MATLAB and Simulink Training

Simulink Fundamentals

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Course Details

This course (formerly known as Simulink for System and Algorithm Modeling) is for engineers new to system and algorithm modeling in Simulink®. It teaches attendees how to apply basic modeling techniques and tools to develop Simulink block diagrams.

Topics include:

  • Creating and modifying Simulink models and simulating system dynamics
  • Modeling continuous-time, discrete-time, and hybrid systems
  • Modifying solver settings for simulation accuracy and speed
  • Building hierarchy into a Simulink model
  • Creating reusable model components using subsystems, libraries, and model references

If your application is signal processing or communications, please refer to the Signal Processing with Simulink course.

Day 1 of 2

Creating and Simulating a Model

Objective: Create a simple Simulink model, simulate it, and analyze the results.

  • Introduction to the Simulink interface
  • Potentiometer system
  • System inputs and outputs
  • Simulation and analysis

Modeling Programming Constructs

Objective: Model and simulate basic programming constructs in Simulink.

  • Comparisons and decision statements
  • Vector signals
  • PWM conversion system
  • Zero crossings
  • MATLAB Function block

Modeling Discrete Systems

Objective: Model and simulate discrete systems in Simulink.

  • Discrete signals and states
  • PI controller system
  • Discrete transfer functions and state-space systems
  • Multirate discrete systems

Modeling Continuous Systems

Objective: Model and simulate continuous systems in Simulink.

  • Continuous states
  • Throttle system
  • Continuous transfer functions and state-space systems
  • Physical boundaries

Day 2 of 2

Solver Selection

Objective: Select a solver that is appropriate for a given Simulink model.

  • Solver behavior
  • System dynamics
  • Discontinuities
  • Algebraic loops

Developing Model Hierarchy

Objective: Use subsystems to combine smaller systems into larger systems.

  • Subsystems
  • Bus signals
  • Masks

Modeling Conditionally Executed Algorithms

Objective: Create subsystems that are executed based on a control signal input.

  • Conditionally executed subsystems
  • Enabled subsystems
  • Triggered subsystems
  • Input validation model

Combining Models into Diagrams

Objective: Use model referencing to combine models.

  • Subsystems and model referencing
  • Model referencing workflow
  • Model reference simulation modes
  • Model workspaces
  • Model dependencies

Creating Libraries

Objective: Use libraries to create and distribute custom blocks.

  • Creating and populating libraries
  • Managing library links
  • Adding a library to the Simulink Library Browser

Level: Fundamental

Prerequisites:

Duration: 2 days

Languages: Deutsch, English, Français, 日本語, 한국어, 中文

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