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Simulink Fundamentals
A comprehensive introduction to Simulink exploring dynamic system modeling, model hierarchy, and component reusability.
Complimentary Services: Post training email support & 1-hr consultation session within 1 month after the course completion!
Course
Highlights
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
Who Should
Attend
Engineers who are new to the Simulink environment.
Course
Prerequisites
MATLAB Fundamentals
Course
Benefits
Upon the completion of the course, the participants will be able to:
- create, modify and simulate dynamic systems using Simulink
- build continuous, discrete, algebraic and logic systems
- understand solver setting
- build hierarchy into Simulink model
- create reusable model components
Partners
Upcoming Program
- Please keep me posted on the next schedule
- Please contact me to arrange customized/ in-house training
Course Outline
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
- Solver behavior
- Algebraic loops
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
- Throtle system
- Physical boundaries
- Continuous transfer functions and state-space systems
- Simulation speed and accuracy
Modeling Continuous Systems
Objective: Model and simulate continuous systems in Simulink.
- Continuous states
- Throttle system
- Physical boundaries
- Continuous transfer functions and state-space systems
- Simulation speed and accuracy
Developing Model Hierarchy
Objective: Use subsystems to combine smaller systems into larger systems.
- Ports and Subsystems
- Masks
- Vector and bus signals
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
Referencing Model Components
Objective: Use referencing to combine subsystems and models.
- Referencing workflow
- Subsystems referencing
- Model referencing
- Root-level inputs and outputs
- Model workspaces
- Model reference simulation modes
- 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