## Simulink Control Design |

This example shows how to linearize a Simulink model with delays in it.

**Linearization of Models with Continuous Delays**

You can linearize a Simulink model with continuous time delays blocks such as the Transport Delay, Variable Transport Delay, and Variable Time Delay using one of the following options:

Use a Pade approximations of the delays to get a rational linear system through linearizations.

Compute a linearization where the delay is exactly represented. Use this option when you need accurate simulation and frequency responses from a linearized model and when assessing the accuracy of Pade approximation.

By default, Simulink Control Design uses Pade approximations of the delay blocks in a Simulink model.

To open the engine speed model used in this example, type

```
model = 'scdspeed';
open_system(model);
```

The engine speed model contains a Variable Transport Delay block named dM/dt in the subsystem Induction to Power Stroke Delay. For convenience you can store the path to the block in a MATLAB variable by typing

```
DelayBlock = 'scdspeed/Induction to Power Stroke Delay/dM//dt delay';
```

To compute a linearization using a first order approximation, use one of the following techniques to set the order of the Pade approximation to 1:

In the Variable Transport Delay block dialog box, enter 1 in the

**Pade Order (for linearization)**field.At the command line, enter the following command:

set_param(DelayBlock,'PadeOrder','1');

Next, specify the linearization I/O to throttle angle as the input and engine speed as the output by running:

io(1) = linio('scdspeed/throttle (degrees)',1,'input'); io(2) = linio('scdspeed/rad//s to rpm',1,'output');

Compute the linearization using the following linearize command:

sys_1st_order_approx = linearize(model,io);

You can compute a linearization using a second order approximation by setting the Pade order to 2:

set_param(DelayBlock,'PadeOrder','2'); sys_2nd_order_approx = linearize(model,io);

To compute a linear model with the exact delay representation, set the 'UseExactDelayModel' property in the linoptions object to on:

```
opt = linearizeOptions;
opt.UseExactDelayModel = 'on';
```

Linearize the model using the following linearize command:

sys_exact = linearize(model,io,opt);

Compare the Bode response of the Pade approximation model and the exact linearization model by running:

p = bodeoptions('cstprefs'); p.Grid = 'on'; p.PhaseMatching = 'on'; p.XLimMode = {'Manual'}; p.XLim = {[0.1 1000]}; f = figure; bode(sys_1st_order_approx,sys_2nd_order_approx,sys_exact,p); h = legend('sys_1st_order_approx','sys_2nd_order_approx','sys_exact',... 'Location','SouthWest'); h.Interpreter = 'none';

In the case of a first order approximation, the phase begins to diverge around 50 rad/s and diverges around 100 rad/s.

Close the Simulink model.

bdclose(model)

**Linearization of Models with Discrete Delays**

When linearizing a model with discrete delay blocks, such as (Integer) Delay and Unit Delay blocks use the exact delay option to account for the delays without adding states to the model dynamics. Explicitly accounting for these delays improves your simulation performance for systems with many discrete delays because your fewer states in your model.

To open the Simulink model of a discrete system with a Delay block with 20 delay state used for this example, run the following.

```
model = 'scdintegerdelay';
open_system(model);
```

By default the linearization includes all of the states folded into the linear model. Set the linearization I/Os and linearize the model as follows:

io(1) = linio('scdintegerdelay/Step',1,'input'); io(2) = linio('scdintegerdelay/Discrete Filter',1,'output'); sys_default = linearize(model,io);

Integrate the resulting model to see that it has 21 states (1 - Discrete Filter, 20 - Integer Delay).

size(sys_default)

State-space model with 1 outputs, 1 inputs, and 21 states.

You can linearize this same model using the 'UseExactDelayModel' property as follows:

```
opt = linearizeOptions;
opt.UseExactDelayModel = 'on';
sys_exact = linearize(model,io,opt);
```

Interrogating the new resulting model shows that it has 1 state and the delays are accounted for internally in the linearized model.

size(sys_exact)

State-space model with 1 outputs, 1 inputs, and 1 states.

Run a step response simulation of both linearized model to see that they are identical by running the following commands.

step(sys_default,sys_exact); h = legend('sys_default','sys_exact',... 'Location','SouthEast'); h.Interpreter = 'none';

Close the Simulink model and clean up figures.

bdclose(model) close(f)

**Working with Linearized Models with Delays**

For more information on manipulating linearized models with delays, see the Control System Toolbox documentation along with the examples "Specifying Time Delays" and "Analyzing Control Systems with Delays" .