Stabilising a PID-Controlled Quadcopter

I am currently leading a capstone project at Maynooth University where our team is building a 6-DoF quadcopter model from the ground up. My main goal is to make the controller feel natural—responsive enough for a pilot while still rejecting wind gusts and sensor noise.

What the build looks like

• Modelled the aircraft dynamics in MATLAB/Simulink and exported plant data into a tidy test harness so we could iterate every morning without waiting on hardware time.
• Tuned three cascaded PID loops (attitude, rate, and altitude) and brought the steady-state error under 5% while improving the transient response by ~20%.
• Connected the telemetry stream to Unreal Engine for a photorealistic sandbox; it allows us to present stability plots beside cinematic footage that non-technical stakeholders can understand.

Why it matters

The project forced me to connect the dots between modelling, control, and communication. I now maintain a reusable library of Simulink blocks for multi-rotor vehicles, plus a workflow for presenting results visually. Those habits translated into other robotics work where I need to validate ideas fast and explain them even faster.