convert ARMAX to discrete or continiuous transfer function

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mohsen
mohsen 2013 年 10 月 6 日
回答済み: vidya kurada 2016 年 7 月 3 日
hi here is what i have found as armax estimation
>> amx2221
amx2221 =
Discrete-time ARMAX model: A(z)y(t) = B(z)u(t) + C(z)e(t)
A(z) = 1 - 1.12 z^-1 + 0.1199 z^-2
B(z) = 0.0004663 z^-1 - 0.0004681 z^-2
C(z) = 1 - 1.154 z^-1 + 0.1929 z^-2
Name: amx2221
Sample time: 1.5e-05 seconds
Parameterization:
Polynomial orders: na=2 nb=2 nc=2 nk=1
Number of free coefficients: 6
Use "polydata", "getpvec", "getcov" for parameters and their uncertainties.
Status:
Estimated using POLYEST on time domain data "p50".
Fit to estimation data: 98.35% (prediction focus)
FPE: 8.796e-12, MSE: 8.791e-12
while i use tf(amx2221) it answers me:
>> tf(amx2221)
ans =
From input "u1" to output "y1":
0.0004663 z^-1 - 0.0004681 z^-2
-------------------------------
1 - 1.12 z^-1 + 0.1199 z^-2
Name: amx2221
Sample time: 1.5e-05 seconds
Discrete-time transfer function.
or in the other shape:
>> d2c(tf(amx2221))
ans =
From input "u1" to output "y1":
75.11 s - 1.904e04
-----------------------
s^2 + 1.414e05 s - 9996
Continuous-time transfer function.
and this is exactly B(z)/A(z) and there is no effect of C(z);
How can i get a transfer function that have the effect of C(z)?

回答 (1 件)

vidya kurada
vidya kurada 2016 年 7 月 3 日
tf(amx2221,'noise') should give the noise model

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