This Simulink training is designed to help participants model, simulate, and analyze dynamic systems using MATLAB Simulink. The course covers Simulink fundamentals, block-based modeling, simulation workflows, signal routing, subsystem design, model configuration, basic control system modeling, and code generation concepts. Participants will gain hands-on experience to build and validate dynamic system models for engineering, automotive, aerospace, and industrial automation applications.

• Understand the modeling environment, simulation architecture, and system design capabilities of Simulink for engineering application  development.
• Set up and configure the Simulink environment, libraries, and development tools for simulation projects.
• Design block diagrams, dynamic models, control systems, and modular simulation workflows using Simulink development approaches.
• Implement signal processing, system modeling, data analysis, and simulation workflows effectively.
• Debug, test, and optimize Simulink models for performance, accuracy, and maintainability.
• Build scalable, reliable, and production-ready simulation and control system solutions using Simulink best practices.

 • Control systems engineers
 • Automotive and aerospace engineers
 • Embedded systems developers
 • Mechatronics and robotics engineers
 • Engineering students and researchers

 • Basic understanding of MATLAB fundamentals
 • Familiarity with basic engineering and mathematical concepts
 • Interest in system modeling and simulation

 • Building dynamic system models in Simulink
 • Configuring and running simulations
 • Using Simulink blocks and libraries
 • Creating subsystems and hierarchical models
 • Analyzing simulation results
 • Integrating Simulink with MATLAB scripts
 • Applying basic control system modeling
 • Preparing models for code generation

By the end of this training, participants will be able to build, simulate, and analyze dynamic system models using Simulink with confidence. Learners will gain strong fundamentals in block-based modeling, control system simulation, and model validation, enabling them to apply Simulink effectively in engineering and industrial applications.

Introduction to Simulink & Modeling Basics
 • What is Simulink and where it is used
 • Simulink interface and libraries
 • Creating basic block diagrams
 • Connecting and configuring blocks

Signal Routing & Data Types
 • Working with signals and buses
 • Data types and signal attributes
 • Using mux, demux, and bus creators
 • Managing signal flow

Subsystems & Model Organization
 • Creating subsystems
 • Hierarchical modeling
 • Masking subsystems basics
 • Organizing large models

Simulation Configuration & Execution
 • Simulation settings and solvers
 • Fixed-step vs variable-step solvers
 • Running and stopping simulations
 • Viewing simulation results

Modeling Dynamic Systems
 • Continuous and discrete systems
 • Integrators and transfer functions
 • Modeling physical systems basics
 • Using Simscape overview

Control System Modeling Basics
 • Modeling feedback control systems
 • PID controller blocks
 • Tuning PID controllers basics
 • Analyzing control system responses

Data Visualization & Analysis
 • Scopes and data inspection tools
 • Logging simulation data
 • Using Simulation Data Inspector
 • Analyzing time-series data

Interfacing Simulink with MATLAB
 • Calling MATLAB functions from Simulink
 • Using MATLAB Function blocks
 • Parameter tuning from MATLAB
 • Automating simulations

Model Verification & Validation
 • Model checking basics
 • Validating simulation results
 • Comparing simulation scenarios
 • Best practices for model verification

Code Generation Basics
 • Introduction to Simulink Coder
 • Generating C/C++ code
 • Embedded code generation overview
 • Preparing models for deployment

Real-Time & Hardware-in-the-Loop Basics
 • Real-time simulation concepts
 • HIL testing overview
 • Interfacing with hardware basics
 • Testing embedded controllers

Performance Optimization & Model Management
 • Improving simulation performance
 • Managing large models
 • Version control for Simulink models
 • Collaboration best practices

Simulink Project Workshop & Best Practices
 • Building a complete Simulink model
 • Applying modeling standards
 • Running end-to-end simulations
 • Final project review and optimization

• Simulink Setup & Simulation Architecture
• Project Configuration, Libraries & Block Diagram Modeling
• Dynamic Systems, Control Models & Signal Processing
• Data Analysis, Simulation Workflows & Model Integration
• Testing, Debugging & Performance Optimization
• End-to-End Simulink Application Development Project

Participants will be evaluated through hands-on Simulink modeling labs, practical simulation exercises, instructor-led model reviews, and a final project-based assessment focused on building and validating a complete Simulink system model.

Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.

Upon successful completion of the training, participants will receive an AcadNXT Certificate of Completion for Simulink. This digital, verifiable certification validates practical Simulink modeling, simulation, and basic control system development skills and can be shared on LinkedIn and included in professional profiles to enhance engineering career credibility.