Document Type

Thesis - Open Access

Award Date

2018

Degree Name

Master of Science (MS)

Department / School

Mechanical Engineering

First Advisor

Marco Ciarcià

Keywords

Accurate landing, Ar Drone 2.0, Energy minimization, Jerk minimization, Nonlinear programming, Real-time trajectory optimization

Abstract

Despite the vast popularity of rotary wing unmanned aerial vehicles and research centres that develop their guidance software, there are only a limited number of references that provide an exhaustive description of a step-by-step procedure to build-up a multirotor testbed. In response to such need, the first part of this thesis aims to describe, in detail, the complete procedure to establish and operate an autonomous multirotor unmanned aerial vehicle indoor experimental platform to test and validate guidance, navigation and control strategies. Both hardware and software aspects of the testbed are described to offer a complete understanding of the different aspects. The second part of this thesis focuses on two benchmarks multirotor guidance, navigation and control problems. Initially, the guidance law for an accurate landing manoeuvre is studied. Multirotor usually have a flight time limited to a few minutes. Autonomous landing and docking to a charging station could extend the mission duration of these vehicles. Subsequently, the guidance strategy for the formation flight between two multirotors is considered. In this case, the fundamental goal is an accurate autonomous alignment between two vehicles, each of them behaving as a target and chaser simultaneously. In the last part of this thesis, the problem of minimum energy manoeuvres is tackled. Again, in this case, the motive is to address the limitation in multirotor flight duration. The fundamental objective of this guidance, navigation and control strategy is to determine and implement, in real-time, the minimum energy control histories that transfer the multirotor from its initial point to a given final point. As opposed to conventional guidance strategies, mostly based on proportional-integral-derivative laws, a minimum energy controller allows the vehicle to execute the manoeuvre with a minimum electrical power expenditure.

Library of Congress Subject Headings

Drone aircraft -- Testing.
Drone aircraft -- Control systems.
Drone aircraft -- Mathematical models.
Real-time control.
Trajectory optimization.

Description

Includes bibliographical references

Format

application/pdf

Number of Pages

103

Publisher

South Dakota State University

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Rights Statement

In Copyright