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From: AsimV <asimvod@gmail.com>
Newsgroups: comp.soft-sys.matlab
Subject: Re: Linear parametric identification
Date: Thu, 26 Feb 2009 13:11:06 -0800 (PST)
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On Feb 24, 6:16 pm, AsimV <asim...@gmail.com> wrote:
> On Feb 23, 3:47 pm, "Rajiv Singh" <rajiv_si...@msn.com> wrote:
>
>
>
> > Your model has one "measured" input and one output. However, there is also a
> > noise input which you could think of an unmeasured input. When you perform
> > an estimation, you not only estimate a "measured" model G, but also a
> > "noise" model H, according to equation:
>
> > y = Gu+He
>
> > H is the transfer function between the unmeasured (noise) input e and the
> > output y. H explains the component of the output that could not be captured
> > by G.  H is also called a disturbance model. The inputs are "u" (measured)
> > and "e" (unmeasured).
>
> > When you do TF(arx221), this operation converts the noise input channel (e)
> > into a regular input. Hence the number of inputs in the resulting model
> > becomes 2. If you just need "G", the transfer function between measured
> > input and output, you should do:
>
> > g2 = tf(arx221('m'))
>
> > This operation separates out the measured component (G) and converts only
> > that component into a TF object.
>
> > HTH,
> > Rajiv
>
> > "AsimV" <asim...@gmail.com> wrote in message
>
> >news:dcb69d15-194c-40d1-acb9-49000bd8f1c8@l16g2000yqo.googlegroups.com...
>
> > > Hello to all,
>
> > > I'm experimenting with linear parametric identification methods. I
> > > have tested this methods when output data contains noise. I simulated
> > > noise by random number generator.
> > > Can you please explain to me what does it mean when one gets the
> > > following result:
> > > g2 = tf(arx221)
>
> > > Transfer function from input "u1" to output "y1":
> > >   -0.4777 z + 0.4677
> > > ------------------------
> > > z^2 - 0.9353 z - 0.01695
>
> > > Transfer function from input "v@y1" to output "y1":
> > >      0.01454 z^2
> > > ------------------------
> > > z^2 - 0.9353 z - 0.01695
>
> > > Data object for identification is formed from one input and one output
> > > vector. It is SISO system. How to inperpret input "v@y1" to output
> > > "y1"? What does it mean?
>
> > > Thank you
>
> Thank you Rajiv, you're most helpful.


Rajiv, I also need help abput simulating noise channel.
For example, I have created a model with process data, and I have also
"v@y1" part (transfer function) in my model.
I'd like to simulate and test the model in the Simulink. It's fairly
easy to set up transfer functions blocks with inputs and outputs, but
how to simulate that noise part, because I don't know anything about
nature of the process noise that is present in the data.
Should I use random generator for such such purpose?

Thanks