Dynamic Modeling & Simulation of a Self-Balancing Two-Wheeled Robot using Lagrangian Method, PID & LQR Control – MATLAB Simulink

📦 Product Description

🎯 Simulate & stabilize your own two-wheeled robot!
This comprehensive simulation models a self-balancing robot (inverted pendulum on wheels) using Lagrangian dynamics and implements both PID and LQR control strategies in MATLAB Simulink.

From physical modeling to real-time control, this package is your complete guide to mastering dynamic systems and balance control!

📘 What’s Included:

• ✅ MATLAB Simulink (.slx) model – Fully editable & commented

• ✅ Lagrangian-based dynamic modeling of a two-wheeled system

• ✅ Two control strategies: PID and LQR included

• ✅ Real-time visualization with robot animation

• ✅ Scopes for tracking: position, angle, velocity, input force

• ✅ Documentation & ReadMe for smooth setup

• ✅ All parameters & equations derived from physics

💡 Key Features:

• 🧠 Dual Control Logic: Switch between PID and LQR to understand control behavior

• 🛠️ Physics-based system modeled from first principles

• 📊 Full simulation visualization: angles, positions, velocities

• ⚙️ Easily modify system parameters or extend for research

• 🧩 Ideal for real-world robotics, inverted pendulum demos, or academic control system studies

• 🎥 Includes tutorial video on how to run & customize the simulation

🧑‍🎓 Perfect For:

• Control systems students & instructors

• Robotics, mechatronics & mechanical engineering researchers

• Final-year projects or simulation-based learning

• Simulation enthusiasts exploring Simulink + Dynamics

🔧 Built With:

• MATLAB Simulink (no .m code execution required)

• Lagrangian Modeling Approach

• PID & LQR Control Design

• Scope blocks for signal tracking

• Realistic dynamic behavior

• Optional extensions to add sensors, filters, or real-time tuning

📂 Files Included:

• 📁 .slx Simulink model file

• 📝 Equations & parameters documentation (PPT)

• 📺 Step-by-step tutorial video included

📬 Need help?
Email: mregnineer294@gmail.com

📲 Follow for more simulations & robotics projects:
📧 Email: mregnineer294@gmail.com
📷 Instagram: @engrprogrammer2494
▶️ YouTube: @engrprogrammer

Thanks again, and happy simulating!
— engrprogrammer 🚀