# Idmodel

Simulate identified linear model in Simulink software

**Libraries:**

System Identification Toolbox /
Models

## Description

The Idmodel block simulates the output of an identified linear model
using time-domain input data. The model is a state-space (`idss`

),
linear grey-box (`idgrey`

), polynomial (`idpoly`

),
transfer function (`idtf`

), or process (`idproc`

)
model that you previously estimated or created. For the simulation of state-space and
linear grey-box models, you can specify the initial state values. For other linear
models, specify initial conditions using an `initialCondition`

object.
You can also add noise to the simulated output.

## Examples

### Simulate Identified Linear Model in Simulink with Initial Conditions

Set the initial states for simulating a linear model such that the simulation provides a best fit to measured input-output data.

## Ports

### Input

**Port_1(In1)** — Simulation input data

scalar | vector

Simulation input data, specified as a scalar for a single-input model.
The data must be time-domain data. For multi-input models, specify the
input as an *Nu*-element vector, where
*Nu* is the number of inputs. For example, you can
use a Vector Concatenate (Simulink) block
to concatenate scalar signals into a vector signal.

**Note**

Do not use a Bus Creator (Simulink) or Mux (Simulink) block to produce the vector signal.

**Data Types: **`double`

### Output

**Port_1(Out1)** — Simulated output

scalar | vector

Simulated output from linear model, returned as a scalar for a
single-output model and an *Ny*-element vector for a
model with *Ny* outputs.

**Data Types: **`double`

## Parameters

**Identified model** — Linear model to be simulated

`idss(-1,1,1,0,'Ts',1)`

(default) | `idss`

object | `idgrey`

object | `idpoly`

object | `idtf`

object | `idproc`

object

Linear model to be simulated, specified as one of these objects:

This object must be a MATLAB^{®} or model workspace variable for a previously estimated or
constructed linear model. The linear model can be continuous-time or
discrete-time, and with or without input/output delays.

**Initial conditions** — Initial conditions

`0`

(default) | numeric vector | `initialCondition`

object

Initial conditions of the linear model specified as a numeric vector or
`initialCondition`

object.

If the linear model specified by

**Identified model**is a state-space (`idss`

) or linear grey-box (`idgrey`

) model, specify**Initial conditions**as an*Nx*-element numeric vector of initial state values, where*Nx*is the number of states of the model.For all other linear models supported by the Idmodel block, specify

**Initial conditions**as an`initialCondition`

object. You can also use this object to specify the initial conditions for`idss`

and`idgrey`

models.

To generate the initial state values or `initialCondition`

object used to specify the initial conditions, see Estimate Initial Conditions for Simulating Linear Models.

To denote zero initial conditions, specify **Initial
conditions** as `0`

or
`[]`

.

To reproduce the simulation results that you get in the Model Output plot
window in the System Identification app, or from the `compare`

command, see Reproduce Command Line or System Identification App Simulation Results in Simulink.

**Add noise** — Add noise to simulated output

`on`

(default) | `off`

When you select this parameter, the block derives the noise amplitude from
the linear model property `model.NoiseVariance`

. The
software filters random Gaussian white noise with the noise transfer
function of the model and adds the resulting noise to the simulated model
response. If you want to add the same noise every time you run the
Simulink^{®} model, specify the **Noise seed(s)**
parameter.

If you add noise to the simulated output, then to generate the noise at the correct time steps, you must either:

Set the sample time of the linear model specified by the

**Identified model**parameter.Specify the

**Initial conditions**parameter as a`initialCondition`

object. This object contains model sample time information.

For continuous-time models, the ideal variance of the noise term is infinite. In reality, you see a band-limited noise that accounts for the time constants of the system. You can interpret the resulting simulated output as a response that is filtered using a lowpass filter with a passband that does not distort the dynamics from the input.

**Noise seed(s)** — Add same noise to output for multiple simulations

`[]`

(default) | nonnegative integer | vector

The **Noise seed(s)** property seeds the random number
generator such that the block adds the same noise to the simulated output
every time you run the Simulink model. For information about using seeds, see `rng`

.

For multi-output models, you can use independent noise realizations that
generate the outputs with additive noise. Enter a vector of
*Ny* nonnegative integer entries, where
*Ny* is the number of output channels.

For random restarts that vary from one simulation to another, specify
**Noise seed(s)** as `[]`

.

#### Dependency

To enable this parameter, select ```
Add
noise
```

.

## Extended Capabilities

### C/C++ Code Generation

Generate C and C++ code using Simulink® Coder™.

## Version History

**Introduced in R2008a**

## See Also

### Functions

### Blocks

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