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Simulate a System Model—Wolfram Documentation

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• See Also
  • SystemModelSimulationData
  • SystemModelExamples
  • SystemModel
  • SystemModelSimulateSensitivity
  • SystemModelPlot
  • SystemModelParametricSimulate
  • NDSolveValue
  • DSolveValue
  • NBodySimulation
• Related Guides
  • Systems Modeling
  • Differential Equations
  • System Model Simulation
  • System Model Analytics & Design
  • System Modeling Overview
  • Scientific Models
  • Life Sciences & Medicine: Data & Computation
• Tech Notes
  • Getting Started with Model Simulation and Analysis

SystemModelSimulate[model,vars,{t_min,t_max}]

stores only simulation data for the variables vars.

• The model can have the following forms:
• SystemModelSimulate returns a SystemModelSimulationData object.
• The stored simulation variables vars can have the following values:
• Automatic automatically choose what to store {v₁,v₂,…} store only variables v_i All store all variables
• SystemModelSimulate[…,spec] uses Association spec for initial values, parameters and inputs:
• "ParameterValues" {p₁val₁,…} parameter p_i has value val_i "InitialValues" {v₁val₁,…} variable v_i has initial value val_i "Inputs" {in₁fun₁,…} input in_i has value fun_i[t] at time t
• Setting "ParameterValues" or "InitialValues" to {p_i->{c₁,c₂,…},…} runs simulations in parallel, with p_i taking values c_j.
• "InitialValues" corresponds to the start property in the Modelica model.
• The following options can be given:
• The option Method is supported when model is a SystemModel.
• Method settings take the form Method->"method" or Method{"method","sub₁"->val₁,…}.
• The following adaptive step methods can be used:
• "DASSL" DASSL DAE solver "CVODES" CVODES ODE solver
• Suboptions for adaptive-step methods include:
• "InterpolationPoints" Automatic number of interpolation points "Tolerance" 10^-6 tolerance for adaptive step size
• The following fixed-step methods can be used:
• "Euler" explicit Euler's method of order 1 "Heun" Heun's method of order 2 "RungeKutta" explicit Runge–Kutta method of order 4
• Suboptions for fixed-step methods include:
• "StepSize" 10^-3 fixed step size
• With Method->{"NDSolve",sub₁->val₁,…}, NDSolve is used as the solver. Method options sub_i are passed to NDSolve.

Simulate a model with the time interval of simulation settings from the model:

Do a parameter sweep over a voltage offset:

Plot the voltage for all simulations:

Use the diagram representation of a model as input:

Copy and paste the output above:

Or use the name string:

Simulate with settings from the model:

Simulate from time 0 to 5:

Simulate for an explicit time interval:

Use a Quantity to specify the time interval:

Initial values for variables can be set using "InitialValues":

Parameter values can be set using "ParameterValues":

Simulate a model that adds two inputs together:

Plot the inputs and the output:

Simulate for different initial values for the variable x:

Plot the variable x from all simulations:

Simulate a model with default parameters:

Set a parameter in the simulation:

Compare the variable between the simulations:

Do a parameter sweep over a voltage offset:

Plot the voltage for all simulations:

Setting ranges for two parameters simulates once for each position in the ranges:

Simulate a model with a TimeSeries as input:

Define a time series object:

Simulate the model:

Plot the input and the output:

Simulate a model and plot the variables x1 and x2:

Simulate a model:

Get simulation results for the variables x and x':

Plot the variables using the Plot function:

Simulate a model and find the maximum of a variable:

Get the value of the variable angle1v:

Find the maximum value of the angle:

Run a simulation and plot in a single call:

Specify arguments to SystemModelSimulate:

Store only selected variables:

Only the given variables are saved:

Debug messages are collected in the message group "WSMDebug":

Turn on debug messages for initialization:

Turn off all debug messages for "WSMDebug":

Simulate with interpolation orders 1 and 3, and 3 interpolation points:

Show the x variable:

Use a fixed-step solver:

Plot the result:

Use an adaptive-step solver:

Show the result in a ParametricPlot:

For stiff problems, use an adaptive-step method:

Simulating with too few interpolation points can give inexact plots:

Increasing the number of points gives a better result:

The default step size for a fixed-step solver might be smaller than needed:

Use a larger step size to speed up computation:

The result is comparable:

Let an adaptive solver choose the solver steps:

Use NDSolve for simulating a model:

The result is a SystemModelSimulationData object containing the simulation results:

Pass options to NDSolve:

The accuracy is reduced because of the options:

Calculate the overshoot of the height in a tank system:

Find the maximum peak value:

Get the value of the step sent in to the tank:

Calculate the overshoot:

Show the overshoot:

Calculate the rise time for the height in a tank system:

Get the required values at 10% and 90% by looking at the steady-state value for height:

Find the times at which the signal reaches these values:

Calculate the rise time:

Plot lines at the final value, and when the signal reaches 10% and 90% of the final value:

Calculate the settling time for the height in a tank system:

Find 5% bounds on the final value:

Find the time at which the signal stays within these values:

Plot the bounds and the found settling time:

Change parameter values interactively:

Simulate a rolling wheel for different starting inertias along the wheel axis:

Fetch the trajectories for the wheel:

Plot the trajectories:

Analyze resonance peaks when varying a spring constant:

Compute from :

Show the resonance peaks:

Calibrate parameters in a model by comparing to measurement data:

Set up a criteria function for model fitting:

Fit parameters to the test data:

Simulate with the fitted parameters:

Show the test data and the calibrated model together:

Filter sampled data from a Tinker Forge Weather Station:

Time shift and retrieve the magnitude of the data:

Run the time series through a lowpass filter:

Simulate a lowpass filter with sound as input:

Simulate with given input sound:

Retrieve the audio for input and output:

Simulate a Newton's cradle:

Fetch trajectories from the result:

Visualize the cradle:

Visualize simulated data with a WaveletScalogram:

Pick out the data you are interested in:

Compute the wavelet transform:

Plot the wavelet vector coefficients:

Simulate a Van der Pol model and show in a parametric plot:

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