Monte Carlo Analysis

Sample uncertain systems for statistical analysis

You can perform Monte Carlo Analysis by analyzing the behavior of random samples taken from an uncertain system. For instance, use usample to obtain an array of numeric models from an uncertain model by sampling the uncertain control design blocks.


usample (LTI models)Generate random samples of uncertain or generalized model
usample (Simulink)Generate random samples of uncertain variables in a Simulink model
rsampleBlockRandomly sample Control Design blocks in generalized model
usubsSubstitute given values for uncertain elements of uncertain objects
gridurealGrid ureal parameters uniformly over their range
complexifyReplace ureal atoms by summations of ureal and ucomplex (or ultidyn) atoms


Sample Uncertain Systems

Generate random samples of uncertain systems from within the modeled uncertainty range.

Generate Samples of Uncertain Systems

Use the usample function to randomly sample an uncertain model, returning non-uncertain instances of the uncertain model.

Evaluate Uncertain Elements by Substitution

Evaluate uncertain elements at particular values of their uncertain parameters, or sample them at multiple parameter values.

Substitution by usubs

Use the usubs command to set uncertain elements of an uncertain model to fixed values.

Model Arrays

Store multiple dynamic system objects in a single MATLAB® array for multiple-model design and analysis.

Array Management for Uncertain Objects

Arrays of uncertain models behave similarly to arrays of fixed-coefficient LTI models.