System Identification Toolbox™

Simulating Model Output

When to Use Simulation Blocks

Add model simulation blocks to your Simulink^® model from the System Identification Toolbox™ block library when you want to:

• Represent the dynamics of a physical component in a Simulink model using a data-based nonlinear model.

• Replace a complex Simulink subsystem with a simpler data-based nonlinear model.

You use the model simulation blocks to import the models you identified using System Identification Toolbox software from the MATLAB^® workspace into the Simulink environment. For a list of System Identification Toolbox simulation blocks, see Summary of Simulation Blocks.

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Summary of Simulation Blocks

The following table summarizes the blocks you use to import models from the MATLAB environment into a Simulink model for simulation. Importing a model corresponds to entering the model variable name in the block parameter dialog box.

After importing the model into Simulink, use the block parameter dialog box to specify the initial conditions for simulating that block, as described in Specifying Initial Conditions for Simulation. For information about configuring each block, see the corresponding reference pages.

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Specifying Initial Conditions for Simulation

For accurate simulation of a linear or a nonlinear model, you can use default initial conditions or specify the initial conditions for simulation using the block parameters dialog box.

Tip   Double-click the block after adding it your Simulink model to open the block parameters dialog box.

Specifying Initial States of Linear Models

For linear models, the default initial states are the states computed during model estimation and stored by the InitialStates model property. For idarx and idpoly models, the default initial states are 0. For idproc, idss, and idgrey models, the InitialStates model property can be nonzero values after model estimation.

Because idss and idgrey models are state-space models, the definition of initial states corresponds to the standard definition of states for state-space representation. For idproc, idpoly, and idarx models, the states are the states of the corresponding state-space model. For example, suppose you have the following idpoly model:

m1=idpoly([1 2 1],[2 2]);

The initial states of the previous model correspond to those of the equivalent state-space model:

m2=idss(m1);

For more information about specifying initial conditions for simulation, see the IDMODEL Model reference page.

Specifying Initial States of Nonlinear ARX Models

The states of a nonlinear ARX model correspond to the dynamic elements of the nonlinear ARX model structure, which are the model regressors. Regressors can be the delayed input/output variables (standard regressors) or user-defined transformations of delayed input/output variables (custom regressors). For more information about the states of a nonlinear ARX model, see the idnlarx reference page.

For more information about specifying initial conditions for simulation, see the IDNLARX Model reference page.

Specifying Initial States of Hammerstein-Wiener Models

The states of a Hammerstein-Wiener model correspond to the states of the embedded linear (idpoly) model. For more information about the states of a Hammerstein-Wiener model, see the idnlhw reference page.

The default initial state for simulating a Hammerstein-Wiener model is 0. This setting might lead to unexpected transients in the simulated response.

For more information about specifying initial conditions for simulation, see the IDNLHW Model reference page.

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Identifying Linear Models

Example – Simulating a Model Using Simulink® Software