User`s guide

5 ODE P ara meter Estimation (Grey-Box Modeling)
Estimating Nonlinear Grey-Box Models
In this section...
“Supported Nonlinear Grey-Box Models” on page 5-16
“Nonlinear Grey-B ox D emo s and Ex amples” on page 5-16
“Specifying the Nonlinear Grey-Box Model Structure” on page 5-17
“Constructing the idnlgrey Object” on page 5-18
“Using pem to Estim ate Nonlinear Grey-B ox Mode ls” on page 5-19
“Options for the Estimation Algorithm” on page 5-20
Supported Nonlinear Grey-Box Models
You can estimate nonlinear discrete-time and continuous-time grey-box
models for arb itrary nonlinear ordinary differential equations usin g
single-output and multiple-output time -domain da ta, or output- only
time-series data. Your gr ey-box models can be static or dynamic.
Grey-box models describe the system behav ior as a set of nonlinear ordinary
differential or difference equations (ODEs) with unknown parameters.
Nonlinear Grey-Box D emos and Examples
The System Identification Toolbox p roduct provides s eve ral de mos and case
studies on creating, manipulating, and estimating nonlinear grey-box models.
You can access these demos by typing the following command at the prompt:
iddemo
For examples of M-files an d MEX-files that specify model structure, see the
toolbox/ident/iddemos/examples directory. For example, the model of a
DC motor—used in the demo
idnlgreydemo1—is described in files dcmotor_m
and dcmotor_c.
5-16