Javascript must be enabled for the correct page display

Decentralized Estimation of the Algebraic Connectivity

Lensing, W. E. and Waarde, H. J. (2017) Decentralized Estimation of the Algebraic Connectivity. Bachelor's Thesis, Industrial Engineering and Management.

[img] Text
Bachelor_IEM_2017_WarnerLensing.pdf - Published Version
Restricted to RUG campus only

Download (859kB)
[img] Text
toestemming.pdf - Other
Restricted to Backend only

Download (79kB)


Network science is an emerging field of study. Networks consist of nodes and links between these nodes. In many practical situations, the way the nodes in a network are connected, is unknown. To control and make predictions about a network, it can be important that the connection structure is known. In some cases, knowledge about certain network properties is sufficient. To control the connectivity in a network, the algebraic connectivity can be used. The algebraic connectivity indicates whether a network is connected. There are algorithms that can estimate the algebraic connectivity in networks with unknown connection structures. To use it in practical situations, it is important that the algebraic connectivity is found in a decentralized way. This means that every component in the network calculates the algebraic connectivity by only using local interactions. In multi-robot systems, a decentralized identification of the algebraic connectivity plays a major role. In matters such as flocking and formations control of the multi-robot systems, control of the connectivity is crucial. In this thesis, three decentralized methods to identify the algebraic connectivity are analyzed and their applications are discussed. Finally, the accuracy, computation time, and convergence conditions of the methods are compared.

Item Type: Thesis (Bachelor's Thesis)
Degree programme: Industrial Engineering and Management
Thesis type: Bachelor's Thesis
Language: English
Date Deposited: 15 Feb 2018 08:28
Last Modified: 15 Feb 2018 08:28

Actions (login required)

View Item View Item