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Understanding Model Architecture

When evaluating the modeling guidelines for your project, it is important that you understand the architecture of your controller model, such the function/subfunction layers, schedule layer, control flow layer, section layer, and data flow layer.

Hierarchical Structure of a Controller Model

This section provides a high-level overview of the hierarchical structuring in a basic model, using a controller model as an example. This table defines the layer concepts in a hierarchy.

Layer conceptLayer purpose



Function layerBroad functional division
Schedule layerExpression of execution timing (sampling, order)



Sub function layerDetailed function division
Control flow layerDivision according to processing order (input → judgment → output, etc.)
Selection layerDivision (select output with Merge) into a format that switches and activates the active subsystem
Data flow layerLayer that performs one calculation that cannot be divided

When applying layer concepts:

  • Layer concepts shall be assigned to layers and subsystems shall be divided accordingly.

  • When a layer concepts is not needed, it does not need to be allocated to a layer.

  • Multiple layer concepts can be allocated to one layer.

When building hierarchies, division into subsystems for the purpose of saving space within the layer shall be avoided.

Top Layer

Layout methods for the top layer include:

  • Simple control model — Represents both the function layer and schedule layer in the same layer. Here, function is execution unit. For example, a control model has only one sampling cycle and all functions are arranged in execution order

  • Complex control model Type α — The schedule layer is positioned at the top. This method makes integration with the code easy, but functions are divided, and the readability of the model is impaired.

  • Complex control model Type β — Function layers are arranged at the top and schedule layers are positioned below the individual function layers.

The first example shows the top level as a schedule layer with two function layers, one for a low speed subsystems and the second for a high speed subsystem. In the example illustration, the top layer is the function layer with two schedule layers, one for a sensing function subsystem and the second for a control function subsystem.

Function Layers and Sub-Function Layers

When modeling function and sub-function layers:

  • Subsystems shall be divided by function, with the respective subsystems representing one function.

    • One function is not always an execution unit so, for that reason, the respective subsystem is not necessarily an atomic subsystem. In the type β example below, it is more appropriate for a function layer subsystem to be a virtual subsystem. Algebraic loops are created when these change into atomic subsystems.

    • Individual functional units shall be described.

    • When the model includes multiple large functions, consider using model references for each function to partition the model.

The first example shows the top level as a schedule layer with two function layers, one for a low speed subsystems and the second for a high speed subsystem. There is an arrow connecting sub-function "C1" in the low speed subsystems to sub-function "S2" in the high speed subsystems layer. In the second example, the top layer is the function layer with two schedule layers, one for a sensing function subsystem and the second for a control function subsystem. There is a connection arrow between sub-function "C1" in the control function subsystem to sub-function "S2" in the sensing function subsystem.

Schedule Layers

When scheduling layers:

  • System sampling intervals and execution priority shall be set. Use caution when setting multiple sampling intervals. In connected systems with varying sampling intervals, ensure that the system is split for each sampling interval. This minimizes the RAM needed to store previous values in the situation where the processing of signals values differs for fast cycles and slow cycles.

  • Priority ranking shall be set. This is important when designing multiple, independent functions. When possible, computation sequence for all subsystems should be based on subsystem connections.

  • Two different types of priority rankings shall be set, one for different sampling intervals and the other for identical sampling rates.

There are two types of methods that can be used for setting sampling intervals and priority rankings:

  • For subsystems and blocks, set the block parameter sample time and block properties priority.

  • When using conditional subsystems, set independent priority rankings to match the scheduler.

Patterns exist for many different conditions, such as the configuration parameters for custom sampling intervals, atomic subsystem settings, and the use of model references. The use of a specific pattern is closely linked to the code implementation method and varies significantly depending on the status of the project. Models that are typically affected include:

  • Models that have multiple sampling intervals

  • Models that have multiple independent functions

  • Usage of model references

  • Number of models (and whether there is more than one set of generated code)

For the generated code, affected factors include:

  • Applicability of a real-time operating system

  • Consistency of usable sampling intervals and computation cycles to be implemented

  • Applicable area (application domain or basic software)

  • Source code type: AUTOSAR compliant - not compliant - not supported.

Control Flow Layers

In the hierarchy, the control layer expresses all input processing, intermediate processing, and output processing by using one function. The arrangement of blocks and subsystems is important in this layer. Multiple, mixed small functions should be grouped by dividing them between the three largest stages of input processing, intermediate processing and output processing, which forms the conceptual basis of control. The general configuration occurs close to the data flow layer and is represented in the horizontal line. The difference in a data flow layer is its construction from multiple subsystems and blocks.

In control flow layers, the horizontal direction indicates processing with different significance; blocks with the same significance are arranged vertically.

Illustrates three control flow layers column that are arranged from left to right. The first column is labeled Input Processing, the middle is labeled Intermediate Processing, the and last column is labeled Output Processing. The blocks in the control flow layer column have the same significance with regard to function of the vertical column.

Block groups are arranged horizontally and are given a provisional meaning. Red borders, which signify the delimiter for processing that is not visible, correspond to objects called virtual objects. Using annotations to mark the delimiters makes it easier to understand.

Illustrates the Input Processing, Intermediate Processing,and Output Processing control flow columns that are presented horizontally from left to right. The blocks in each control flow layer column have the same significance with regard to function of the column. Red borders are used to mark the delimiter for processing that is not visible.

Control flow layers can co-exist with blocks that have a function. They are positioned between the sub-function layer and the data flow layer. Control flow layers are used when:

  • The number of blocks becomes too large

  • All is described in the data flow layer

  • Units that can be given a minimum partial meaning are made into subsystems

Placement in the hierarchy organizes the internal layer configuration and makes it easier to understand. It also improves maintainability by avoiding the creation of unnecessary layers.

When the model consists solely of blocks and does not include a mix of subsystems, if the horizontal layout can be split into input/intermediate/output processing, it is considered a control flow layer.

Selection Layers

When modeling selection layers:

  • Selection layers should be written vertically or side-by-side. There is no significance to which orientation is chosen.

  • Selection layers shall mix with control flow layers.

When a subsystem has switch functions that allow only one subsystem to run depending on the conditional control flow inside the red border, it is referred to as a selection layer. It is also described as a control flow layer because it structures input processing/intermediate processing (conditional control flow)/output processing.

In the control flow layer, the horizontal direction indicates processing with different significance. Parallel processing with the same significance is structured vertically. In selection layers, no significance is attached to the horizontal or vertical direction, but they show layers where only one subsystem can run. For example:

  • Switching coupled functions to run upwards or downwards, changing chronological order

  • Switching the setting where the computation type switches after the first time (immediately after reset) and the second time

  • Switching between destination A and destination B

Illustrates the Input Processing, Intermediate Processing,and Output Processing control flow columns that are presented horizontally from left to right. The blocks in each control flow layer column have the same significance with regard to function of the column. Blue borders are used to mark the selection layers that are grouped to flow horizontally across multiple control flow columns.

Data Flow Layers

A data flow layer is the layer below the control flow layer and selection layer.

A data flow layer represents one function as a whole; input processing, intermediate processing and output processing are not divided. For instance, systems that perform one continuous computation that cannot be split.

Data flow layers cannot coexist with subsystems apart from those where exclusion conditions apply. Exclusion conditions include:

  • Subsystems where reusable functions are set

  • Masked subsystems that are registered in the Simulink® standard library

  • Masked subsystems that are registered in a library by the user

Example of a simple data flow layer.

Basic model that illustrates the left-to-right flow of data between blocks.

Example of a complex data flow layer.

Complex model that illustrates the left-to-right flow of data between blocks.

When input processing and intermediate processing cannot be clearly divided as described above, they are represented as a data flow layer.

A data flow layer becomes complicated when both the feed forward reply and feedback reply from the same signal are computed at the same time. Even when the number of blocks in this type of cases is large, the creation of a subsystem should not be included in the design when the functions cannot be clearly divided. When meaning is attached through division, it should be designed as a control flow layer.

Relationship between Simulink Models and Embedded Implementation

Running an actual micro controller requires embedding the code that is generated from the Simulink model into the micro controller. This requirement affects the configuration Simulink model and is dependent on:

  • The extent to which the Simulink model will model the functions

  • How the generated code is embedded

  • The schedule settings on the embedded micro controller

The configuration is affected significantly when the tasks of the embedded micro controller differs from those modeled by Simulink.

Scheduler Settings in Embedded Software

The scheduler in embedded software has single-task and multi-task settings.

Single-task schedule settings

A single-task scheduler performs all processing by using basic sampling. Therefore, when processing of longer sampling is needed, the function is split so the CPU load is as evenly distributed as possible, and then processed using basic sampling. However, as equal splitting is not always possible, functions may not be able to be allocated to all cycles.

For example, basic sampling is 2 millisecond, and sampling rates of 2 millisecond, 8 millisecond and 10 millisecond exist within the model. An 8 millisecond function is executed once for every four 2 millisecond cycles, and a 10 millisecond function is executed once for every five. The number of executions is counted every 2 millisecond and the sampling function specified by this frequency is executed. Attention needs to be paid to the fact that the 2 millisecond, 8 millisecond and 10 millisecond cycles are all computed with the same 2 millisecond. Because all computations need to be completed within 2 millisecond, the 8 millisecond and 10 millisecond functions are split into several and adjusted so that all 2 millisecond computations are of an almost equal volume.

The following diagram shows the 8 millisecond function split into 4 and the 10 millisecond function split into 5.

FunctionsFundamental frequencyOffset

Illustrates the splitting of the function. The 8 millisecond function is executed once for every four 2-millisecond cycles. The 10 millisecond function is executed once for every five 2-millisecond cycles.

To set frequency-divided tasking:

  1. Set configuration parameter Tasking mode for periodic sample times to SingleTasking for Simulink task setting.

    Screen capture of the "Tasking mode for periodic sample times" configuration parameter.

  2. In the Atomic Subsystem block parameter Sample time, enter the sampling period offset values. A subsystem for which a sampling period can be specified is referred to as an atomic subsystem.

    Screen capture of the "Sample time" block parameter.

    Multi-task scheduler settings

    Multi-task sampling is executed by using a real-time OS that supports multi-task sampling. In single-task sampling, equalizing the CPU load is not done automatically, but a person divides the functions and allocates them to the appointed task. In multi-task sampling, the CPU performs the computations automatically in line with the current status; there is no need to set detailed settings. Computations are performed and results are output starting from the task with the highest priority, but the task priorities are user-specified. Typically, fast tasks are assigned highest priority. The execution order for this task is user-specified.

    CPU processing of 2, 8, and 10 millisecond functions.

    It is important that computations are completed within the cycle, including slow tasks. When the processing of a high priority computation finishes and the CPU is available, the computation for the system with the next priority ranking begins. A high priority computation process can interrupt a low priority computation, which is then aborted so the high priority computation process can execute first.

Effect of Connecting Subsystems with Sampling Differences

If subsystem B with a 20 millisecond sampling interval uses the output of subsystem A with a 10 millisecond sampling interval, the output result of subsystem A can change while subsystem B is computing. If the values change partway through, the results of subsystem B’s computation may not be as expected. For example, a comparison is made in subsystem B’s first computation with the subsystem A output, and the result is computed with the conditional judgment based on this output. At this point, the comparison result is true. It is then compared again at the end of subsystem B; if the output from A is different, then the result of the comparison can be false. Generally, in this type of function development it may happen that the logic created with true, true has become true, false, and an unexpected computation result is generated. To avoid this type of malfunction, when there is a change in task, output results from subsystem A are fixed immediately before they are used by subsystem B as they are used in a different RAM from that used by the subsystem A output signals. In other words, even if subsystem A values change during the process, the values that subsystem B are looking at is in a different RAM, so no effect is apparent.

When a model is created in Simulink and a subsystem is connected that has a different sampling interval in Simulink, Simulink automatically reserves the required RAM.

However, if input values are obtained with a different sampling interval through integration with hand-coded code, the engineer who does the embedding work should design these settings. For example, in the RTW concept using AUTOSAR, different RAMs are all defined at the receiving and exporting side.

CPU processing of 2, 8, and 10 millisecond functions. If Function 2 uses computation results of Function 1, computation results for Function 1 do not change during computation for Functions 2-1, 2-2, 2-3, but there is a possibility that Functions 2-1, 2-2, 2-3 use different values that have been computed on the respective different time axes. Different RAM should be allocated for signal values with different rates.

Single-task scheduler settings

Signal values are the same within the same 2 millisecond cycle, but when there are different 2 millisecond cycles, the computation value differs from the preceding one. When Function 2-1 and 2-2 uses signal A of Function 1, be aware that 2-1 and 2-2 uses results from different times.

Multi-task scheduler settings

For multi-task, you cannot specify at what point to use the computation result to use. With multi-task, always store signals for different tasks in new RAM.

Before new computations are performed within the task, all values are copied.

CPU processing of 2, 8, and 10 millisecond functions. If Function 2 uses computation results of Function 1, it is possible that computation results from Function 1 will replace them while Function 2 is computing. For that reason, computation results that vary at the point when computation starts for each sampling are generally stored in a different RAM.