Speed Up Linearization of Complex Models
Factors That Impact Linearization Performance
Large Simulink models and blocks with complex initialization functions can slow
linearization.Usually, the time it takes to linearize a model is directly related to the time it takes to
update the block diagram (Simulink).Blocks with Complex Initialization Functions
Use the MATLAB Profiler to identify complex bottlenecks in block initialization functions.In the MATLAB Profiler, run the command:set_param(modelname,'SimulationCommand','update')Disabling the Linearization Advisor in the Linear Analysis Tool
You can speed up the linearization of large models by disabling the Linearization Advisor
in the Linear Analysis Tool.The Linearization Advisor stores diagnostic information, including linearization values of
individual blocks, which can impact linearization performance.To disable the Linearization Advisor, in the Linear Analysis Tool, on the Linear Analysis
tab, clear Linearization Advisor.TipAlternatively, you can disable the Linearization Advisor globally in the Simulink
Control Design tab of the MATLAB preferences dialog box. Clear the Launch
Linearization for exact linearizations in the linear analysis tool check box. This
global preference persists from session to session until you change this preference.Batch Linearization of Large Simulink Models
When batch linearizing a large model that contains only a few varying parameters, you
can use linlftfold to reduce the computational load.4 Troubleshooting Linearization Results