slide1
Download
Skip this Video
Download Presentation
State Feedback

Loading in 2 Seconds...

play fullscreen
1 / 16

State Feedback - PowerPoint PPT Presentation


  • 116 Views
  • Uploaded on

State Feedback. State Feedback. State Feedback. Closed loop matrices. R=0 the system is called regulator. State Feedback. The CL state matrix is a function of K. => Faster/stable system. By appropriate changing K we can change eig( A CL ). This method is called pole placement.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'State Feedback' - aurelia-evans


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.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
slide3
State Feedback

Closed loop matrices

R=0 the system is called regulator.

slide4
State Feedback

The CL state matrix is a function of K

=> Faster/stable system

By appropriate changing K we can change eig(ACL)

This method is called pole placement.

WE MUST CHECK IF THE SYSTEM IS CONTROLLABLE

slide5
State Feedback

Eigenvalues of CL system:

3-k

CL eigenvalues at -10

k=13

slide6
State Feedback

If the system is unstable create a controller that will stabilise

the system.

>> eig(A)

>> rank(ctrb(A,B))

ans =

-0.3723

5.3723

ans =

2

slide7
State Feedback

-10 and -11

Matlab

If the system is n x n then you need to solve an n x n system of equations!

K=place(A,B, [-10 -11])

P=[-10 -20 -30];

C=[0 0 1],

D=0.

Matlab

slide8
State Feedback - LQR

Matlab:

State feedback

Response of the system

Reference signal

Study the signal u=-Kx

Place the poles at [-100 -110]

Response of the system

Study the signal u=-Kx

K =[26 72]T

P=[-10 -11]

slide9
State Feedback - LQR

Compromise between speed and energy that we use.

Similar problem/dilemma if we had an input.

Solution: Linear Quadratic Regulator (optimum controller)

Q and R are positive definite matrices

for all nonzero X

Square symmetric matrices, positive eigenvalues

Q: Importance of the error, R: Importance of the energy that we use

(assume that

is stable)

slide10
State Feedback - LQR

(assume that

is stable)

P is positive definite

X=1

Reduced Riccati Equation

slide11
State Feedback - LQR

Steps to design an LQR controller:

  • To find the optimum P solve:

2.Find the optimum gain

[K, P, E]=lqr(sys, Q, R)

E are the eigenvalues of A-BK

Find K,

The eigenvalues of A-BK

The response of the system

For R=1 and Q=eye(2) and Q=2*eye(2) (X(0)=[1 1]).

Matlab

CAD Exercise

slide13
Estimating techniques

Example: A=[1 2;3 4]; B=[1 0]'; C=[1 0]; D=0;

slide14
Estimating techniques

The error between the estimated and real state is

A is unstable

Homogeneous ODE

A is slow

A=[1 2;3 4]; B=[1 0]'; C=[1 0]; D=0; U=1,

slide16
Estimating techniques

G=place(A’, C’, P)

But the system must be observable

Where to place these eigenvalues???

A=[1 2;3 4]; B=[1 0]'; C=[1 0]; D=0; U=1,

ad