how to run simulink simulation from matlab script

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hello i need to run simulink simulation from matlab, how to do it using matlab command in script ?

Accepted Answer

User_in_Gim
User_in_Gim on 16 Mar 2017
Hi,
You can use sim command line to simulate your model : doc sim.
sim('Model_Name',Simulation_Time) % most basic way to simulate with command script.
  6 Comments
Benjia
Benjia on 23 Jul 2024
Does the simulink model need to be open if we use this way?

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More Answers (3)

Reid Spence
Reid Spence on 22 Jan 2024
Edited: Reid Spence on 22 Jan 2024
A prefered way to run a simulation from MATLAB is to use the SimulationInput object.
simIn = Simulink.SimulationInput("Model_Name"); %create object
simIn = simIn.setVariable("my_Parameter",2); %example of setting a parameter override
out = sim(simIn); %run simulation, all results returned in "out"
The benifits of using the SimulationInput object over using ">sim("model_name")" include:
  • ability to override parameters and settings without dirtying the model
  • a helpful container for all run specific overrides
  • easier transitions to other workflows such as parallel simulation with parsim or deployment with Simulink Compiler

Guy Rouleau
Guy Rouleau on 9 Jul 2024

marcus sick
marcus sick on 13 Mar 2024
A recommended approach for executing simulations in MATLAB involves leveraging the SimulationInput object.
simIn = Simulink.SimulationInput("Model_Name i.e (YT3converter)"); % Create object simIn = simIn.setVariable("my_Parameter", 2); % Example of setting a parameter override out = sim(simIn); % Run simulation; all results are returned in "out"
The advantages of utilizing the SimulationInput object over the conventional method ">sim("model_name")" are manifold:
  • It enables parameter and setting overrides without modifying the model directly, ensuring model cleanliness and preserving its integrity.
  • Serving as a convenient container, it organizes all simulation-specific overrides, enhancing clarity and manageability.
  • Facilitates seamless transitions to alternative workflows like parallel simulation with parsim or deployment via Simulink Compiler, thus fostering versatility and adaptability in simulation practices.

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