MATLAB and Simulink Training

Simulink Model Management and Architecture

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Course Details

This two-day course describes techniques for applying Model-Based Design in a common design workflow. It provides guidance on managing and sharing Simulink® models when working in a large-scale project environment.

Topics include:
 
  • Implementing interface control of Simulink subsystems and models
  • Managing requirements in Simulink models
  • Partitioning models using Simulink subsystems, libraries, and model references
  • Managing a model and all its dependencies
  • Addressing model scalability and performance concerns
  • Establishing and enforcing modeling standards
  • Documenting and sharing a Simulink model

Day 1 of 2

Model-Based Design

Objective: Get a brief overview of how Simulink models can be used in a traditional design process. Discuss where the material covered in this course fits into that process.

Requirements Linking and Interface Control

Objective: Link a Simulink model to system requirements, illustrate data flow, and define system interfaces.

  • Component stubs
  • Requirements linking
  • Component interfaces
  • Bus objects

Model Architecture

Objective: Discuss the pros and cons of the different features used for organizing a Simulink model into separate components.

  • System component considerations
  • Virtual subsystems
  • Atomic subsystems
  • Subsystem references
  • Model references
  • Libraries
  • Component variants

Project Management

Objective: Discuss how to effectively organize a project (containing models, data, documentation, etc.) and perform configuration management tasks.

  • Project setup
  • File shortcuts and labels
  • File dependencies and impact
  • Source control integration
  • File differences

Day 2 of 2

Data Management

Objective: Explore the data dependencies of a Simulink model and learn best practices for managing a Simulink model's data.

  • Workspace precedence
  • Parameter management
  • Saving and loading data
  • Data dictionaries

Model Scalability

Objective: Understand data objects, partition data in dictionaries, create reference projects and configurations sets to organize large projects.

  • Data objects
  • Reference data dictionaries
  • Reference configuration sets
  • Data partitioning
  • Reference projects

Model Performance

Objective: Learn how to improve simulation performance, use acceleration modes and understand their tradeoffs.

  • Simulink Profiler
  • Simulation modes
  • Comparing performance
  • Performance Advisor

Modeling Standards

Objective: Explore how to set up and enforce modeling standards, check for common modeling errors, and optimize model performance.

  • Modeling standards
  • Model Advisor
  • Reporting results
  • Additional Simulink advisors
  • Templates

Reporting

Objective: Discuss the methods of automatically creating reports and documentation from Simulink models.

  • Web views
  • Standard reports
  • Custom reports

Level: Intermediate

Prerequisites:

Duration: 2 days

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

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