You can directly estimate the following types of continuous-time models:
You can also used2c
to convert an estimated discrete-time model into a continuous-time model.
You can estimate alllinearandnonlinearmodels supported by the System Identification Toolbox™ product as discrete-time models, except process models, which are defined only in continuous-time..
You can estimate both continuous-time and discrete-time models from time-domain data for linear and nonlinear differential and difference equations.
You can estimate discrete-time Hammerstein-Wiener and nonlinear ARX models from time-domain data.
You can also estimate nonlinear grey-box models from time-domain data. SeeEstimate Nonlinear Grey-Box Models.
There are two types of frequency-domain data:
Frequency response data
Fo频域输入/输出信号urier Transforms of the corresponding time domain signals.
The data is considered continuous-time if its sample time (Ts
) is0
, and is considered discrete-time if the sample time is nonzero.
You can estimate the following types of continuous-time models directly:
Transfer function modelsusing continuous- or discrete-time data.
Process modelsusing continuous- or discrete-time data.
Input-output polynomial modelsof output-error structure using continuous time data.
State-space modelsusing continuous- or discrete-time data.
From continuous-time frequency-domain data, you can only estimate continuous-time models.
You can also used2c
to convert an estimated discrete-time model into a continuous-time model.
You can estimate all linear model types supported by the System Identification Toolbox product as discrete-time models, except process models, which are defined in continuous-time only. For estimation of discrete-time models, you must use discrete-time data.
The noise component of a model cannot be estimated using frequency domain data, except for ARX models. Thus, theKmatrix of an identified state-space model, the noise component, is zero. An identified polynomial model has output-error (OE) or ARX structure; BJ/ARMAX or other polynomial structure with nontrivial values ofCorD无法估计多项式。
For linear grey-box models, you can estimate both continuous-time and discrete-time models from frequency-domain data. The noise component of the model, theKmatrix, cannot be estimated using frequency domain data; it remains fixed to0
.
Nonlinear grey-box models are supported only for time-domain data.
Nonlinear black box (nonlinear ARX and Hammerstein-Wiener models) cannot be estimated using frequency domain data.