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Title: Parameter Identification and Adaptive Control of a Fixed-Wing UAV in the Longitudinal Mode
Authors: Hess, Will
Hsia, Alexander
Advisors: Rowley, Clarence
Department: Mechanical and Aerospace Engineering
Certificate Program: Robotics & Intelligent Systems Program
Class Year: 2019
Abstract: This project aims to use parameter identification to construct state space models for an aircraft’s dynamical behavior given control input and state output histories. Improving upon traditional methods for physics-based dynamical modelling, a data-based system construction approach could circumvent modelling error, track time-variant system changes, and bypass the time and cost intensive aircraft modelling process. To this end, this project necessitates the building of a feedback control loop with low latency and high accuracy. This control loop can then be used to conduct flight tests for controllers designed using both traditional physics-based models and the novel data-based model presented in this project. Comparisons between the traditional and novel system modelling approaches reveal multiple performance benefits of the data-based parameter identification approach. Discussions of these benefits, as well as limitations and areas for future study are also presented.
Type of Material: Princeton University Senior Theses
Language: en
Appears in Collections:Mechanical and Aerospace Engineering, 1924-2020

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