Perform discrete-time integration or accumulation of signal (2024)

Perform discrete-time integration or accumulation of signal

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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-TimeIntegrator block, you can:

Define initial conditions on the block dialog box or as input to theblock
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 outputy(0) = IC or initial state x(0) = IC,depending on the Initial condition setting parametervalue.

For a given step n > 0 with simulation timet(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 outputequations depending on the block sample time, which can be explicit or triggered.When using explicit sample time, t(n)-t(n-1) reduces to thesample time T for all n > 0.

Integration and Accumulation Methods

This block can integrate or accumulate a signal using a forward Euler, backward Euler, ortrapezoidal method. Assume that u is the input,y is the output, and x is the state. For agiven step n, Simulink updates y(n) and x(n+1). Inintegration mode, T is the block sample time (deltaT in the case of triggered sample time). In accumulationmode, T = 1. The block sample time determines when the output iscomputed but not the output value. K is the gain value. Valuesclip according to upper or lower limits.

Forward Euler Method

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

The software approximates 1/s asT/(z-1). The expressions for the output of the block at stepn 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-handapproximation

The software approximates 1/s asT*z/(z-1). The resulting expression for the output of theblock 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 computethe output.

If the parameter Initial condition setting is setto Output or Autofor triggered and function-call subsystems:
```
Step 0: y(0) = IC (clipped if necessary) x(1) = y(0)
```

If the parameter Initial condition setting is setto 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 asT/2*(z+1)/(z-1).

When T is fixed (equal to the sampling period), theexpressions 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 setto Output or Autofor 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 setto 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 isnot the same as the state, in that x(n) is not equal toy(n).

Using this method, input port 1 has direct feedthrough.

When T is a Variable

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

If the parameter Initial condition setting is setto Output or Autofor triggered and function-call subsystems:
```
Step 0: y(0) = IC (clipped if necessary) x(1) = y(0)
```

If the parameter Initial condition setting is setto 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 orinput them from an external signal:

To define the initial conditions as a block parameter, set theInitial condition source parameter tointernal and enter the value in the Initialcondition text box.
To provide the initial conditions from an external source, set theInitial condition source parameter toexternal. An additional input port appears on theblock.

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 resetport or the initial condition port, causing an algebraic loop. For anexample, see the sldemo_bounce_two_integratorsmodel.
When you want to pass the state from one conditionally executed subsystemto 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 portrather 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 theShow state port check box. The state port appears on thetop of the block.

Limit the Integral

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

Integral	Output
Less than the Lower saturation limit	Held at the Lower saturation limit
Between the Lower saturation limit and the Uppersaturation limit	The integral
Greater than the Upper saturation limit	Held at the Upper saturation limit

To generate a signal that indicates when the integral reaches limit, select theShow saturation port check box. A new saturation portappears 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 anexternal signal. To cause the block to reset its state, select one of theExternal reset parameter options. A reset port appears thatindicates the reset trigger type.

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

Reset Trigger Types

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

rising – Resets the state when the reset signalhas a rising edge. For example, this figure shows the effect that a risingreset trigger has on backward Euler integration.
falling — Resets the state when the resetsignal has a falling edge. For example, this figure shows the effect that afalling reset trigger has on backward Euler integration.
either — Resets the state when the reset signalrises or falls. For example, the following figure shows the effect that aneither reset trigger has on backward Euler integration.
level — Resets and holds the output to theinitial condition while the reset signal is nonzero. For example, thisfigure shows the effect that a level reset trigger has on backward Euler integration.
sampled level — Resets the output to theinitial condition when the reset signal is nonzero. For example, this figureshows the effect that a sampled level reset trigger has on backward Euler integration.
The sampled level reset option requires fewercomputations, making it more efficient than thelevel reset option.
Note
For the Discrete-Time Integrator block, all triggerdetections are based on signals with positive values. For example, asignal changing from -1 to 0 is not considered a rising edge, but asignal changing from 0 to 1 is.

Behavior in Simplified Initialization Mode

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

In algebraic loops
On enable and disable
When comparing results using triggered sample time against explicit sampletime, where the block is triggered at the same rate as the explicit sampletime

Simplified initialization mode enables easier conversion fromContinuous-Time Integrator blocks to Discrete-TimeIntegrator blocks, because the initial conditions have the same meaningfor both blocks.

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

Enable and Disable Behavior with Initial Condition Setting set toOutput

When you use simplified initialization mode with Initial conditionsetting set to Output for triggeredand function-call subsystems, the enable and disable behavior of the block issimplified as follows.

At disable time t_d:

 y(t_d) = y(t_d-1)

At enable time t_e:

If the parent subsystem control port has States whenenabling set to reset:
```
y(t_e) = IC.
```
If the parent subsystem control port has States whenenabling set to held:
```
y(t_e) = y(t_d).
```
The following figure shows this condition.

Iterator Subsystems

When using simplified initialization mode, you cannot place theDiscrete-Time Integrator block in an iterator subsystemblock.

In simplified initialization mode, Iterator subsystems do not maintain elapsedtime. Thus, if a Discrete-Time Integrator block, which needselapsed 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 behaviorapplies.

Integrator Method	Sample Time Type of Function-Call TriggerPort	Value of `delta T` WhenFunction-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 firsttime, the integrator algorithm uses `tstart` asthe previous simulation time.
Backward Euler and Trapezoidal	Triggered	`t — tprevious`	When the function-call subsystem executes for the firsttime, the integrator algorithm uses `tprevious`as the previous simulation time.
Forward Euler, Backward Euler, andTrapezoidal	Periodic	Sample time of the function-call generator	In periodic mode, the Discrete-TimeIntegrator block uses sample time of thefunction-call generator for `deltaT`.

Examples

Discrete-Time Integration Using the Forward Euler Integration MethodThe model sldemo_fuelsysuses a Discrete-TimeIntegrator block in the subsystemfuel_rate_control/airflow_calc.

Open Model

Building a Clutch Lock-Up ModelUse 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.

Open Model

Simulation of Bouncing BallUses 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.

Open Model

Ports

Input

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Port_1 — Input signal
scalar | vector | matrix

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

IC — Initial conditions of the states
scalar | vector | matrix

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

Dependencies

To enable this port, set Initial conditionsource to external.

Output

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Port_1 — Discrete-time integration or accumulation of input
scalar | vector | matrix

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

Port_2 — Saturation output
scalar | vector | matrix

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

1 indicates that the upper limit is beingapplied.
0 indicates that the integral is notlimited.
-1 indicates that the lower limit is beingapplied.

Dependencies

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

Data Types: single | double | int8

Port_3 — State output
scalar | vector | matrix

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

The output of the block is fed back into the block through thereset port or the initial condition port, causing an algebraicloop. For an example, see thesldemo_bounce_two_integratorsmodel.
You want to pass the state from one conditionally executedsubsystem to another, which can cause timing problems. For anexample, see the sldemo_clutch model.

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

Dependencies

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

Parameters

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Main

Integrator method — Accumulation method
`Integration: ForwardEuler` (default) | `Integration: Backward Euler` | `Integration: Trapezoidal` | `Accumulation: Forward Euler` | `Accumulation: Backward Euler` | `Accumulation: Trapezoidal`

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

Default:'Integration: Forward Euler'

Gain value — Value to multiply with integrator input
`1.0` (default) | scalar | vector

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

Specifying a value other than 1.0 (the default) issemantically equivalent to connecting a Gain block to the inputof 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 amultiplication operation in the generated code. However, thisparameter must be nontunable to realize this benefit. If you want totune the input gain, set this parameter to 1.0 and use an externalGain block to specify the input gain.

Programmatic Use

Block Parameter:gainval

Type: character vector

Values: scalar | vector

Default:'1.0'

External reset — Select when to reset states to initial conditions
`none` (default) | `rising` | `falling` | `either` | `level` | `sampled level`

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

none — Do not reset the state toinitial conditions.
rising — Reset the state when thereset signal has a rising edge.
falling — Reset the state when thereset signal has a falling edge.
either — Reset the state when thereset signal rises or falls.
level — Reset and hold the outputto the initial condition while the reset signal isnonzero.
sampled level — Reset the output tothe 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

Default:'none'

Initial condition source — Option to set initial condition using external signal
`internal` (default) | `external`

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'

Initial condition — Initial condition of states
`0` (default) | scalar | vector | matrix

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'

Initial condition setting — Select where to apply the initial condition
`Auto` (default) | `Output` | `Compatibility`

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

Auto — Block chooses where to applythe Initial condition parameter.
- If the block is in a non-triggered subsystem andIntegrator method is set to anintegration method, set initial conditions:
  x(0) = IC
  At reset:
  x(n) = IC
- If the block is in a triggered or function-callsubsystem and Integrator method isset to an integration method, set initial conditions asif output wasselected.
  See Also
  Handle transfer of data between blocks operating at different rates
Output — Use this option when theblock is in a triggered or a function-call subsystem andIntegrator method is set to anintegration method.
Set initial conditions:
y(0) = IC
At reset:
y(n) = IC
Compatibility — This option ispresent to provide backward compatibility. You cannot selectthis option for Discrete-Time Integrator blocksin Simulink models but you can select it forDiscrete-Time Integrator blocks in a library.Use this option to maintain compatibility with Simulink modelscreated before R2014a.
Prior to R2014a, the option Autowas known as State only (mostefficient). The optionOutput was known asState and output. The behavior ofthe block with the optionCompatibility is as follows.
- If Underspecified initializationdetection is set toClassic, theInitial condition settingparameter behaves asAuto.
- If Underspecified initializationdetection is set toSimplified, theInitial condition settingparameter behaves asOutput.

Note

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

Programmatic Use

Block Parameter: InitialConditionSetting

Type: character vector

Value: 'Auto' | 'Output' |'Compatibility'

Default: 'Auto'

Sample time (-1 for inherited) — Interval between samples
`-1` (default) | scalar | vector

Enter the discrete time interval between steps.

By default, the block uses a discrete sample time of1. To set a different sample time, enter anotherdiscrete value, such as 0.1.

See Specify Sample Timefor more information.

Tips

Do not specify a sample time of 0. This value specifies acontinuous sample time, which the Discrete-Time Integratorblock does not support.
Do not specify a sample time of inf orNaN because these values are notdiscrete.
If you specify -1 to inherit the sample time from anupstream block, verify that the upstream block uses adiscrete sample time. For example, the Discrete-TimeIntegrator block cannot inherit a sample time of 0.

Programmatic Use

Block Parameter: SampleTime

Type: character vector

Values: scalar | vector

Default: '-1'

Limit output — Limit block output values to specified range
`off` (default) | `on`

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.

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

Output minimum — Minimum output value for range checking
`[]` (default) | scalar

Lower value of the output range that Simulink checks.

Simulink uses the minimum to perform:

Parameter range checking (see Specify Minimum and Maximum Values for Block Parameters) for some blocks.
Simulation range checking (see Specify Signal Ranges and Enable Simulation Range Checking).
Automatic scaling of fixed-point data types.
Optimization of the code that you generate from the model. This optimization can remove algorithmic code and affect the results of some simulation modes such as SIL or external mode. For more information, see Optimize using the specified minimum and maximum values (Embedded Coder).

Note

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

Programmatic Use

Block Parameter: OutMin

Type: character vector

Values: '[ ]'| scalar

Default: '[ ]'

Output maximum — Maximum output value for range checking
`[]` (default) | scalar

Upper value of the output range that Simulink checks.

Simulink uses the maximum value to perform:

Parameter range checking (see Specify Minimum and Maximum Values for Block Parameters) for some blocks.
Simulation range checking (see Specify Signal Ranges and Enable Simulation Range Checking).
Automatic scaling of fixed-point data types.
Optimization of the code that you generate from the model. This optimization can remove algorithmic code and affect the results of some simulation modes such as SIL or external mode. For more information, see Optimize using the specified minimum and maximum values (Embedded Coder).

Note

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

Programmatic Use

Block Parameter: OutMax

Type: character vector

Values: '[ ]'| scalar

Default: '[ ]'

Data type — Output data type
`Inherit: Inherit via internal rule` (default) | `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>`

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

Default: 'Inherit: Inherit via internal rule'

Lock output data type setting against changes by the fixed-point tools — Option to prevent fixed-point tools from overriding Output data type
`off` (default) | `on`

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

Block Parameter: LockScale

Type: character vector

Values: 'off' | 'on'

Default: 'off'

Integer rounding mode — Specify the rounding mode for fixed-point operations
`Floor` (default) | `Ceiling` | `Convergent` | `Nearest` | `Round` | `Simplest` | `Zero`

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

Default: 'Floor'

Saturate on integer overflow — Method of overflow action
`off` (default) | `on`

Specify whether overflows saturate or wrap.

off — Overflows wrap to the appropriate value that the data type can represent.
For example, the number 130 does not fit in a signed 8-bit integer and wraps to -126.
on — Overflows saturate to either the minimum or maximum value that the data type can represent.
For example, an overflow associated with a signed 8-bit integer can saturate to -128 or 127.

Tip

Consider selecting this check box when your model has a possible overflow and you want explicit saturation protection in the generated code.
Consider clearing this check box when you want to optimize efficiency of your generated code.
Clearing this check box 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 check box, 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

Block Parameter: SaturateOnIntegerOverflow

Type: character vector

Values: 'off' | 'on'

Default: 'off'

Mode — Select data type mode
`Inherit` (default) | `Built in` | `Fixed Point`

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.

Data type override — Specify data type override mode for this signal
`Inherit` | `Off`

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.

State name — Unique name for block state
`''` (default) | alphanumeric string

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: ''

State name must resolve to Simulink signal object — Option to require that state names resolve to signal object
`off` (default) | `on`

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`

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

Depends on absolute time when used inside a triggered subsystem hierarchy.

HDL Code Generation
Generate VHDL, Verilog and SystemVerilog code for FPGA and ASIC designs using HDL Coder™.

HDL Coder™ provides additional configuration options that affect HDLimplementation and synthesized logic.

HDL Architecture

This block has one default HDL architecture.

HDL Block Properties

General
ConstrainedOutputPipeline	Number of registers to place at the outputs by moving existing delays within your design. Distributed pipelining does not redistribute these registers. The default is `0`. For more details, see ConstrainedOutputPipeline (HDL Coder).
InputPipeline	Number of input pipeline stages to insert in the generated code. Distributed pipelining and constrained output pipelining can move these registers. The default is `0`. For more details, see InputPipeline (HDL Coder).
OutputPipeline	Number of output pipeline stages to insert in the generated code. Distributed pipelining and constrained output pipelining can move these registers. The default is `0`. For more details, see OutputPipeline (HDL Coder).

Native Floating Point
HandleDenormals	Specify whether you want HDL Coder to insert additional logic to handle denormal numbers in your design. Denormal numbers are numbers that have magnitudes less than the smallest floating-point number that can be represented without leading zeros in the mantissa. The default is `inherit`. See also HandleDenormals (HDL Coder).
LatencyStrategy	Specify whether to map the blocks in your design to `inherit`, `Max`, `Min`, or `Zero` for the floating-point operator. The default is `inherit`. See also LatencyStrategy (HDL Coder).
MantissaMultiplyStrategy	Specify how to implement the mantissa multiplication operation during code generation. By using different settings, you can control the DSP usage on the target FPGA device. The default is `inherit`. See also MantissaMultiplyStrategy (HDL Coder).

Restrictions

State ports are not supported for HDL code generation. Clear theShow state port option.
External initial conditions are not supported for HDL code generation.Set Initial condition source toInternal.
External Reset must be set tonone, rising,falling or level.
Continuous sample time is not supported. Use a discrete sample timefor the block.

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

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Perform discrete-time integration or accumulation of signal (2024)

Description

Output Equations

Integration and Accumulation Methods

Define Initial Conditions

When to Use the State Port

Limit the Integral

Reset the State

Reset Trigger Types

Behavior in Simplified Initialization Mode

Behavior in an Enabled Subsystem Inside a Function-Call Subsystem

Examples

Ports

Input

Port_1 — Input signalscalar | vector | matrix

IC — Initial conditions of the states scalar | vector | matrix

Dependencies

Output

Port_1 — Discrete-time integration or accumulation of inputscalar | vector | matrix

Port_2 — Saturation output scalar | vector | matrix

Dependencies

Port_3 — State output scalar | vector | matrix

Dependencies

Parameters

Main

Integrator method — Accumulation methodIntegration: ForwardEuler (default) | Integration: Backward Euler | Integration: Trapezoidal | Accumulation: Forward Euler | Accumulation: Backward Euler | Accumulation: Trapezoidal

Programmatic Use

Gain value — Value to multiply with integrator input 1.0 (default) | scalar | vector

Programmatic Use

External reset — Select when to reset states to initial conditions none (default) | rising | falling | either | level | sampled level

Programmatic Use

Initial condition source — Option to set initial condition using external signal internal (default) | external

Programmatic Use

Initial condition — Initial condition of states 0 (default) | scalar | vector | matrix

Dependencies

Programmatic Use

Initial condition setting — Select where to apply the initial condition Auto (default) | Output | Compatibility

Programmatic Use

Sample time (-1 for inherited) — Interval between samples -1 (default) | scalar | vector

Tips

Programmatic Use

Limit output — Limit block output values to specified range off (default) | on

Dependencies

Programmatic Use

Upper saturation limit — Upper limit for the integralinf (default) | scalar | vector | matrix

Dependencies

Programmatic Use

Lower saturation limit — Lower limit for the integral -inf (default) | scalar | vector | matrix

Dependencies

Programmatic Use

Show saturation port — Enable saturation output port off (default) | on

Dependencies

Programmatic Use

Show state port — Enable state output port off (default) | on

Dependencies

Programmatic Use

Ignore limit and reset when linearizing — Treat block as not resettable off (default) | on

Programmatic Use

Signal Attributes

Output minimum — Minimum output value for range checking[] (default) | scalar

Programmatic Use

Output maximum — Maximum output value for range checking [] (default) | scalar

Programmatic Use

Data type — Output data type Inherit: Inherit via internal rule (default) | 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>

Programmatic Use

Lock output data type setting against changes by the fixed-point tools — Option to prevent fixed-point tools from overriding Output data type off (default) | on

Programmatic Use

Integer rounding mode — Specify the rounding mode for fixed-point operations Floor (default) | Ceiling | Convergent | Nearest | Round | Simplest | Zero

Programmatic Use

See Also

Saturate on integer overflow — Method of overflow action off (default) | on

Programmatic Use

Mode — Select data type modeInherit (default) | Built in | Fixed Point

Dependencies

Data type override — Specify data type override mode for this signal Inherit | Off

Dependencies

Tips

Signedness — Signedness of fixed-point data Signed (default) | Unsigned

Dependencies

Word length — Bit size of the word that holds the quantized integer 16 (default) | integer from 0 to 32

Port_1 — Input signal
scalar | vector | matrix

IC — Initial conditions of the states
scalar | vector | matrix

Port_1 — Discrete-time integration or accumulation of input
scalar | vector | matrix

Port_2 — Saturation output
scalar | vector | matrix

Port_3 — State output
scalar | vector | matrix

Integrator method — Accumulation method
`Integration: ForwardEuler` (default) | `Integration: Backward Euler` | `Integration: Trapezoidal` | `Accumulation: Forward Euler` | `Accumulation: Backward Euler` | `Accumulation: Trapezoidal`

Gain value — Value to multiply with integrator input
`1.0` (default) | scalar | vector

External reset — Select when to reset states to initial conditions
`none` (default) | `rising` | `falling` | `either` | `level` | `sampled level`

Initial condition source — Option to set initial condition using external signal
`internal` (default) | `external`

Initial condition — Initial condition of states
`0` (default) | scalar | vector | matrix

Initial condition setting — Select where to apply the initial condition
`Auto` (default) | `Output` | `Compatibility`

Sample time (-1 for inherited) — Interval between samples
`-1` (default) | scalar | vector

Limit output — Limit block output values to specified range
`off` (default) | `on`

Upper saturation limit — Upper limit for the integral
`inf` (default) | scalar | vector | matrix

Lower saturation limit — Lower limit for the integral
`-inf` (default) | scalar | vector | matrix

Show saturation port — Enable saturation output port
`off` (default) | `on`

Show state port — Enable state output port
`off` (default) | `on`

Ignore limit and reset when linearizing — Treat block as not resettable
`off` (default) | `on`

Output minimum — Minimum output value for range checking
`[]` (default) | scalar

Output maximum — Maximum output value for range checking
`[]` (default) | scalar

Lock output data type setting against changes by the fixed-point tools — Option to prevent fixed-point tools from overriding Output data type
`off` (default) | `on`

Integer rounding mode — Specify the rounding mode for fixed-point operations
`Floor` (default) | `Ceiling` | `Convergent` | `Nearest` | `Round` | `Simplest` | `Zero`

Saturate on integer overflow — Method of overflow action
`off` (default) | `on`

Mode — Select data type mode
`Inherit` (default) | `Built in` | `Fixed Point`

Data type override — Specify data type override mode for this signal
`Inherit` | `Off`

Signedness — Signedness of fixed-point data
`Signed` (default) | `Unsigned`

Word length — Bit size of the word that holds the quantized integer
`16` (default) | integer from 0 to 32

Scaling — Method for scaling fixed-point data
`Best precision` (default) | `Binary point` | `Slope and bias`

Fraction length — Specify fraction length for fixed-point data type
`0` (default) | scalar integer

Slope — Specify slope for the fixed-point data type
`2^0` (default) | positive, real-valued scalar

Bias — Specify bias for the fixed-point data type
`0` (default) | real-valued scalar

State name — Unique name for block state
`''` (default) | alphanumeric string

State name must resolve to Simulink signal object — Option to require that state names resolve to signal object
`off` (default) | `on`

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

HDL Code Generation
Generate VHDL, Verilog and SystemVerilog code for FPGA and ASIC designs using HDL Coder™.

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

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