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Discrete-Time Integrator

Perform discrete-time integration or accumulation of signal

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  • Discrete-Time Integrator block

Libraries:
Simulink / Commonly Used Blocks
Simulink / Discrete
HDL Coder / Discrete
HDL Coder / HDL Floating Point Operations

Description

Use the Discrete-Time Integrator block in place of the Integrator block to create a purely discrete model. With the Discrete-Time Integrator block, you can:

  • Define initial conditions on the block dialog box or as input to the block

  • Define an input gain (K) value

  • Output the block state

  • Define upper and lower limits on the integral

  • Reset the state with an additional reset input

Output Equations

With the first time step, block state n = 0, with either initial output y(0) = IC or initial state x(0) = IC, depending on the Initial condition setting parameter value.

For a given step n > 0 with simulation time t(n), Simulink® updates output y(n) as follows:

  • Forward Euler method:

    y(n) = y(n-1) + K*[t(n) - t(n-1)]*u(n-1)

  • Backward Euler method:

    y(n) = y(n-1) + K*[t(n) - t(n-1)]*u(n)

  • Trapezoidal method:

    y(n) = y(n-1) + K*[t(n)-t(n-1)]*[u(n)+u(n-1)]/2

Simulink automatically selects a state-space realization of these output equations depending on the block sample time, which can be explicit or triggered. When using explicit sample time, t(n)-t(n-1) reduces to the sample time T for all n > 0.

Integration and Accumulation Methods

This block can integrate or accumulate a signal using a forward Euler, backward Euler, or trapezoidal method. Assume that u is the input, y is the output, and x is the state. For a given step n, Simulink updates y(n) and x(n+1). In integration mode, T is the block sample time (delta T in the case of triggered sample time). In accumulation mode, T = 1. The block sample time determines when the output is computed but not the output value. K is the gain value. Values clip according to upper or lower limits.

Forward Euler Method

Forward Euler method (default), also known as forward rectangular, or left-hand approximation

The software approximates 1/s as T/(z-1). The expressions for the output of the block at step n are:

x(n+1) = x(n) + K*T*u(n)
y(n)   = x(n)

The block uses these steps to compute the output:

Step 0:          y(0)   = IC (clip if necessary)
                 x(1)   = y(0) + K*T*u(0)

Step 1:          y(1)   = x(1)
                 x(2)   = x(1) + K*T*u(1)

Step n:          y(n)   = x(n)
                 x(n+1) = x(n) + K*T*u(n) (clip if necessary)

Using this method, input port 1 does not have direct feedthrough.

Backward Euler Method

Backward Euler method, also known as backward rectangular or right-hand approximation

The software approximates 1/s as T*z/(z-1). The resulting expression for the output of the block at step n is

y(n) = y(n-1) + K*T*u(n).

Let x(n) = y((n)-1). The block uses these steps to compute the output.

  • If the parameter Initial condition setting is set to Output or Auto for triggered and function-call subsystems:

    Step 0:          y(0) = IC (clipped if necessary)
                 x(1) = y(0)

  • If the parameter Initial condition setting is set to Auto for non-triggered subsystems:

    Step 0:          x(0)   = IC (clipped if necessary)
                 x(1)   = y(0) = x(0) + K*T*u(0)

Step 1:          y(1)   = x(1) + K*T*u(1)
                 x(2)   = y(1)

Step n:          y(n)   = x(n) + K*T*u(n)
                 x(n+1) = y(n)

Using this method, input port 1 has direct feedthrough.

Trapezoidal Method

For this method, the software approximates 1/s as T/2*(z+1)/(z-1).

When T is fixed (equal to the sampling period), the expressions to compute the output are:

x(n) = y(n-1) + K*T/2*u(n-1)
y(n) = x(n) + K*T/2*u(n)

  • If the parameter Initial condition setting is set to Output or Auto for triggered and function-call subsystems:

    Step 0:          y(0)   = IC (clipped if necessary)
                 x(1)   = y(0) + K*T/2*u(0)

  • If the parameter Initial condition setting is set to Auto for non-triggered subsystems:

    Step 0:          x(0)   = IC (clipped if necessary)
                 y(0)   = x(0) + K*T/2*u(0)
                 x(1)   = y(0) + K*T/2*u(0)

Step 1:          y(1)   = x(1) + K*T/2*u(1)
                 x(2)   = y(1) + K*T/2*u(1)

Step n:          y(n)   = x(n) + K*T/2*u(n)
                 x(n+1) = y(n) + K*T/2*u(n)

Here, x(n+1) is the best estimate of the next output. It is not the same as the state, in that x(n) is not equal to y(n).

Using this method, input port 1 has direct feedthrough.

When T is a Variable

WhenT is a variable (for example, obtained from the triggering times), the block uses these steps to compute the output.

  • If the parameter Initial condition setting is set to Output or Auto for triggered and function-call subsystems:

    Step 0:          y(0)   = IC (clipped if necessary)
                 x(1)   = y(0)

  • If the parameter Initial condition setting is set to Auto for non-triggered subsystems:

    Step 0:          x(0)   = IC (clipped if necessary)
                 x(1)   = y(0) = x(0) + K*T/2*u(0)

Step 1:          y(1)   = x(1) + K*T/2*(u(1) + u(0))
                 x(2)   = y(1)

Step n:          y(n)   = x(n) + K*T/2*(u(n) + u(n-1))
                 x(n+1) = y(n)

Define Initial Conditions

You can define the initial conditions as a parameter on the block dialog box or input them from an external signal:

  • To define the initial conditions as a block parameter, set the Initial condition source parameter to internal and enter the value in the Initial condition text box.

  • To provide the initial conditions from an external source, set the Initial condition source parameter to external. An additional input port appears on the block.

When to Use the State Port

Use the state port instead of the output port:

  • When the output of the block is fed back into the block through the reset port or the initial condition port, causing an algebraic loop. For an example, see the sldemo_bounce_two_integrators model.

  • When you want to pass the state from one conditionally executed subsystem to another, which can cause timing problems. For an example, see Building a Clutch Lock-Up Model.

You can work around these problems by passing the state through the state port rather than the output port. Simulink generates the state at a slightly different time from the output, which protects your model from these problems. To output the block state, select the Show state port check box. The state port appears on the top of the block.

Limit the Integral

To keep the output within certain levels, select the Limit output check box and enter the limits in the corresponding text box. Doing so causes the block to function as a limited integrator. When the output reaches the limits, the integral action turns off to prevent integral windup. During a simulation, you can change the limits but you cannot change whether the output is limited. The table shows how the block determines output.

IntegralOutput
Less than the Lower saturation limitHeld at the Lower saturation limit
Between the Lower saturation limit and the Upper saturation limitThe integral
Greater than the Upper saturation limitHeld at the Upper saturation limit

To generate a signal that indicates when the integral reaches limit, select the Show saturation port check box. A new saturation port appears below the block output port.

The saturation signal has one of three values:

  • 1 indicates that the integral is at the upper limit.

  • 0 indicates that the integral is not limited.

  • -1 indicates that the integral is at the lower limit.

Reset the State

The block resets its state to the specified initial condition, based on an external signal. To cause the block to reset its state, select one of the External reset parameter options. A reset port appears that indicates the reset trigger type.

The reset port has direct feedthrough. If the block output feeds back into this port, either directly or through a series of blocks with direct feedthrough, an algebraic loop results. To resolve this loop, feed the output of the block state port into the reset port instead. To access the block state, select the Show state port check box.

Reset Trigger Types

The External reset parameter lets you determine the attribute of the reset signal that triggers the reset. The trigger options include:

  • rising – Resets the state when the reset signal has a rising edge. For example, this figure shows the effect that a rising reset trigger has on backward Euler integration.

  • falling — Resets the state when the reset signal has a falling edge. For example, this figure shows the effect that a falling reset trigger has on backward Euler integration.

  • either — Resets the state when the reset signal rises or falls. For example, the following figure shows the effect that an either reset trigger has on backward Euler integration.

  • level — Resets and holds the output to the initial condition while the reset signal is nonzero. For example, this figure shows the effect that a level reset trigger has on backward Euler integration.

  • sampled level — Resets the output to the initial condition when the reset signal is nonzero. For example, this figure shows the effect that a sampled level reset trigger has on backward Euler integration.

    The sampled level reset option requires fewer computations, making it more efficient than the level reset option.

    Note

    For the Discrete-Time Integrator block, all trigger detections are based on signals with positive values. For example, a signal changing from -1 to 0 is not considered a rising edge, but a signal changing from 0 to 1 is.

Behavior in Simplified Initialization Mode

Simplified initialization mode is enabled when you set Underspecified initialization detection to Simplified in the Configuration Parameters dialog box. If you use simplified initialization mode, the behavior of the Discrete-Time Integrator block differs from classic initialization mode. The new initialization behavior is more robust and provides more consistent behavior in these cases:

  • In algebraic loops

  • On enable and disable

  • When comparing results using triggered sample time against explicit sample time, where the block is triggered at the same rate as the explicit sample time

Simplified initialization mode enables easier conversion from Continuous-Time Integrator blocks to Discrete-Time Integrator blocks, because the initial conditions have the same meaning for both blocks.

For more information on classic and simplified initialization modes, see Underspecified initialization detection.

Enable and Disable Behavior with Initial Condition Setting set to Output

When you use simplified initialization mode with Initial condition setting set to Output for triggered and function-call subsystems, the enable and disable behavior of the block is simplified as follows.

At disable time td:

 y(td) = y(td-1)

At enable time te:

  • If the parent subsystem control port has States when enabling set to reset:

    y(te) = IC.

  • If the parent subsystem control port has States when enabling set to held:

    y(te) = y(td).

    The following figure shows this condition.

Iterator Subsystems

When using simplified initialization mode, you cannot place the Discrete-Time Integrator block in an iterator subsystem block.

In simplified initialization mode, Iterator subsystems do not maintain elapsed time. Thus, if a Discrete-Time Integrator block, which needs elapsed time, is placed inside an iterator subsystem block, Simulink reports an error.

Behavior in an Enabled Subsystem Inside a Function-Call Subsystem

Suppose you have a function-call subsystem that includes an enabled subsystem, which contains a Discrete-Time Integrator block. The following behavior applies.

Integrator MethodSample Time Type of Function-Call Trigger Port Value of delta T When Function-Call Subsystem Executes for the First Time After Enabled Reason for Behavior

Forward Euler

Triggered

t — tstart

When the function-call subsystem executes for the first time, the integrator algorithm uses tstart as the previous simulation time.

Backward Euler and Trapezoidal

Triggered

t — tprevious

When the function-call subsystem executes for the first time, the integrator algorithm uses tprevious as the previous simulation time.

Forward Euler, Backward Euler, and Trapezoidal

Periodic

Sample time of the function-call generator

In periodic mode, the Discrete-Time Integrator block uses sample time of the function-call generator for delta T.

Examples

Discrete-Time Integration Using the Forward Euler Integration Method

Discrete-Time Integration Using the Forward Euler Integration Method

The model sldemo_fuelsysuses a Discrete-Time Integrator block in the subsystem fuel_rate_control/airflow_calc.

Building a Clutch Lock-Up Model

Building a Clutch Lock-Up Model

Use Simulink® to model and simulate a rotating clutch system. Although modeling a clutch system is difficult because of topological changes in the system dynamics during lockup, this example shows how enabled subsystem can easily handle such problems. We illustrate how to employ important Simulink modeling concepts in the creation of the clutch simulation. Designers can apply these concepts to many models with strong discontinuities and constraints that may change dynamically.

Simulation of Bouncing Ball

Simulation of Bouncing Ball

Uses two models of a bouncing ball to show different approaches to modeling hybrid dynamic systems with Zeno behavior. Zeno behavior is informally characterized by an infinite number of events occurring in a finite time interval for certain hybrid systems. As the ball loses energy, the ball collides with the ground in successively smaller intervals of time.

Ports

Input

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Input signal, specified as a scalar, vector, or matrix

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | fixed point

External reset signal, specified as a scalar. When the specified trigger event occurs, the block resets the states to their initial conditions.

Tip

The icon for this port changes based on the value of the External reset parameter.

Dependencies

To enable this port, set External reset to rising, falling, either, level, or sampled level.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | fixed point

Initial conditions of the states, specified as a finite scalar, vector, or matrix.

Dependencies

To enable this port, set Initial condition source to external.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | fixed point

Output

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Discrete-time integration or accumulation of the input signal, specified as a scalar, vector, or matrix.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | fixed point

Signal indicating when the state is being limited, specified as a scalar, vector, or matrix. The signal has one of three values:

  • 1 indicates that the upper limit is being applied.

  • 0 indicates that the integral is not limited.

  • -1 indicates that the lower limit is being applied.

Dependencies

To enable this port, select the Show saturation port check box.

Data Types: single | double | int8

Block states, output as a scalar, vector, or matrix. By default, the block adds this port to the top of the block icon. Use the state port when:

  • The output of the block is fed back into the block through the reset port or the initial condition port, causing an algebraic loop. For an example, see the sldemo_bounce_two_integrators model.

  • You want to pass the state from one conditionally executed subsystem to another, which can cause timing problems. For an example, see the sldemo_clutch model.

For more information, see When to Use the State Port.

Dependencies

To enable this port, select the Show state port check box.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | fixed point

Parameters

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Main

Specify the integration or accumulation method. See Output Equations and Integration and Accumulation Methods for more information.

Programmatic Use

Block Parameter: IntegratorMethod
Type: character vector
Values: 'Integration: Forward Euler' | 'Integration: Backward Euler' | 'Integration: Trapezoidal' | 'Accumulation: Forward Euler' | 'Accumulation: Backward Euler' | 'Accumulation: Trapezoidal'
Default: 'Integration: Forward Euler'

Specify a scalar, vector, or matrix by which to multiply the integrator input. Each element of the gain must be a positive real number.

  • Specifying a value other than 1.0 (the default) is semantically equivalent to connecting a Gain block to the input of the integrator.

  • Valid entries include:

    • double(1.0)

    • single(1.0)

    • [1.1 2.2 3.3 4.4]

    • [1.1 2.2; 3.3 4.4]

Tip

Using this parameter to specify the input gain eliminates a multiplication operation in the generated code. However, this parameter must be nontunable to realize this benefit. If you want to tune the input gain, set this parameter to 1.0 and use an external Gain block to specify the input gain.

Programmatic Use

Block Parameter: gainval
Type: character vector
Values: scalar | vector
Default: '1.0'

Select the type of trigger event that resets the states to their initial conditions:

  • none — Do not reset the state to initial conditions.

  • rising — Reset the state when the reset signal has a rising edge.

  • falling — Reset the state when the reset signal has a falling edge.

  • either — Reset the state when the reset signal rises or falls.

  • level — Reset and hold the output to the initial condition while the reset signal is nonzero.

  • sampled level — Reset the output to the initial condition when the reset signal is nonzero.

For more information, see Reset the State and Reset Trigger Types.

Programmatic Use

Block Parameter: ExternalReset
Type: character vector
Values: 'none' | 'rising' | 'falling' | 'either' | 'level' | 'sampled level'
Default: 'none'

Select source of initial condition:

  • internal — Get the initial conditions of the states from the Initial condition parameter.

  • external — Get the initial conditions of the states from an external signal. When you select this option, an input port appears on the block.

Programmatic Use

Block Parameter: InitialConditionSource
Type: character vector, string
Values: 'internal' | 'external'
Default: 'internal'

Specify initial condition of the block states. The minimum and maximum values are bound by the Output minimum and Output maximum block parameters.

Tip

Simulink software does not allow the initial condition of this block to be inf or NaN.

Dependencies

To enable this parameter, set the Initial condition source to internal.

Programmatic Use

Block Parameter: InitialCondition
Type: character vector, string
Values: scalar | vector | matrix
Default: '0'

Select whether to apply the value of the Initial condition parameter to the block state or block output. The initial condition is also the reset value.

  • Auto — Block chooses where to apply the Initial condition parameter.

    • If the block is in a non-triggered subsystem and Integrator method is set to an integration method, set initial conditions:

      x(0) = IC

      At reset:

      x(n) = IC

    • If the block is in a triggered or function-call subsystem and Integrator method is set to an integration method, set initial conditions as if output was selected.

  • Output — Use this option when the block is in a triggered or a function-call subsystem and Integrator method is set to an integration method.

    Set initial conditions:

    y(0) = IC

    At reset:

    y(n) = IC

  • Compatibility — This option is present to provide backward compatibility. You cannot select this option for Discrete-Time Integrator blocks in Simulink models but you can select it for Discrete-Time Integrator blocks in a library. Use this option to maintain compatibility with Simulink models created before R2014a.

    Prior to R2014a, the option Auto was known as State only (most efficient). The option Output was known as State and output. The behavior of the block with the option Compatibility is as follows.

    • If Underspecified initialization detection is set to Classic, the Initial condition setting parameter behaves as Auto.

    • If Underspecified initialization detection is set to Simplified, the Initial condition setting parameter behaves as Output.

Note

This parameter was named Use initial condition as initial and reset value for in Simulink before R2014a.

Programmatic Use

Block Parameter: InitialConditionSetting
Type: character vector
Value: 'Auto' | 'Output' | 'Compatibility'
Default: 'Auto'

Enter the discrete time interval between steps.

By default, the block uses a discrete sample time of 1. To set a different sample time, enter another discrete value, such as 0.1.

See Specify Sample Time for more information.

Tips

  • Do not specify a sample time of 0. This value specifies a continuous sample time, which the Discrete-Time Integrator block does not support.

  • Do not specify a sample time of inf or NaN because these values are not discrete.

  • If you specify -1 to inherit the sample time from an upstream block, verify that the upstream block uses a discrete sample time. For example, the Discrete-Time Integrator block cannot inherit a sample time of 0.

Programmatic Use

Block Parameter: SampleTime
Type: character vector
Values: scalar | vector
Default: '-1'

Limit the block's output to a value between the Lower saturation limit and Upper saturation limit parameters.

  • Selecting this check box limits the block's output to a value between the Lower saturation limit and Upper saturation limit parameters.

  • Clearing this check box does not limit the block's output values.

Dependencies

Selecting this parameter enables the Lower saturation limit and Upper saturation limit parameters.

Programmatic Use

Block Parameter: LimitOutput
Type: character vector
Values: 'off' | 'on'
Default: 'off'

Specify the upper limit for the integral as a scalar, vector, or matrix. You must specify a value between the Output minimum and Output maximum parameter values.

Dependencies

To enable this parameter, select the Limit output check box.

Programmatic Use

Block Parameter: UpperSaturationLimit
Type: character vector, string
Values: scalar | vector | matrix
Default: 'inf'

Specify the lower limit for the integral as a scalar, vector, or matrix. You must specify a value between the Output minimum and Output maximum parameter values.

Dependencies

To enable this parameter, select the Limit output check box.

Programmatic Use

Block Parameter: LowerSaturationLimit
Type: character vector , string
Values: scalar | vector | matrix
Default: '-inf'

Select this check box to add a saturation output port to the block. When you clear this check box, the block does not have a saturation output port.

Dependencies

Selecting this parameter enables a saturation output port.

Programmatic Use

Block Parameter: ShowSaturationPort
Type: character vector , string
Values: 'off' | 'on'
Default: 'off'

Select this check box to add a state output port to the block. When you clear this check box, the block does not have a state output port.

Dependencies

Selecting this parameter enables a state output port.

Programmatic Use

Block Parameter: ShowStatePort
Type: character vector , string
Values: 'off' | 'on'
Default: 'off'

Select this check box to have Simulink linearization commands treat this block as not resettable and as having no limits on its output, regardless of the settings of the block reset and output limitation options.

Tip

Ignoring the limit and resetting allows you to linearize a model around an operating point. This point may cause the integrator to reset or saturate.

Programmatic Use

Block Parameter: IgnoreLimit
Type: character vector
Values: 'off' | 'on'
Default: 'off'

Signal Attributes

Lower value of the output range that the software checks.

The software uses the minimum to perform:

Tips

Output minimum does not saturate or clip the actual output signal. Use the Saturation block instead.

Programmatic Use

To set the block parameter value programmatically, use the set_param function.

Parameter: OutMin
Values: '[]' (default) | scalar in quotes

Upper value of the output range that the software checks.

The software uses the maximum value to perform:

Tips

Output maximum does not saturate or clip the actual output signal. Use the Saturation block instead.

Programmatic Use

To set the block parameter value programmatically, use the set_param function.

Parameter: OutMax
Values: '[]' (default) | scalar in quotes

Choose the data type for the output. The type can be inherited, specified directly, or expressed as a data type object such as Simulink.NumericType. For more information, see Control Data Types of Signals.

When you select an inherited option, the block behaves as follows:

  • Inherit: Inherit via internal rule — Simulink chooses a data type to balance numerical accuracy, performance, and generated code size, while taking into account the properties of the embedded target hardware. If you change the embedded target settings, the data type selected by the internal rule might change. For example, if the block multiplies an input of type int8 by a gain of int16 and ASIC/FPGA is specified as the targeted hardware type, the output data type is sfix24. If Unspecified (assume 32-bit Generic), i.e., a generic 32-bit microprocessor, is specified as the target hardware, the output data type is int32. If none of the word lengths provided by the target microprocessor can accommodate the output range, Simulink software displays an error in the Diagnostic Viewer.

    It is not always possible for the software to optimize code efficiency and numerical accuracy at the same time. If the internal rule doesn’t meet your specific needs for numerical accuracy or performance, use one of the following options:

    • Specify the output data type explicitly.

    • Use the simple choice of Inherit: Same as input.

    • Explicitly specify a default data type such as fixdt(1,32,16) and then use the Fixed-Point Tool to propose data types for your model. For more information, see fxptdlg (Fixed-Point Designer).

    • To specify your own inheritance rule, use Inherit: Inherit via back propagation and then use a Data Type Propagation block. Examples of how to use this block are available in the Signal Attributes library Data Type Propagation Examples block.

  • Inherit: Inherit via back propagation — Use data type of the driving block.

Programmatic Use

Block Parameter: OutDataTypeStr
Type: character vector
Values: 'Inherit: Inherit via internal rule | 'Inherit: Inherit via back propagation' | 'double' | 'single' | 'int8' | 'uint8' | 'int16' | 'uint16' | 'int32' | 'uint32' | 'int64' | 'uint64' | 'fixdt(1,16)' | 'fixdt(1,16,0)' | 'fixdt(1,16,2^0,0)' | '<data type expression>'
Default: 'Inherit: Inherit via internal rule'

Select this parameter to prevent the fixed-point tools from overriding the Output data type you specify on the block. For more information, see Use Lock Output Data Type Setting (Fixed-Point Designer).

Programmatic Use

To set the block parameter value programmatically, use the set_param function.

Parameter: LockScale
Values: 'off' (default) | 'on'

Choose one of these rounding modes.

Ceiling

Rounds both positive and negative numbers toward positive infinity. Equivalent to the MATLAB® ceil function.

Convergent

Rounds number to the nearest representable value. If a tie occurs, rounds to the nearest even integer. Equivalent to the Fixed-Point Designer™ convergent function.

Floor

Rounds both positive and negative numbers toward negative infinity. Equivalent to the MATLAB floor function.

Nearest

Rounds number to the nearest representable value. If a tie occurs, rounds toward positive infinity. Equivalent to the Fixed-Point Designer nearest function.

Round

Rounds number to the nearest representable value. If a tie occurs, rounds positive numbers toward positive infinity and rounds negative numbers toward negative infinity. Equivalent to the Fixed-Point Designer round function.

Simplest

Automatically chooses between round toward floor and round toward zero to generate rounding code that is as efficient as possible.

Zero

Rounds number toward zero. Equivalent to the MATLAB fix function.

Programmatic Use

Block Parameter: RndMeth
Type: character vector
Values: 'Ceiling' | 'Convergent' | 'Floor' | 'Nearest' | 'Round' | 'Simplest' | 'Zero'
Default: 'Floor'

See Also

For more information, see Rounding Modes (Fixed-Point Designer).

Specify whether overflows saturate or wrap.

  • on — Overflows saturate to either the minimum or maximum value that the data type can represent.

  • off — Overflows wrap to the appropriate value that the data type can represent.

For example, the maximum value that the signed 8-bit integer int8 can represent is 127. Any block operation result greater than this maximum value causes overflow of the 8-bit integer.

  • With this parameter selected, the block output saturates at 127. Similarly, the block output saturates at a minimum output value of -128.

  • With this parameter cleared, the software interprets the overflow-causing value as int8, which can produce an unintended result. For example, a block result of 130 (binary 1000 0010) expressed as int8 is -126.

Tips

  • Consider selecting this parameter when your model has a possible overflow and you want explicit saturation protection in the generated code.

  • Consider clearing this parameter when you want to optimize efficiency of your generated code. Clearing this parameter also helps you to avoid overspecifying how a block handles out-of-range signals. For more information, see Troubleshoot Signal Range Errors.

  • When you select this parameter, saturation applies to every internal operation on the block, not just the output or result.

  • In general, the code generation process can detect when overflow is not possible. In this case, the code generator does not produce saturation code.

Programmatic Use

To set the block parameter value programmatically, use the set_param function.

Parameter: SaturateOnIntegerOverflow
Values: 'off' (default) | 'on'

Select the category of data to specify.

  • Inherit — Inheritance rules for data types. Selecting Inherit enables a second menu/text box to the right where you can select the inheritance mode.

  • Built in — Built-in data types. Selecting Built in enables a second menu/text box to the right where you can select a built-in data type.

  • Fixed point — Fixed-point data types. Selecting Fixed point enables additional parameters that you can use to specify a fixed-point data type.

  • Expression — Expressions that evaluate to data types. Selecting Expression enables a second menu/text box to the right, where you can enter the expression.

For more information, see Specify Data Types Using Data Type Assistant.

Dependencies

To enable this parameter, click the Show data type assistant button.

Select the data type override mode for this signal.

  • When you select Inherit, Simulink inherits the data type override setting from its context, that is, from the block, Simulink.Signal object or Stateflow® chart in Simulink that is using the signal.

  • When you select Off, Simulink ignores the data type override setting of its context and uses the fixed-point data type specified for the signal.

For more information, see Specify Data Types Using Data Type Assistant in the Simulink documentation.

Dependencies

To enable this parameter, set Mode to Built in or Fixed point.

Tips

The ability to turn off data type override for an individual data type provides greater control over the data types in your model when you apply data type override. For example, you can use this option to ensure that data types meet the requirements of downstream blocks regardless of the data type override setting.

Specify whether you want the fixed-point data as signed or unsigned. Signed data can represent positive and negative values, but unsigned data represents positive values only. For more information, see Specifying a Fixed-Point Data Type.

Dependencies

To enable this parameter, set Mode to Fixed point.

Specify the bit size of the word that holds the quantized integer. For more information, see Specifying a Fixed-Point Data Type.

Dependencies

To enable this parameter, set Mode to Fixed point.

Specify the method for scaling your fixed-point data to avoid overflow conditions and minimize quantization errors. For more information, see Specifying a Fixed-Point Data Type.

Dependencies

To enable this parameter, set Mode to Fixed point.

Specify fraction length for fixed-point data type as a positive or negative integer. For more information, see Specifying a Fixed-Point Data Type.

Dependencies

To enable this parameter, set Scaling to Binary point.

Specify slope for the fixed-point data type. For more information, see Specifying a Fixed-Point Data Type.

Dependencies

To enable this parameter, set Scaling to Slope and bias.

Specify bias for the fixed-point data type as any real number. For more information, see Specifying a Fixed-Point Data Type.

Dependencies

To enable this parameter, set Scaling to Slope and bias.

State Attributes

Use this parameter to assign a unique name to the block state. The default is ' '. When this field is blank, no name is assigned. When using this parameter, remember these considerations:

  • A valid identifier starts with an alphabetic or underscore character, followed by alphanumeric or underscore characters.

  • The state name applies only to the selected block.

For more information, see C Data Code Interface Configuration for Model Interface Elements (Simulink Coder).

Dependencies

When you specify a value for State name and click Apply, you enable the State name must resolve to Simulink signal object parameter.

Programmatic Use

Parameter: StateName
Type: character vector
Values: unique name
Default: ''

Specify whether state names are required to resolve to signal objects. If selected, the software generates an error at run time if you specify a state name that does not match the name of a signal object.

Selecting this parameter disables the Code generation storage class parameter.

Dependencies

Enabled when you specify a value for the State name parameter and set the Signal resolution model configuration parameter to a value other than None.

Programmatic Use

Block Parameter: StateMustResolveToSignalObject
Type: character vector
Values: 'off' | 'on'
Default: 'off'

Block Characteristics

Data Types

double | fixed point | integer | single

Direct Feedthrough

yes

Multidimensional Signals

no

Variable-Size Signals

no

Zero-Crossing Detection

no

More About

expand all

Extended Capabilities

PLC Code Generation
Generate Structured Text code using Simulink® PLC Coder™.

Fixed-Point Conversion
Design and simulate fixed-point systems using Fixed-Point Designer™.

Version History

Introduced before R2006a

See Also

Topics