User`s guide

Estimating Linear Grey- Box Models
2 Use the following syntax to define an idgrey model o bject based on the
myfunc M-file:
m = idgrey('myfunc',par,'c',T,aux)
where par represents user-defined parameters and contains their n ominal
(initial) values.
'c' specifies that the underlying parameterization is in
continuous time.
aux contains the values of the auxiliary param eters.
Note You must specify T and aux even if they are not used by the myfunc
code.
Use pem to estimate the grey-box parameter values:
m = pem(data,m)
where data is the estimation data and m is the idgrey object with unknown
parameters.
Note Compare this example to “Example – Estimating Structured
Continuous-Time State-Space Models” on page 3-97, where the same problem
is solved using a structured state-s pace representation.
Example – Estimating a Continuous-Time Grey-Box
Model for Heat Diffusion
In this example, you estimate the heat conductivity and the heat-transfer
coefficient of a continuous-time grey-bo x model for a heated-rod system.
This system consists of a well-insulated metal rod of length L and a
heat-diffusion coefficient
κ
. T he input to the system is the heating power u(t)
and the measured output y(t) is the tem perature at the o ther end.
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