Simulink Control Design™ - MathWorks

Batch Linearization Efficiency When You Vary Parameter

Values

You can use the Simulink Control Design linearization tools to efficiently batch linearize a

model at varying model parameter values. If all the model parameters you vary are

tunable, the linearization tools use a single model compilation to compute linearizations

for all parameter grid points.

Tunable and Nontunable Parameters

The term tunable parameters refers to parameters whose values you can change during

model simulation without recompiling the model. In general, only parameters that

represent mathematical variables are tunable. Common tunable parameters include the

Gain parameter of the Gain block, PID gains of the PID Controller block, and Numerator

and Denominator coefficients of the Transfer Fcn block.

In contrast, when you vary the value of nontunable parameters, the linearization tools

compile the model for each parameter grid point. This repeated compilation makes batch

linearization slower. Parameters that specify the appearance or structure of a block, such

as the number of inputs of a Sum block, are not tunable. Parameters that specify when a

block is evaluated, such as a block's sample time or priority, are also not tunable.

Controlling Model Recompilation

By default, the linearization tools compute all linearizations with a single compilation

whenever it is possible to do so, i.e., whenever all parameters are tunable. If the software

detects nontunable parameters specified for variation, it issues a warning and recompiles

the model for each parameter-grid point. You can change this default behavior at the

command line using the AreParamsTunable option of linearizeOptions. In the

Linear Analysis Tool, click More Options and use the Recompile the model when

parameter values are varied for linearization option. The following table describes

how these options affect the recompilation behavior.

3 Batch Linearization