Tightening the error tolerances

Multiple Simulations Workflow Tips

This example uses:

The goal of this example is to provide helpful tips for running multiple simulations using parallel simulation tools. This example will work even if the Parallel Computing Toolbox™ is not available, but the simulations will run in serial. We will be using the model sldemo_suspn_3dof .

Initializing an Array of Simulink.SimulationInput Objects

Typically you will construct an array of Simulink.SimulationInput objects in order to run multiple simulations. There are several ways to initialize the array before populating it with data.

Method 1: Initialize the array before the loop

Method 2: Initialize the array in the loop

Note that the loop variable idx starts from the largest value so that the entire array is pre-allocated.

Setting Model and Block Parameters

The setModelParameter and setBlockParameter methods use the same parameter-value pair syntax that the set_param API uses. This means that most values you pass in to these methods should be character arrays, not their literal value.

Setting Variables

The setVariable method expects that you will pass the literal value you want to assign to a variable. The idea is that this closely reflects the assignin syntax.

Diagnosing Runtime Errors

Assume that you’ve accidentally set up an array of Simulink.SimulationInput objects with an incorrect value.

Simulating these will cause a runtime error

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Why do I get error when running my Simulink model? How do I reduce the fixed step size and what is meant by tightening the error tolerances?

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Tightening the error tolerances simulink

Specify the largest acceptable solver error, relative to the size of each state during each time step. If the relative error exceeds this tolerance, the solver reduces the time step size.

Settings

Setting the relative tolerance to auto is actually the default value of 1e-3 .

The relative tolerance is a percentage of the state’s value.

The default value ( 1e-3 ) means that the computed state is accurate to within 0.1%.

The acceptable error at each time step is a function of both the Relative tolerance and the Absolute tolerance. For more information about how these settings work together, see Error Tolerances for Variable-Step Solvers.

During each time step, the solver computes the state values at the end of the step and also determines the local error – the estimated error of these state values. If the error is greater than the acceptable error for any state, the solver reduces the step size and tries again.

The default relative tolerance value is sufficient for most applications. Decreasing the relative tolerance value can slow down the simulation.

To check the accuracy of a simulation after you run it, you can reduce the relative tolerance to 1e-4 and run it again. If the results of the two simulations are not significantly different, you can feel confident that the solution has converged.

Dependencies

This parameter is enabled only if you set:

Solver Type to Variable-step .

Solver to a continuous variable-step solver.

This parameter works along with Absolute tolerance to determine the acceptable error at each time step. For more information about how these settings work together, see Error Tolerances for Variable-Step Solvers.

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How to fix tolerances in matlab simulink. this showing diagonistic error.

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Multiple Simulations Workflow Tips

This example uses:

The goal of this example is to provide helpful tips for running multiple simulations using parallel simulation tools. This example will work even if the Parallel Computing Toolbox™ is not available, but the simulations will run in serial. We will be using the model sldemo_suspn_3dof .

Initializing an Array of Simulink.SimulationInput Objects

Typically you will construct an array of Simulink.SimulationInput objects in order to run multiple simulations. There are several ways to initialize the array before populating it with data.

Method 1: Initialize the array before the loop

Method 2: Initialize the array in the loop

Note that the loop variable idx starts from the largest value so that the entire array is pre-allocated.

Setting Model and Block Parameters

The setModelParameter and setBlockParameter methods use the same parameter-value pair syntax that the set_param API uses. This means that most values you pass in to these methods should be character arrays, not their literal value.

Setting Variables

The setVariable method expects that you will pass the literal value you want to assign to a variable. The idea is that this closely reflects the assignin syntax.

Diagnosing Runtime Errors

Assume that you’ve accidentally set up an array of Simulink.SimulationInput objects with an incorrect value.

Simulating these will cause a runtime error

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Levi asked . 2020-07-10

I am receiving the following error messages about singularities in my Simulink model:

 Derivative of block at time is Inf of NaN.  Stopping Simulation.  There may be a singularity in the solution.  If not, try reducing the step size (either by reducing the fixed step size or by tightening the error tolerances.)

I have tried reducing the step size and adjusting tolerances, but I still receive this error message. I have also tried changing solvers, some solvers will just get to one point of the simulation, and hang.

Simulink, Matlab

Kshitij Singh answered . 2023-02-10 01:49:27

This message may be caused by a singularity in your system. One situation where this may occur is if the values of your states differ by a large magnitude. If this is the case, the Simulink solver will have a hard time resolving your step size within the error tolerance as it attempts to «bounce» back and forth between the states.

To check if this is the case:

1. Return the states of your system as follows-

a) In the model editor go to Simulation-> Configuration Parameters

b) Select Data Import/Export, in the ‘Save to Workspace’ field, check ‘States’ to log the states as output

2. Run the simulation.

3. Plot:

plot(tout,xout)

You can see if one of the states is changing over a wide range compared to the others.

There are a couple of things you can do to try to correct this situation. If possible, you may want to rescale the model so that the states are within a couple of orders of magnitude of one another.

Also, you can set specific error tolerances for the integrator blocks in your system. For more information, please refer to ‘Specifying the Absolute Tolerance for the Block’s Outputs’ section in the Integrator block documentation by entering

doc integrator

at the MATLAB command prompt.

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