Specify Behavioral Constraints

When converting a system to use fixed-point data types, use your system requirements to set signal tolerances and behavioral constraints on your model. The Fixed-Point Tool uses the information you provide to propose fixed-point data types that meet your requirements. After conversion, you can use signal tolerances and behavioral constraints to verify the numerical behavior of the fixed-point implementation.

In the Optimized Fixed-Point Conversion workflow of the Fixed-Point Tool, or when using fxpopt at the command line, you must specify at least one behavioral constraint using signal tolerances or Model Verification blocks. Data types are optimized to meet all specified constraints.

In the Iterative Fixed-Point Conversion workflow of the Fixed-Point Tool, or when using DataTypeWorkflow.Converter at the command line, you can specify behavioral constraints to improve data type proposals and verify the numerical behavior of the model with embedded types. After simulating with embedded types, the Workflow Browser indicates whether the embedded run meets the specified signal tolerances compared to the range collection run. For more information, see Verify New Settings.

Specify Target Hardware

Specify details of your target device in the Hardware Implementation pane of the Configuration Parameters dialog box. The Fixed-Point Tool uses this information to propose fixed-point data types. For more information, see How the Fixed-Point Tool Uses Target Hardware Information.

Specify Design Minimum and Maximum Values

For elements in your system which have known ranges, or minimum or maximum range limits, enter these as known design ranges in your model. The Fixed-Point Tool prioritizes this information when proposing fixed-point data types. If necessary, you can also specify a safety margin in the Fixed-Point Tool. For more information, see How the Fixed-Point Tool Uses Range Information.

Specify Known Parameter Data Types

When using fxpopt to optimize data types, you can specify known parameter data types. These known parameter data types are not considered during range collection, and will not be changed during the optimization process.

Lock Blocks Against Automatic Data Typing

You can choose to lock some blocks against automatic data typing by selecting the Lock output data type setting against changes by the fixed-point tools parameter for the block. For more information, see Use Lock Output Data Type Setting.

Create a Test Bench with Multiple Simulation Inputs

Create a thorough test bench for range collection and verification by using the Simulink.SimlationInput object to specify multiple simulation scenarios. Including simulation scenarios that cover the full range of real-world use cases can improve data type proposals. During range collection, the Fixed-Point Tool merges the results from these simulation runs and proposes data types based on the merged ranges. After conversion to fixed point, you can use the simulation scenarios again to verify performance of the model with embedded types applied.

For examples, see Use the Fixed-Point Tool to Explore Numerical Behavior, Propose Data Types for Merged Simulation Ranges, and Optimize Data Types Using Multiple Simulation Scenarios.

Specify Signal Tolerances

You can specify tolerances for signals in your model that have signal logging enabled. To enable signal logging:

  • In the Simulink® Editor, select one or more signals.

  • In the Signal tab of the Simulink Editor, click Log Signals.

In the Fixed-Point Tool, specify individual signal tolerances in the table under Signal Tolerances. The table contains all signals in the model with signal logging enabled. If you log additional signals after opening the Fixed-Point Tool, click Refresh Signals to update the Signal Tolerances table. At the command line, specify tolerances using the addTolerance method.

You can specify any of the following types of tolerances:

  • Abs Tol — Absolute value of the maximum acceptable difference between the original signal and the signal in the converted design.

  • Rel Tol — Maximum relative difference, specified as a percentage, between the original signal and the signal in the converted design. For example, a value of 1e-2 indicates a maximum relative difference of one percent.

  • Time Tol (seconds) — Time interval, in which the maximum and minimum values define the upper and lower values to compare against.

Enter signal tolerances using any valid MATLAB® expression that returns a finite, non-negative value. (since R2023a)

You can define a tolerance band using any combination of absolute, relative, and time tolerance values. When you specify the tolerance for your signal using multiple types of tolerances, the overall tolerance band is computed by selecting the most lenient tolerance result for each data point. For more information about how tolerances are computed, see Tolerance Computation.

Use Model Verification Blocks

You can use enabled Model Verification blocks to specify custom behavioral constraints on the behavior of your system.

The blocks in the Model Verification library maintain a true (1) assertion when a specified desired behavior is maintained by the input signals. The block halts the simulation and returns an error message by default if the true (1) assertion is not maintained. If a new fixed-point implementation is unable to maintain a true (1) assertion for a Model Verification block during simulation, that set of data types is considered infeasible for the model because it does not meet the specified constraints.

All Model Verification blocks must be able to maintain a true (1) assertion when the model is simulated with the floating-point data type selected for data type override in order to establish a baseline for the model behavior.

The following examples use Model Verification blocks for data type optimization.

See Also

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