The FFT will work. It is only exact for periodic signals, but it's a
reasonable approximation for a whole lot of signals of infinite extent.
If you can arrange for a test input that's got the same value at
beginning and end (like a step-up followed by a step-down), and then
measure long enough so
Dear Tim,
Thank you for your reply.
First, you're not doing what I recommended you do. Why? <== As I informed you
that my inut u is not periodic. I thought that it is not practical to use fft
to my problem. Is my understanding not right? Is fft the recomeded method for
my problem?
In additio
First, you're not doing what I recommended you do. Yet you are
addressing me for help with your solution, when I've already suggested
two. Why?
Second, your prototype transfer function is 11th order, and you instruct
time_id to find the best fit to a second-order transfer function. You
are surp
Dear Tim,
Thank you for yor advise.
However, u is the step signal, such as 50% ==>60% ==> 50%.
u and y are sampled with constant interval, such as one second.
I made following Scilabe code, using time_id:
//
z=poly(0,'z');
h=(0.065/(z-0.934))*(1/z^10)//<== 10 Sampling period dead time
u=
Denis
[@@ THALES GROUP INTERNAL @@]
De : users [mailto: [hidden email] ] De la part de Fukashiimo
Envoyé : samedi 24 septembre 2016 2 3:11
À : [hidden email]
Objet : Re: [Scilab-users] System Identification for First order delay and dead
time
s is the Laplace operator, u is the pr
Heh. I just realized a better way to do this:
I assume that you've sampled u and y at a constant rate, and that you
have captured some reasonable amount of the response. This will be
perfect if u is periodic.
If u is periodic, then for some integer number of periods, take U =
fft(u) and Y = fft
Thank you for your suggestion. However, I am not sure how I should
formulate my Laplace domain equation. Could you please advise me more
specifically?
Thanks.
2016/09/25 午前9:33 "Tim Wescott [via Scilab / Xcos - Mailing Lists
Archives]" :
> I suggest that you roll your own cost function, and use
I suggest that you roll your own cost function, and use optim.
Where possible, with optim, if part of the problem is nonlinear and part
is linear, it's good to use a plain old linear least-squares fit for the
plain old linear part. In your case, that's K. Tau and Td will have to
be determine
Yes. I have data of y and u. s is the Laplaceoperator, no data is available.
for s.
"Samuel GOUGEON [via Scilab / Xcos - Mailing Lists Archives]"
:
>Le 25/09/2016 01:02, Fukashiimo a écrit :
>
>Thank you for your advice. y and u have some correration. X in your equation
>is the Laplace operat
Le 25/09/2016 01:02, Fukashiimo a écrit :
Thank you for your advice. y and u have some correration. X in your
equation is the Laplace operator, In this case, how I can use datafit?
.
AFAIK, there is no way in Scilab to perform a formal fit.
This is why i asked about known values of u, s or both.
Thank you for your advice. Is it possible to obtain Td also?
I am going to use it.
"Clément David-2 [via Scilab / Xcos - Mailing Lists Archives]"
:
>Hello,
>
>I suggest you to take a look at the `time_id` function [1]. AFAIK this will
>give you a first idea of the parameters. If you need more,
e la part de Fukashiimo
>Envoyé : samedi 24 septembre 2016 23:11
>À : [hidden email]
>Objet : Re: [Scilab-users] System Identification for First order delay and
>dead time
>
>
>
>s is the Laplace operator, u is the process input vatiable, y is the process
>output
...@lists.scilab.org] De la part de Fukashiimo
Envoyé : samedi 24 septembre 2016 23:11
À : users@lists.scilab.org
Objet : Re: [Scilab-users] System Identification for First order delay and dead
time
s is the Laplace operator, u is the process input vatiable, y is the process
output variable,
2016/09/24
s is the Laplace operator, u is the process input vatiable, y is the
process output variable,
2016/09/24 23:44 "Samuel GOUGEON [via Scilab / Xcos - Mailing Lists
Archives]" :
> Le 24/09/2016 15:59, Fukashiimo a écrit :
>
> > Hello,
> >
> > I am looking for a Scilab software which is similar to Ma
Hello,
I suggest you to take a look at the `time_id` function [1]. AFAIK this will give you a first idea of the parameters. If you need more, I suggest you to take a look at the "Optimization" topic in the help and implement a custom cost function.
@samuel : IMHO `s` is supposed to be the %s Scilab
Le 24/09/2016 15:59, Fukashiimo a écrit :
Hello,
I am looking for a Scilab software which is similar to Matlab System ID tool
box.
I would like to obtain values of parameters, Tau, K and Td for following
first order delay + Dead time model from time series data.
ymodel = (K/(Tau*s+1))*exp(-Td*s
Hello,
Le 24/09/2016 15:59, Fukashiimo a écrit :
Hello,
I am looking for a Scilab software which is similar to Matlab System ID tool
box.
I would like to obtain values of parameters, Tau, K and Td for following
first order delay + Dead time model from time series data.
ymodel = (K/(Tau*s+1))*e
Hello,
I am looking for a Scilab software which is similar to Matlab System ID tool
box.
I would like to obtain values of parameters, Tau, K and Td for following
first order delay + Dead time model from time series data.
ymodel = (K/(Tau*s+1))*exp(-Td*s)*u
ymodel: process output, u: process input
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