MATLAB & Simulink

SIMULATION AND MODEL-BASED DESIGN

Simulink for System and Algorithm Modeling

​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

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​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

Course Outline

Day 1 of 2

Creating and Simulating a Model
Objective:Create a simple Simulink model simulate it, and analyze the results.

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• 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 

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• 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 

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• 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 .

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• 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.

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• Solver behaviour

• System Dynamics

• Discontinuties

• Algebraic Loops

Developing Model Hierarchy 
Objective: Use subsystems to combine smaller systems into larger systems.

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• Subsystems

• Bus signals

• Masks

Modeling Conditionally Executed Algorithms 
Objective: Create subsystems that are executed based on a control signal input.

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• Conditionally executed subsystems

• Enabled subsystems

• Tiggered subsystems

• Input validation model

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Combining Models into Diagrams

Objective: Use model referencing to combine models.

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• Subsystems and model referencing

• Model referencing workflow

• Model reference simulation modes

• Model workspaces

• Model dependencies

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Creating Libraries
 Use libraries to create and distribute custom blocks.

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• Creating and populating libraries

• Managing library links

• Addding a library to the Simulink Library Browser