Developed an embedded control system for a cart-mounted inverted pendulum using encoder and vision-based feedback. Implemented PID & LQR algorithms on microcontrollers. Achieved 21ms rise-time & 0.5 degree overshoot in simulation. Integrated vision-based sensing with embedded processing, achieving 1.24 degree avg. error and 314ms latency.
This repository contains the report for the design and development of a cart-mounted inverted pendulum test bench, created as an undergraduate thesis project by Sarwan Shah, Muhammad Abdullah Siddiqui, and Adil Ali Khan at Habib University in 2021. The project aims to offer students an accessible, scalable, and cost-effective platform for learning control system principles and exploring vision-based control strategies.
This system was entirely designed and constructed in-house to facilitate hands-on research and education.
**PITCH VIDEO: **
- Custom-built hardware platform with a cart-mounted pendulum.
- MATLAB/Simulink models for system dynamics and simulation.
- Real-time feedback from both rotary encoders and a vision-based tracking system (ZED2 camera).
- Open-source design with a low-cost implementation (< $200).
- Scalable system for varying levels of control complexity and educational use.
- Custom track and cart with rotary encoders.
- DC motor and timing belt for actuation.
- Arduino Mega 2560 as the primary microcontroller.
- ZED2 Stereo Camera for vision-based tracking.
- Power supply and motor driver (Pololu VNH5019).
- MATLAB/Simulink for simulations and control.
- LabVIEW for data visualization (optional).
- Arduino IDE for uploading firmware.
- Python (optional) for vision-processing algorithms.