Main Content

Select

**Estimate**>**State Space Models**.The State Space Models dialog box opens.

**Tip**For more information on the options in the dialog box, click

**Help**.Specify a model name by clicking adjacent to

**Model name**. The name of the model must be unique in the Model Board.Select the

**Specify value**option (if not already selected) and specify the model order in the edit field. Model order refers to the number of states in the state-space model.**Tip**When you do not know the model order, search for and select an order. For more information, see Estimate Model With Selected Order in the App.

Select the

**Continuous-time**or**Discrete-time**option to specify the type of model to estimate.You cannot estimate a discrete-time model if the working data is continuous-time frequency-domain data.

Expand the

**Model Structure Configuration**section to select the model structure, such as canonical form, whether to estimate the disturbance component (*K*matrix) and specification of feedthrough and input delays.For more information about the type of state-space parameterization, see Supported State-Space Parameterizations.

Expand the

**Estimation Options**section to select the estimation method and configure the cost function.Select one of the following

**Estimation Method**from the drop-down list and configure the options. For more information about these methods, see State-Space Model Estimation Methods.Click

**Estimate**to estimate the model. A new model gets added to the System Identification app.

You can specify how the estimation algorithm weights the fit at various frequencies. In the
app, set **Focus** to one of the following options:

`Prediction`

— Uses the inverse of the noise model*H*to weigh the relative importance of how closely to fit the data in various frequency ranges. Corresponds to minimizing one-step-ahead prediction, which typically favors the fit over a short time interval. Optimized for output prediction applications.`Simulation`

— Uses the input spectrum to weigh the relative importance of the fit in a specific frequency range. Does not use the noise model to weigh the relative importance of how closely to fit the data in various frequency ranges. Optimized for output simulation applications.`Stability`

— Estimates the best stable model. For more information about model stability, see Unstable Models.`Filter`

— Specify a custom filter to open the Estimation Focus dialog box, where you can enter a filter, as described in Simple Passband Filter or Defining a Custom Filter. This prefiltering applies only for estimating the dynamics from input to output. The disturbance model is determined from the estimation data.