placement of the pole is determined by conflicting interests. • suppression of output noise • effectiveness of the zero • In general, • the zero z is placed around desired closed loop wn • the pole p is placed between 5 and 20 times of z

  29. Lead Compensation • Design approach (A) • Initial design z=wn, p=5z • Noise: additional requirement, max(p)=20 • Iterations • First design: z=wn, p=5z (neglecting the add. req.) • Second design: z=wn, p=20 • Third design: new z, p=20

  30. Lead Compensation Possible pole location Matlab – design 1 sysG = tf([1],[1 1 0]) sysD = tf([1 7],[1 5*7]) rlocus(sysD*sysG)

  31. Lead Compensation No possible pole location ! Matlab – design 2 sysG = tf([1],[1 1 0]) sysD = tf([1 7],[1 20]) rlocus(sysD*sysG)

  32. Lead Compensation Possible location New zero location Matlab – design 3 sysG = tf([1],[1 1 0]) sysD = tf([1 4],[1 20]) rlocus(sysD*sysG)

  33. Lead Compensation • Design approach (B) • Pole placement from the requirements • Noise: Additional requirement, max(p)=20. So, p=20 to minimize the effect of the pole.

  34. Lead Compensation

  35. Lead Compensation Pole location Matlab – design B sysG = tf([1],[1 1 0]) sysD = tf([1 5.4],[1 20]) rlocus(sysD*sysG)

  36. Lead Compensation • Exercise • Design a lead compensation D(s) to the plant G(s) so that the dominant poles are located at s = -2 ± 2j You can use, triangle a/sin(A) = b/sin(B) r(t) e(t) controller D(s) u(t) plant G(s) y(t) + -

  37. Lead Compensation • Answer • we have three poles and one zero f1 y f2 Notice, triangle a/sin(A) = b/sin(B)

  38. Dynamic Compensation PD Lead PI Lag

  39. Lag Compensation • Lag compensation • Steady state characteristics (requirements) • Position error constant Kp • Velocity error constant Kv • Let us continue using the example system • and the designed controller (lead compensation)

  40. Lag Compensation • Calculation of error constants • Suppose we want Kv≥ 100 • We need additional gain at low frequencies !

  41. Lag Compensation • Selecting p and z • To minimize the effect on the dominant dynamics z and p must chosen as low as possible (i.e. at low frequencies) • To minimize the settling time z and p must chosen as high as possible (i.e. at high frequencies) • Thus, the lag pole-zero location must be chosen at as high a frequency as possible without causing any major shifts in the dominant pole locations

  42. Lag Compensation • Design approach • Increase the error constant by increasing the low frequency gain • Choose z and p somewhat below wn • Example system: • K = 1 (the proportional part has already been chosen) • z/p = 3, with z = 0.03, and p = 0.01.

  43. Lag Compensation Notice, a slightly different pole location Lead-lag Controller

  44. Lag Compensation z p

  45. Lag Compensation Step

  46. Lag Compensation Ramp

  47. Notch compensation • Example system • We have successfully designed a lead-lag controller • Suppose the real system has a rather undampen oscillation about 50 rad/sec. • Include this oscillation in the model • Can we use the original controller ?

  48. Notch compensation Step response using the lead-lag controller

More Related