Simulink Training Course

Introduction

Overview of Simulink Features and Architecture

• Model-based design using Simulink
• Comparing MATLAB and Simulink
• Advantages of utilizing Simulink
• Simulink add-ons

Getting Started with Simulink

• User interface and block libraries
• Creating and modifying models
• Defining system inputs and outputs
• Simulating models

Modeling Discrete Dynamical Systems

• Modeling using fundamental blocks
• Utilizing frames and buffers
• Distinguishing frames from multichannel signals
• Frame-based signals
• Multichannel frame-based signals

Modeling Logical Expressions

• Basic logical expressions
• Conditional signal routing
• Detecting zero-crossings
• Incorporating the MATLAB function block

Modeling from an Algorithm

• Modeling algorithmic specifications
• Iterative development with Simulink
• Verifying models

Modeling Mixed-Signal Systems

• Examples of mixed-signal models
• Modeling ADCs

Solving Models with Simulink Solver

• Single models
• Discrete and continuous states
• Multiple rates
• Fixed-step versus variable-step approaches
• Managing zero crossings and algebraic loops

Working with Simulink Subsystems and Libraries

• Creating subsystems (virtual and atomic)
• Building configurable subsystems
• Developing custom block libraries
• Modeling conditionally executed subsystems
• Condition-driven systems (enabled and triggered subsystems)

Performing Spectral Analysis with Simulink

• Analyzing via the Spectrum Scope block
• Selecting appropriate analysis parameters
• Power spectrum analysis (e.g., motor noise)
• Frequency response of discrete systems

Modeling Multirate Systems

• Blocks for multirate signal processing
• Resampling oversampled data
• Designing and converting model filters
• Anti-imaging and anti-aliasing filters
• Multirate filter blocks

Exploring Advanced Simulink Topics

• Importing MATLAB or C code into models
• Integrating models for large-scale projects
• Automating modeling tasks

Troubleshooting

Summary and Conclusion