Committee Chair
Pack, Daniel J.
Committee Member
Wang, Jin; Tanis, Craig; Wu, Dalei
College
College of Engineering and Computer Science
Publisher
University of Tennessee at Chattanooga
Place of Publication
Chattanooga (Tenn.)
Abstract
Algebraic connectivity is the second-smallest eigenvalue of the Laplacian matrix and can be used as a metric for the robustness and efficiency of a network. This connectivity concept applies to teams of multiple unmanned aerial vehicles (UAVs) performing cooperative tasks, such as arriving at a consensus. As a UAV team completes its mission, it often needs to control the network connectivity. The algebraic connectivity can be controlled by altering edge weights through movement of individual UAVs in the team, or by adding and deleting edges. The addition and deletion problem for algebraic connectivity, however, is NP-hard. The contributions of this work are 1) a comparison of four heuristic methods for modifying algebraic connectivity through the addition and deletion of edges, 2) a rule-based algorithm for tracking a connectivity profile through edge weight modification and the addition and deletion of edges, 3) a new, hybrid method for selecting the best edge to add or remove, 4) a distributed method for estimating the eigenvectors of the Laplacian matrix and selecting the best edge to add or remove for connectivity modification and tracking, and 5) an implementation of the distributed connectivity tracking using a consensus controller and double-integrator dynamics.
Degree
Ph. D.; A dissertation submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Doctor of Philosophy.
Date
8-2019
Subject
Drone aircraft -- Scientific applications
Document Type
Doctoral dissertations
DCMI Type
Text
Extent
xi, 100 leaves
Language
English
Rights
https://rightsstatements.org/page/InC/1.0/?language=en
License
http://creativecommons.org/licenses/by/4.0/
Recommended Citation
Trimble, James, "Network connectivity tracking for a team of unmanned aerial vehicles" (2019). Masters Theses and Doctoral Dissertations.
https://scholar.utc.edu/theses/617
Department
Dept. of Computational Engineering