While PID control remains the industry standard, advanced strategies like model-based control are increasingly used in high-end applications. This project focuses on designing and optimizing a control system for a ball-balancing tripod, developed as a demonstration platform to highlight the benefits of model-based control.

The tripod, a parallel manipulator with three linear actuators, stabilizes a ball with variable inertia by adjusting the platform’s tilt and height. A digital twin (DT) was created to enable model-based control and directly compare it with traditional PID strategies. A detailed Simscape model simulated kinematics, dynamics, actuation, and sensor noise, and was validated through mathematical modeling and time-domain analysis. Both controllers were tuned and tested on the DT before implementation on hardware.

The video below demonstrates the power of Model Based Control applied to our ball balancing tripod system. Watch as the ball smoothly navigates a predefined maze, then moves accurately to target positions set in real time via a touchscreen interface. This setup highlights how Model Based Control enables faster settling times, reduced overshoot, and improved stability compared to classic control strategies.