Author ORCID Identifier

https://orcid.org/0000-0002-6297-5765

Date Available

8-9-2023

Year of Publication

2022

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Engineering

Department/School/Program

Mechanical Engineering

First Advisor

Dr. Jesse B. Hoagg

Abstract

Advances in the miniaturization of powerful electronic components and motors, the democratization of global navigation satellite systems (GNSS), and improvements in the performance, safety, and cost in lithium batteries has led to the proliferation of small and relatively inexpensive unmanned aerial vehicles (UAVs). Many of these UAVs are of the multi-rotor design, however, fixed-wing designs are often more efficient than rotary-wing aircraft, leading to a reduction in the power required for a UAV of a given mass to stay airborne. Autonomous cooperation between multiple UAVs would enable them to complete objectives that would be difficult or impossible for a single UAV to complete alone, and to do so with minimal human oversight. Such objectives include distributed sensing, efficient airspace integration, and physical interaction (e.g., docking, in-flight refueling, etc). Formation control is one form of autonomous cooperation.

We present new formation-control algorithms for robotic vehicles modeled by extended unicycle dynamics, that include orientation kinematics on SO(m), first-order speed dynamics, and a hard constraint on speed. The desired interagent positions are time-varying. The analytic results show that for almost all initial conditions, the agents converge to the desired relative positions with the other agents and the leader, and that if the initial and desired speeds are always within the agent’s speed bounds, the agent speed is within those bounds. We provide sufficient conditions to ensure that the desired speed is within the speed bounds. We also present several sets of experiments and simulations with up to 4 fixed-wing unmanned air vehicles (UAVs) that demonstrate the formation-control algorithms.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2022.299

Share

COinS