UWSpace is currently experiencing technical difficulties resulting from its recent migration to a new version of its software. These technical issues are not affecting the submission and browse features of the site. UWaterloo community members may continue submitting items to UWSpace. We apologize for the inconvenience, and are actively working to resolve these technical issues.
 

Biologically Inspired Adaptive Control of Quadcopter Flight

Thumbnail Image

Files

Komer_Brent.pdf (4.24 MB)

Date

2015-08-20

Authors

Komer, Brent

Journal Title

Journal ISSN

Volume Title

Publisher

University of Waterloo

Abstract

This thesis explores the application of a biologically inspired adaptive controller to quadcopter flight control. This begins with an introduction to modelling the dynamics of a quadcopter, followed by an overview of control theory and neural simulation in Nengo. The Virtual Robotics Experimentation Platform (V-REP) is used to simulate the quadcopter in a physical environment. Iterative design improvements leading to the final controller are discussed. The controller model is run on a series of benchmark tasks and its performance is compared to conventional controllers. The results show that the neural adaptive controller performs on par with conventional controllers on simple tasks but exceeds far beyond these controllers on tasks involving unexpected external forces in the environment.

Description

Keywords

Quadcopter, Control, Adaptive Control, Nengo, Neural Network, Learning, Neuromorphic, Computer Science

LC Keywords

Citation

URI

http://hdl.handle.net/10012/9549

Collections

Theses
Computer Science