# ​Course Highlight

This two-day course is for engineers who are new to system and algorithm modeling and design validation in Simulink®. It demonstrates 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 Simulink for Signal Processing course.

# Who Should Attend

Engineers who are new to the SIMULINK environment.

# Course Prerequisite

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

# 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

• Comparisions and decision statements

• Vector signals

• PWM conversion system

• Zero crossings

• MATLAB function block

Modeling Discrete Systems
Objective:Model and simulates discrete systems in Simulink

• Discrete signals and states

• PI Controller system

• Model discrete transfer functions and state space systems

• Multirate discrete systems

Modeling Continuous Systems
Objective:Model and simulates continues system 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 behaviour

• System Dynamics

• Discontinuties

• 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

• Tiggered 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
Use libraries to create and distribute custom blocks.

• Creating and populating libraries