The aim of this project is to design an intelligent control system that can optimise the trajactory of an insect inspired flapping wing system.
The aim of this project is to design an intelligent control system that can optimise the trajactory of an insect inspired flapping wing system. Owing to the high speed of the flapping, a high bandwidth control system is required which may be implemented on a Field Programmable Gate Array or neuromorphic hardware. Using machine learning and evolutionary techniques, the system will learn how to best control the angle of attack and flapping motion to most efficiently produce thrust. This project will involve testing algorithms on a tethered one degree of freedom system that allows vertical control of hover. Depending on progress, the project may progress to testing on a 6 DOF free-flight Micro Air Vehicle
Contact:
School of Engineering & Technology
Systems & Control
