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This example shows how to access or edit parameter values and metadata in LTI objects.

The `tf`

, `zpk`

, `ss`

, and `frd`

commands create LTI objects that store model data in a single MATLAB® variable. This data includes model-specific parameters (e.g., A,B,C,D matrices for state-space models) as well as generic metadata such as input and output names. The data is arranged into a fixed set of data fields called **properties**.

You can access model data in the following ways:

The

`get`

commandStructure-like dot notation

Data retrieval commands

For illustration purposes, create the SISO transfer function (TF):

`G = tf([1 2],[1 3 10],'inputdelay',3)`

G = s + 2 exp(-3*s) * -------------- s^2 + 3 s + 10 Continuous-time transfer function.

To see all properties of the TF object `G`

, type

get(G)

Numerator: {[0 1 2]} Denominator: {[1 3 10]} Variable: 's' IODelay: 0 InputDelay: 3 OutputDelay: 0 Ts: 0 TimeUnit: 'seconds' InputName: {''} InputUnit: {''} InputGroup: [1x1 struct] OutputName: {''} OutputUnit: {''} OutputGroup: [1x1 struct] Notes: [0x1 string] UserData: [] Name: '' SamplingGrid: [1x1 struct]

The first four properties `Numerator`

, `Denominator`

, `IODelay`

, and `Variable`

are specific to the TF representation. The remaining properties are common to all LTI representations. You can use `help tf.Numerator`

to get more information on the `Numerator`

property and similarly for the other properties.

To retrieve the value of a particular property, use

`G.InputDelay % get input delay value`

ans = 3

You can use abbreviations for property names as long as they are unambiguous, for example:

`G.iod % get transport delay value`

ans = 0

`G.var % get variable`

ans = 's'

You can also retrieve all model parameters at once using `tfdata`

, `zpkdata`

, `ssdata`

, or `frdata`

. For example:

[Numerator,Denominator,Ts] = tfdata(G)

`Numerator = `*1x1 cell array*
{[0 1 2]}

`Denominator = `*1x1 cell array*
{[1 3 10]}

Ts = 0

Note that the numerator and denominator are returned as cell arrays. This is consistent with the MIMO case where `Numerator`

and `Denominator`

contain cell arrays of numerator and denominator polynomials (with one entry per I/O pair). For SISO transfer functions, you can return the numerator and denominator data as vectors by using a flag, for example:

`[Numerator,Denominator] = tfdata(G,'v')`

`Numerator = `*1×3*
0 1 2

`Denominator = `*1×3*
1 3 10

You can modify the data stored in LTI objects by editing the corresponding property values with `set`

or dot notation. For example, for the transfer function `G`

created above,

G.Ts = 1;

changes the sample time from 0 to 1, which redefines the model as discrete:

G

G = z + 2 z^(-3) * -------------- z^2 + 3 z + 10 Sample time: 1 seconds Discrete-time transfer function.

The `set`

command is equivalent to dot assignment, but also lets you set multiple properties at once:

```
G.Ts = 0.1;
G.Variable = 'q';
G
```

G = q + 2 q^(-3) * -------------- q^2 + 3 q + 10 Sample time: 0.1 seconds Discrete-time transfer function.

Using model editing together with LTI array support, you can easily investigate sensitivity to parameter variations. For example, consider the second-order transfer function

$$H(s)=\frac{s+5}{{s}^{2}+2\zeta s+5}$$

You can investigate the effect of the damping parameter `zeta`

on the frequency response by creating three models with different `zeta`

values and comparing their Bode responses:

s = tf('s'); % Create 3 transfer functions with Numerator = s+5 and Denominator = 1 H = repsys(s+5,[1 1 3]); % Specify denominators using 3 different zeta values zeta = [1 .5 .2]; for k = 1:3 H(:,:,k).Denominator = [1 2*zeta(k) 5]; % zeta(k) -> k-th model end % Plot Bode response bode(H) grid