PID-Controlled Feeding System for TUM

Commissioned by the Technical University of Munich, the system leverages PID control theory to manage nutrient flow within bioprocess systems. Built for biological research labs, it autonomously adjusts feeding rates based on sensor feedback, ensuring exact delivery tailored to biological growth curves and environmental variability.

TUM researchers faced limitations in their feeding strategies due to the imprecision of existing systems and lack of automation of their desired feeding protocols. Inconsistent nutrient delivery affected experimental reproducibility and scalability, creating a bottleneck in high-value biological experimentation.

I engineered an autonomous PID-based algorithmic model that dynamically computes optimal flow rates by continuously analyzing real-time sensor data. This embedded control solution adapts to fluctuations in system dynamics and supports integration into diverse lab environments.

Achieved 92% accuracy in nutrient delivery, surpassing all prior benchmarks. Enabled TUM researchers to execute bioprocess experiments with unmatched reliability and opened the door for scalable automation in lab workflows. The system has since attracted interest from lab equipment manufacturers.