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Training - Courses

SL01-O: Simulink for Aerospace System Design

This course targets engineers who are new to system and algorithm modeling and will teach them to validate their designs using the Simulink environment, as well as:

  • Aerospace modeling and analysis using Simulink
  • Modeling continuous-time, single- and multirate discrete-time, and hybrid systems
  • Understanding model hierarchy
  • Executing a condition-based system
  • Automating model simulations
  • Developing custom blocks and libraries

Please Note: This course is equivalent to Simulink for System and Algorithm Modeling (SL01) course

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 Detailed course outline

 

Day 1 of 2
Introduction

Objective: Obtain a quick overview of The MathWorks and discuss course logistics

Introduction to System Modeling

Objective: Describe the model-based design process and system modeling in Simulink.

  • System modeling with the Simulink environment
  • Model-Based Design with Simulink
  • Electronic Throttle Control model
Modeling Algebraic Systems

Objective: Use Simulink to model and simulate algebraic systems.

  • Define the potentiometer system
  • Introduce the Simulink interface
  • Create a Simulink model of the potentiometer system
  • Simulate the model and analyze results
Modeling Logical Systems

Objective: Use Simulink to model and simulate logical systems

  • Define the logical system
  • Create a Simulink model for the logical system
  • Introduce zero crossings
  • Simulate the model and analyze the results
  • Model the system with Embedded MATLAB
Modeling Continuous Systems

Objective: Use Simulink to model and simulate continuous systems.

  • Define the throttle system
  • Create a Simulink model for the throttle system
  • Define continuous states
  • Choose a continuous solver
  • Simulate the model and analyze results
Day 2 of 2
Modeling Discrete Systems

Objective: Use Simulink to model and simulate discrete systems.

  • Define the PI controller system
  • Create a Simulink model for the PI controller
  • Define discrete states
  • Choose a discrete solver
  • Model multirate discrete systems
Modeling Systems with Subsystems

Objective: Use subsystems to combine smaller systems into larger systems and to model signal driven systems.

  • Create and use subsystems
  • Define model callbacks
  • Contrast virtual and non-virtual subsystems
  • Model conditionally executed subsystems
Combining Models into Diagrams

Objective: Use model reference to combine models

  • Model referencing and subsystems
  • Set up a model reference
  • Model reference simulation modes
  • View signals in referenced models
  • Store parameters in referenced models
Creating Custom Blocks and Libraries

Objective: Use masks and libraries to create and distribute custom blocks.

  • Mask subsystems
  • Create new libraries
  • Create configurable subsystems
  • Add libraries to the Library Browser
  • Compare libraries and model references

 


Prerequisites

Knowledge of MATLAB basics.

Course Length - 2  days

Price - $1,100.00

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