|
|
Hey all,
I got the following problem....i identified a process with the system
identification toolbox with the state space model..so i got Matrixes
for A,B,C,D and x(0).
After I converted it into a transfer function but i always get a
minus in the denumerator what means a singularity!
The model output in matlab is the following:
The free model parameterization means that the matrix elements
have no well defined variance. To display the standard deviations
of the matrix elements, first convert to canonical form by
Model.ss = 'can'.
State-space model: x(t+Ts) = A x(t) + B u(t) + K e(t)
y(t) = C x(t) + D u(t) + e(t)
A =
x1
x1 0.79489
B =
u1
x1 0.040598
C =
x1
y1 3.8457
D =
u1
y1 0
K =
y1
x1 0
x(0) =
x1 -1.063
Estimated using N4SID from data set L3A5SPPV1708d
Loss function 0.13405 and FPE 0.138543
Sampling interval: 1
Created: 30-Sep-2005 14:14:13
Last modified: 30-Sep-2005 14:14:15
>> [num, den]=tfdata(n4s1)
num =
[1x2 double]
den =
[1x2 double]
>> data=tf(num, den)
Transfer function:
0.1912
----------
s - 0.8088 <------
when I convert the -0.8088 into a +0.8088 than i get the right
solution in the simulation.... but what do I make wrong?? Why do i
get the minus?
Thanks a lot
Marcus
|
|