Glossary

Accelerator Simulation Mode

Simulink executes an Accelerator mode submodel by creating a MEX-file (or simulation target) for the submodel, then running the MEX-file. The Accelerator mode generates and links code into a C-MEX S-function. Simulink uses this acceleration target code to perform the simulation, and the code remains available for use in later simulations. In Accelerator mode, the model methods are separate from the Simulink software and are part of the Acceleration target code. A C-MEX S-function API communicates with the Simulink software, and a MEX API communicates with MATLAB. The target code executes in the same process as MATLAB and Simulink.

Algebraic Loop

An algebraic loop in a Simulink model occurs when a signal loop exists with only direct feedthrough blocks within the loop. Direct feedthrough means that the block output depends on the value of an input port; the value of the input directly controls the value of the output. Non-direct-feedthrough blocks maintain a State variable. Two examples are the Integrator or Unit Delay block. When some Simulink blocks have input ports with direct feedthrough, the software cannot compute the output of these blocks without knowing the values of the signals entering the blocks at these input ports at the current time step. In Simulink models, algebraic loops are algebraic constraints. Models with algebraic loops define a system of differential algebraic equations. Simulink does not solve DAEs directly. Simulink solves the algebraic equations (the algebraic loop) numerically for xa at each step of the ODE solver.

Black-box

A black-box model is a model whose inputs, outputs, and functional performance are known, but whose internal implementation is unknown or irrelevant. Contrast with: glass box model, white box model. An "Simcenter Amesim-Simulink Black-Box (ASBB)" is a Simulink license-free S-function.

Block Diagram

A classic block diagram model of a dynamic system graphically consists of blocks and lines (signals). The history of these block diagram models is derived from engineering areas such as Feedback Control Theory and Signal Processing. The relationship between signals and state variables are defined by a set of equations represented by blocks. Each block consists of a set of equations (block methods). These equations define a relationship between the input signals, output signals and the state variables. Inherent in the definition of an equation is the notion of parameters, which are the coefficients found within the equation.

Block Libraries

A block library is a collection of blocks that serve as prototypes for instances of blocks in a Simulink® model.

Block Parameters

Key properties of many standard blocks are parameterized with block parameters. For example, the Constant value of the Simulink Constant block is a parameter. Each parameterized block has a block dialog that lets you set the values of the parameters.

Closed Loop

Closed Loop refers to a controlled system using feedback or feedforward. It's also related to a closed-loop transfer function in control theory, which is a mathematical expression (algorithm) describing the net result of the effects of a closed (feedback) loop on the input signal to the circuits enclosed by the loop.

Conditional Subsystem

A conditional subsystem, also known as a conditionally executed subsystem, is a subsystem whose execution depends on the value of an input signal. The signal that controls whether a subsystem executes is called the control signal. The signal enters a subsystem block at the control input.

Configurable Subsystem

Configurable Subsystem blocks simplify creation of models that represent families of designs. It represents any block selected from user-specified library of blocks. The Configurable Subsystem block represents one of a set of blocks contained in a specified library of blocks. The block's context menu lets you choose which block the configurable subsystem represents. To create a configurable subsystem in a model, users must first create a library containing a master configurable subsystem and the blocks that it represents. They can then create configurable instances of the master subsystem by dragging copies of the master subsystem from the library and dropping them into models.

Controller

A controller is a control system that manages the behavior of another device or system. It's a device, possibly in the form of a chip, analogue electronics, or computer, which monitors and physically alters the operating conditions of a given dynamical system. In SiL simulation, it refers to the (embedded) control software that executes with simulated hardware (plant).

Control Logic

Control Logic is a key part of a software program that controls the operations of the program. The control logic responds to commands from the user, and it also acts on its own to perform automated tasks that have been structured into the program. Control logic can be modeled using a state diagram, which is a form of hierarchical state machine. These state diagrams can also be combined with flow charts to provide a set of computational semantics for describing complex control logic.

Control Strategy Design

Control Strategy Design involves developing a control algorithm that effectively manipulates the actuators to meet the needs of the system requirements. The challenge is to achieve the desired system behavior with a limited set of measured variables in the presence of disturbances, measurement noise and part variations.

Control System

A Control System is a device, or a collection of devices that manage the behavior of other devices. Some devices are not controllable. A control system is an interconnection of components connected or related in such a manner as to command, direct, or regulate itself or another system.

Co-simulation

Coupling (i.e., dynamic mutually exchange and utilization of intermediate results) of several simulation programs including their numerical solvers in order to simulate a system consisting of several subsystems. AME2SLCosim and SL2AMECosim interface modes are based on co-simulation between Simcenter Amesim and Simulink.

Demux

Demux extracts and outputs elements of vector signal. The Demux block extracts the components of an input signal and outputs the components as separate signals. The output signals are ordered from top to bottom output port.

Dialog Parameters

Users can pass parameters to an S-function at the start of and during the simulation, using the S-function parameters field of the Block Parameters dialog box. Such parameters are called dialog box parameters to distinguish them from run-time parameters created by the S-function to facilitate code generation. Dialog parameters can be either tunable or non-tunable.

Dialog Variables

The Dialog variables list displays the names of the variables associated with the subsystem's mask parameters.

DLL (Dynamic-Link Library)

DLL is Microsoft's implementation of the shared library concept in the Microsoft Windows and OS/2 operating systems. As with executables, a DLL file can contain code, data, and resources, in any combination. A function contained in a DLL cannot run on its own, it can only run from inside an executable file in which it was previously declared before being called (DLL function call).

ECU

(Electronic Control Unit)

Embedded system that controls one or more electrical subsystems in a vehicle, for instance. In a car, examples for ECU are: Engine Control Unit (ECU), Transmission Control Unit (TCU), Telephone Control Unit (TCU), Human-Machine Interface (HMI).

Enabled Subsystem

It represents a subsystem whose execution is enabled by external input Enabled subsystems are subsystems that execute at each simulation step for which the control signal has a positive value.

Exported Code

Code (most of the time, C Source Code) that can be used for Hardware-in-the-Loop Simulation, Rapid Control Prototyping, Model Integration into other simulation programs (typically Simulink via a S-function) or even accelerated simulation runs.

Feedback

Feedback is considered when the output of the system is passed through some sort of processing unit H, and that result is fed into the plant as an input.

Feedforward

Feedforward is considered when a priori knowledge is used to forecast at least part of the control response.

Fixed-Step Solver

Fixed-step solvers are solvers that use the same step size during the simulation. They provide no error control and do not locate zero crossings but comply with Real-Time constraints.

From

The From block accepts a signal from a corresponding Goto block, then passes it as output. The data type of the output is the same as that of the input from the Goto block. From and Goto blocks allow you to pass a signal from one block to another without actually connecting them. To associate a Goto block with a From block, enter the Goto block's tag in the Goto Tag parameter.

Goto

The Goto block passes its input to its corresponding From blocks. The input can be a real- or complex-valued signal or vector of any data type. From and Goto blocks allow you to pass a signal from one block to another without actually connecting them.

I/O

Input/Output.

Icon Display

Specify the information to be displayed on the icon of this input port. Settings are Signal name: to display the name of the signal connected to this port (or signals if the input is a bus), Port number: to display port number of this port, Port number and signal name: to display both the port number and the names of the signals connected to this port. Default setting is Port number.

Inport

Create input port for subsystem or external input. Inport blocks are the links from outside a system into the system.

Libraries Pane

The Libraries pane allows users to select block libraries for browsing. The pane displays a tree-structured directory (tree view) of libraries installed on your system, each of whose nodes you can select with your mouse or keyboard.

Library Browser

The Library Browser is used to browse and search Simulink block libraries for blocks to use in your models. You can also select from a list of your most frequently used blocks.

Linked Blocks

When users copy a block from a library into a model, Simulink creates a linked block in the model, and connects it to the library block using a library link. The library block is the prototype block, and the linked block in the model is an instance of the library block.

Lookup Table

A lookup table block uses an array of data to map input values to output values, approximating a mathematical function. Given input values, Simulink performs a "lookup" operation to retrieve the corresponding output values from the table. If the lookup table does not define the input values, the block estimates the output values based on nearby table values.

Makefile

Files that contain a collection of commands that allow groups of programs, object files, libraries, etc. to interact. Makefiles are executed by the make utility.

Mask

Masks are custom interfaces users can apply to Simulink blocks. A mask hides the user interface of the block, and instead displays a custom dialog to control specific parameters of the masked block. Users can use the Simulink Mask Editor to define a custom interface for a Subsystem block, Model block, S-Function block, or built-in blocks.

Master

A master is a device that controls one or more other devices. In networking, for example, a master/slave configuration is a communications model in which one device or process (known as the master) controls one or more other devices or processes (known as slaves).

Master/Slave

A method of communication, where one device or process has unidirectional control over one or more other devices. Once a master/slave relationship between devices or processes is established, the direction of control is always from the master to the slaves. In some systems a master is elected from a group of eligible devices, with the other devices acting in the role of slaves.

MathWorks

MathWorks is the leading developer of mathematical computing software. It was founded in 1984. MATLAB®, the language of technical computing, is a programming environment for algorithm development, data analysis, visualization, and numeric computation. Simulink® is a graphical environment for simulation and Model-Based Design of multidomain dynamic and embedded systems.

MathWorks Help / Simulink

Simulink software provides comprehensive online help describing features, blocks, and functions with detailed procedures for common tasks. It's accessible on: Users can access additional Simulink resources on the MathWorks® Web site, including Simulink related books, webinars, and technical support. To access the Simulink product page, go to:

MDL Model File

Models and libraries format when saved. Simulink saves the model by generating a specially formatted file called the model file that contains the block diagram and block properties.

MEX File

MEX stands for "MATLAB executable". Users can call their own C, C++, or Fortran subroutines from the MATLAB® command line as if they were built-in functions. These programs, called binary MEX-files, are dynamically-linked subroutines that the MATLAB interpreter loads and executes. The term mex has different meanings:

• Source MEX-file: C, C++, or Fortran source code file.

• Binary MEX-file: dynamically-linked subroutine executed in the MATLAB environment.

• MEX function library: MATLAB C/C++ and Fortran API Reference library to perform operations in the MATLAB environment.

• Mex build script: MATLAB function to create a binary file from a source file.

MIMO

Multi-Input, Multi-Output (MIMO) models. Users can define for example MIMO Transfer Function Model, MIMO State-Space Model, or MIMO Frequency Response Data Model.

Model Configuration

A model configuration is a named set of values for the parameters of a model. It is referred to as a configuration set. Every new model is created with a default configuration set, called Configuration, that initially specifies default values for the model parameters.

Model Export

The process of exporting a model into a format that can be understood by another tool.

Mux

Mux combines several input signals into vector. The Mux block combines its inputs into a single vector output. An input can be a scalar or vector signal. All inputs must be of the same data type and numeric type. The elements of the vector output signal take their order from the top to bottom, or left to right, input port signals.

Normal Simulation Mode

Simulink executes a Normal mode submodel interpretively. Normal mode executes slower than Accelerator mode does. In Normal mode, the MATLAB technical computing environment is the foundation on which the Simulink software is built. Simulink controls the solver and model methods used during simulation. Model methods include such things as computation of model outputs. Normal mode runs in one process.

Open-loop Controller

An open-loop controller, also called a non-feedback controller, is a type of controller that computes its input into a system using only the current state and its model of the system.

Outport

Outport creates output port for subsystem or external output Outport blocks are the links from a system to a destination outside the system.

Plant Model

A plant in control theory is the combination of process and actuator. Plant modeling can be data-driven or first principles based. Data-driven plant modeling uses techniques such as System identification. With system identification, the plant model is identified by acquiring and processing raw data from a real-world system and choosing a mathematical algorithm with which to identify a mathematical model. Various kinds of analysis and simulations can be performed using the identified model before it is used to design a model-based controller. First principles based modeling is based on creating a block diagram model that implements known differential-algebraic equations governing plant dynamics. A type of first principles based modeling is physical modeling, where a model is created by connecting blocks that represent the physical elements that the actual plant consists of. The plant model is the engine model, vehicle model, airplane model, etc. that is expected by the ECU. Its complexity level depends on the desired application. For developing ECU control capability against the plant model, higher fidelity may be required than for "only" testing the diagnostic capability of the ECU. For instance, to develop a new multi-injection fueling strategy for a diesel engine, the plant model should be capable of accumulating and reacting to all of the fuel pulses.

Port Label

Port Label draws port label on masked subsystem icon.

Rapid Accelerator Simulation Mode

The Rapid Accelerator mode creates a Rapid Accelerator standalone executable from your model. This executable includes the solver and model methods, but it resides outside of MATLAB and Simulink. It uses External mode to communicate with Simulink.

RTW

Real Time Workshop, see Simulink Coder.

Run-time Parameters

Users can create internal representations of external S-function dialog box parameters called run-time parameters. Run-time parameters facilitate the following kinds of S-function operations:

• Computed parameters: often the output of a block is a function of the values of several dialog parameters.

• Data type conversions: often a block needs to change the data type of a dialog parameter to facilitate internal processing.

• Code generation: during code generation, the Simulink Coder product writes all run-time parameters automatically to the model.rtw file.

Sample Time

The sample time of a block is a parameter that indicates when, during simulation, the block produces outputs and if appropriate, updates its internal state. The internal state includes but is not limited to continuous and discrete states that are logged.

Scope

The Scope block displays inputs signals with respect to simulation time.

S-function

S-function (system-function) blocks allow you to write MATLAB, C, C++, or Fortran code to define custom functionality. It's a customized Simulink block written in C or M-code. S-functions can be inlined in the Real-Time Workshop. C, C++, and Fortran S-functions are compiled as MEX files using the mex utility. As with other MEX files, S-functions are dynamically linked subroutines that the MATLAB interpreter can automatically load and execute. S-functions use a special calling syntax called the S-function API that enables users to interact with the Simulink engine. This interaction is very similar to the interaction that takes place between the engine and built-in Simulink blocks. S-functions follow a general form and can accommodate continuous, discrete and hybrid systems.

Simulink

Simulink® is an environment for multi-domain simulation and Model-Based Design for dynamic and embedded systems. It provides an interactive graphical environment and a customizable set of block libraries that let you design, simulate, implement, and test a variety of time-varying systems, including communications, controls, signal processing, video processing, and image processing. Simulink provides a graphical editor, customizable block libraries, and solvers for modeling and simulating dynamic systems. Simulink is integrated with MATLAB®, providing immediate access to an extensive range of tools that let you develop algorithms, analyze and visualize simulations, create batch processing scripts, customize the modeling environment, and define signal, parameter, and test data.

Simulink Coder

Simulink Coder™ (formerly Real-Time Workshop® prior to MATLAB R2011b) generates and executes C and C++ code from Simulink® diagrams, Stateflow® charts, and MATLAB® functions. The generated source code can be used for real-time and non-real-time applications, including simulation acceleration, rapid prototyping, and hardware-in-the-loop testing. You can tune and monitor the generated code using Simulink or run and interact with the code outside MATLAB and Simulink.

SISO

Continuous-time Single-Input, Single-Output (SISO) models. Users can define for example Transfer Function Model Using Numerator and Denominator Coefficients, Transfer Function Model Using Zeros/Poles/Gain, State-Space Model, or Frequency-Response Model.

Slave

See Master/Slave.

SLX Model File

The default file format for Simulink models in R2012b is SLX. Users save new models and libraries in the SLX format by default, with file extension .slx. SLX is a compressed package that conforms to the Open Packaging Conventions (OPC) interoperability standard. SLX stores model information using Unicode® UTF-8 in XML and other international formats. Saving Simulink models in the SLX format typically reduces file size compared to MDL. The file size reduction between MDL and SLX varies depending on the model. It also solves some problems in previous releases with loading and saving MDL files containing Korean and Chinese characters.

Solver

A solver is a component of the Simulink software. The Simulink product provides an extensive library of solvers, each of which determines the time of the next simulation step and applies a numerical method to solve the set of ordinary differential equations that represent the model. Every solver in the Simulink library can perform on models that contain algebraic loops. Solver refers to the integration algorithms used to solve the Ordinary Differential Equations (ODE). For a non-real-time simulation this could be a variable step solver such as ODE45, ODE15t, etc. However, these solvers are not suitable for real-time simulations since they require 'going back' in time. Simulink generates code that uses real-time solvers such as ODE1(Euler's method), ODE2, ODE4, etc.

Stability

If the controller parameters are chosen incorrectly, the controlled process input can be unstable, i.e., its output diverges, with or without oscillation, and is limited only by saturation or mechanical breakage. Instability is caused by excess gain, particularly in the presence of significant lag. Generally, stabilization of response is required and the process must not oscillate for any combination of process conditions and setpoints, though sometimes marginal stability (bounded oscillation) is acceptable or desired.

Stateflow

Stateflow® is an environment for modeling and simulating combinatorial and sequential decision logic based on state machines and flow charts. Stateflow lets you combine graphical and tabular representations, including state transition diagrams, flow charts, state transition tables, and truth tables, to model how your system reacts to events, time-based conditions, and external input signals. With Stateflow you can design logic for supervisory control, task scheduling, and fault management applications. Stateflow includes state machines animation and static and run-time checks for testing design consistency and completeness before implementation.

Subsystem

A subsystem is a set of blocks that users replace with a single block called a Subsystem block. As the model increases in size and complexity, users can simplify it by grouping blocks into subsystems. Using subsystems has these advantages: it helps reduce the number of blocks displayed in your model window, it keeps functionally related blocks together, it establishes a hierarchical block diagram, where a Subsystem block is on one layer and the blocks that make up the subsystem are on another. A Simulink block diagram can consist of layers. Each layer is defined by a subsystem. A subsystem is part of the overall block diagram and ideally has no impact on the meaning of the block diagram. Subsystems are provided primarily to help with the organizational aspects of a block diagram. Subsystems do not define a separate block diagram.

Tolerance

The Relative tolerance measures the error relative to the size of each state. The relative tolerance represents a percentage of the state value. The default, 1e-3, means that the computed state is accurate to within 0.1%. The Absolute tolerance is a threshold error value. This tolerance represents the acceptable error as the value of the measured state approaches zero.

Trigger

Add trigger port to model or subsystem. Adding a Trigger block to a model allows an external signal to trigger its execution. Users can add a trigger port to a root-level model or to a subsystem.

Triggered Subsystems

Triggered subsystems are subsystems that execute each time a trigger event occurs. A triggered subsystem has a single control input, called the trigger input, that determines whether the subsystem executes. Users create a triggered subsystem by placing a trigger port block within a subsystem. The resulting subsystem executes when a rising or falling edge with respect to zero is seen on the signal driving the subsystem trigger port. A Stateflow chart can also have a trigger port which is defined by using the Stateflow editor. Simulink does not distinguish between a triggered subsystem and a triggered chart.

Tunable Parameters

Many block parameters are tunable. A tunable parameter is a parameter whose value can be changed without recompiling the model. A tunable parameter is a parameter that a user can change while the simulation is running.

Variable Step Solver

Variable-step solvers can modify their step sizes during the simulation. They provide error control and zero crossing detection and may not comply with Real-Time constraints.

Variants

Variants represent the different choices within a graphical model and enable you to specify multiple configurations in a single unified block diagram and also switch programmatically between them prior to model simulation.

Variant Subsystem

Variant subsystems represent a subsystem with multiple subsystems. Variant subsystems provide multiple implementations for a subsystem where only one implementation is active during simulation. Users can programmatically swap out the active implementation with another implementation without modifying the model. The Variant Subsystem block includes multiple child subsystems, where only one subsystem is active during simulation. Each child subsystem is associated with a variant control, which is created in the base workspace.

Zero Crossing

Zero crossings in Simulink will automatically detect exactly when the switch block changes its output, and the solver will step to the exact time that the event happens.

Zero-Crossing Detection

A variable-step solver dynamically adjusts the time step size, causing it to increase when a variable is changing slowly and to decrease when the variable changes rapidly. This behavior causes the solver to take many small steps in the vicinity of a discontinuity because the variable is rapidly changing in this region. This improves accuracy but can lead to excessive simulation times. The Simulink software uses a technique known as zero-crossing detection to accurately locate a discontinuity without resorting to excessively small time steps. Usually this technique improves simulation run time, but it can cause some simulations to halt before the intended completion time.