Overview

For our capstone project, we worked with Dr. Zeng’s team to create a non-linear control system for an Electric Vertical Takeoff and Landing (E-VTOL) drone using a novel method for generating optimal control sequences. Our focus was primarily on updating the drone hardware, developing a simulation of the drone, and applying an iterative Taylor-series process to develop optimal control sequences for transitioning the drone between vertical and horizontal flight modes, minimizing energy consumption, thus increasing the aircraft’s efficiency and range.

Electric Vertical Takeoff and Landing (E-VTOL) drone

E-VTOL is a fixed-wing aircraft with sitters on its tails allowing for vertical takeoff and landing. This aircraft can switch between a horizontal, fast, and energy-efficient cruise mode, and a vertical hover that allows for tighter maneuverability and landing without a runway.

The stage between the hovering and horizontal flight is called the forward transition, and the reverse case is called the backward transition[1]. After going through the forward transition phase, in which the tailsitter rotates its whole body from the vertical position to the horizontal one, the aircraft flies in a conventional way. Thanks to the fixed-wing-like flight, it benefits from better aerodynamics, more reliable mechanical structure, more efficient power conversion, etc. In a nutshell, a tailsitter combines merits from VTOL aircraft, like the helicopter, and fixed-wing ones, like the Boeing-747.

In order to extend flight times, it is valuable to improve operational efficiency. One costly part of the drone’s flight is the transition between flight modes, which is difficult to stabilize and requires more energy than either flight mode. Our project is mainly focused on optimizing The process of transitioning between these two modes.

Meet Team members

Ethan Cuka

B.S in Physics

B.S in System Engineering

Yucen Zhong

B.S in System Engineering

M.S in Computer Science

Weijia Will Li

B.A in Mathematics

B.S in System Engineering

M.S in Data Analytics & Statistics