Simulink Training Course

Introduction

Overview of Simulink Features and Architecture

• Model-based design principles in Simulink
• Comparing MATLAB and Simulink
• Advantages of utilizing Simulink
• Simulink add-on tools

Getting Started with Simulink

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

Modeling Discrete Dynamical Systems

• Modeling using basic blocks
• Utilizing frames and buffers
• Differences between frames and multichannel signals
• Frame-based signals
• Multichannel frame-based signals

Modeling Logical Expressions

• Simple logical expressions
• Conditional signal routing
• Zero-crossing detection
• Using the MATLAB function block

Modeling from an Algorithm

• Modeling algorithmic specifications
• Iterative development processes in Simulink
• Model verification

Modeling Mixed-Signal Systems

• Examples of mixed-signal models
• Modeling ADCs

Solving Models with the Simulink Solver

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

Working with Simulink Subsystems and Libraries

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

Performing Spectral Analysis with Simulink

• Analysis using 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
• Model integration for large-scale projects
• Automating modeling tasks

Troubleshooting

Summary and Conclusion