User`s guide

3 Linear Model Identification
Transforming Between Discrete-Time and Continuous-Time
Representations
In this section...
“Why Transform Between Continuous and Discrete Time?” on page 3-112
“Using the c2d, d2c, and d2d Commands” on page 3-112
“Specifying Intersample Behavior” on page 3-114
“How d2c Handles Input Delays” on page 3-114
“Effects on the Noise Model” on page 3-115
Why Transform Between Continuous and Discrete
Time?
Transforming between continuous-time and discrete-time representations is
useful, for example, if you have estimated a discrete-time linear model and
require a continuous-time model instead.
d2d is useful is you want to change the sampling interval of a discrete
model. All of these operations change the sampling interval, which is called
resampling the model.
Using the c2d, d2c, and d2d Commands
You can use c2d and d2c to transform any i dmodel object between
continuous-time and discrete-time representations.
Thefollowingtablesummarizesthecommands for transforming between
continuous-time and discrete-time model representatio n s. These commands
also transform the estimated model uncertainty, which corresponds to the
estimated covariance matrix of the parameters. For detaile d inf ormation
about these commands, see the corresponding reference page.
3-112