## 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

#### 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