Simulink Control Design™ - MathWorks

More Efficient Batch Linearization Varying Parameters

This example shows how to speed up the batch linearization of a model when a set of

model parameters are varied.

The decrease the linearization time, you pass the varying parameter values to the

linearize function. linearize avoids recompiling the model when the varied

parameters are tunable parameters. The best improvements in the overall linearization

time are for models with large model update times. To run this example, you need

Aerospace Blockset™ software.

Plant Model

In this example, you linearize a lightweight airplane model. For more information on this

model, see “Lightweight Airplane Design” (Aerospace Blockset).

Open the model.

mdl = 'scdskyhogg';

open_system(mdl)

io = getlinio(mdl);

op = operpoint(mdl);

Linearize Model By Calling linearize Multiple Times

For this example, you vary the gains of the altitude and pitch controllers by +/- 10%.

Initialize the gains of the controllers to vary with MATLAB® workspace variables k1 and

k2.

open_system('scdskyhogg/Vehicle System Model/Avionics/Autopilot')

blks = {'scdskyhogg/Vehicle System Model/Avionics/Autopilot/Alt Controller';...

3 Batch Linearization