generate parameter samples for sensitivity analysis -凯发k8网页登录

generate parameter samples for sensitivity analysis

you can perform global sensitivity analysis using simulink^® design optimization™ software. using techniques such as design of experiments (doe) (also referred to as experimental design), you can choose a parameter set for sensitivity analysis.

you generate parameter samples by varying the value of the simulink model parameters and states of interest according to a specified probability distribution. these parameters and states are collectively referred to as parameters. the set of parameters you want to vary for a particular analysis, together with the specifications for varying them (such as probability distributions or specified sets of values) defines a parameter space. each combination of generated parameter values is referred to as a sample or sample point. a collection of samples is referred to as a design space, sample space, or parameter set.

for sensitivity analysis, in addition to generating a parameter set, you define a cost function by creating design requirements on the model signals. you then evaluate the cost function for each sample in the parameter set. finally, you analyze the relation between the parameters and requirement to understand how varying the parameters influences the cost function.

you can generate two kinds of parameter values:

— draw sets of random parameter values using a uniform probability distribution or probability distributions you specify.
— specify a grid of allowed parameter values to create a parameter set of points in the grid.

you can generate both types of parameter samples in sensitivity analyzer or at the command line. for details, see:

generate parameter samples for sensitivity analysis -凯发k8网页登录