System Identification of a Nonlinear Flight Dynamics Model for a Small, Fixed-Wing UAV
This thesis describes the development of a nonlinear flight dynamics model for a small, fixed-wing unmanned aerial vehicle (UAV). Models developed for UAVs can be used for many applications including risk analysis, controls system design and flight simulators. Several challenges exist for system ide...
Main Author: | |
---|---|
Other Authors: | |
Format: | Others |
Published: |
Virginia Tech
2019
|
Subjects: | |
Online Access: | http://hdl.handle.net/10919/95324 |
id |
ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-95324 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-953242020-09-29T05:44:48Z System Identification of a Nonlinear Flight Dynamics Model for a Small, Fixed-Wing UAV Simmons, Benjamin Mason Aerospace and Ocean Engineering Woolsey, Craig A. Patil, Mayuresh J. Artis, Harry Pat Raj, Pradeep Output Error Method Unmanned Aerial Vehicle Vortex Lattice Method Flight Testing Aerodynamic Modeling Parameter Estimation This thesis describes the development of a nonlinear flight dynamics model for a small, fixed-wing unmanned aerial vehicle (UAV). Models developed for UAVs can be used for many applications including risk analysis, controls system design and flight simulators. Several challenges exist for system identification of small, low-cost aircraft including an increased sensitivity to atmospheric disturbances and decreased data quality from a cost-appropriate instrumentation system. These challenges result in difficulties in development of the model structure and parameter estimation. The small size may also limit the scope of flight test experiments and the consequent information content of the data from which the model is developed. Methods are presented to improve the accuracy of system identification which include data selection, data conditioning, incorporation of information from computational aerodynamics and synthesis of information from different flight test maneuvers. The final parameter estimation and uncertainty analysis was developed from the time domain formulation of the output-error method using the fully nonlinear aircraft equations of motion and a nonlinear aerodynamic model structure. The methods discussed increased the accuracy of parameter estimates and lowered the uncertainty in estimates compared to standard procedures for parameter estimation from flight test data. The significant contributions of this thesis are a detailed explanation of the entire system identification process tailored to the needs of a small UAV and incorporation of unique procedures to enhance identification results. This work may be used as a guide and list of recommendations for future system identification efforts of small, low-cost, minimally instrumented, fixed-wing UAVs. MS 2019-11-08T07:00:25Z 2019-11-08T07:00:25Z 2018-05-16 Thesis vt_gsexam:15301 http://hdl.handle.net/10919/95324 In Copyright http://rightsstatements.org/vocab/InC/1.0/ ETD application/pdf Virginia Tech |
collection |
NDLTD |
format |
Others
|
sources |
NDLTD |
topic |
Output Error Method Unmanned Aerial Vehicle Vortex Lattice Method Flight Testing Aerodynamic Modeling Parameter Estimation |
spellingShingle |
Output Error Method Unmanned Aerial Vehicle Vortex Lattice Method Flight Testing Aerodynamic Modeling Parameter Estimation Simmons, Benjamin Mason System Identification of a Nonlinear Flight Dynamics Model for a Small, Fixed-Wing UAV |
description |
This thesis describes the development of a nonlinear flight dynamics model for a small, fixed-wing unmanned aerial vehicle (UAV). Models developed for UAVs can be used for many applications including risk analysis, controls system design and flight simulators. Several challenges exist for system identification of small, low-cost aircraft including an increased sensitivity to atmospheric disturbances and decreased data quality from a cost-appropriate instrumentation system. These challenges result in difficulties in development of the model structure and parameter estimation. The small size may also limit the scope of flight test experiments and the consequent information content of the data from which the model is developed. Methods are presented to improve the accuracy of system identification which include data selection, data conditioning, incorporation of information from computational aerodynamics and synthesis of information from different flight test maneuvers. The final parameter estimation and uncertainty analysis was developed from the time domain formulation of the output-error method using the fully nonlinear aircraft equations of motion and a nonlinear aerodynamic model structure. The methods discussed increased the accuracy of parameter estimates and lowered the uncertainty in estimates compared to standard procedures for parameter estimation from flight test data. The significant contributions of this thesis are a detailed explanation of the entire system identification process tailored to the needs of a small UAV and incorporation of unique procedures to enhance identification results. This work may be used as a guide and list of recommendations for future system identification efforts of small, low-cost, minimally instrumented, fixed-wing UAVs. === MS |
author2 |
Aerospace and Ocean Engineering |
author_facet |
Aerospace and Ocean Engineering Simmons, Benjamin Mason |
author |
Simmons, Benjamin Mason |
author_sort |
Simmons, Benjamin Mason |
title |
System Identification of a Nonlinear Flight Dynamics Model for a Small, Fixed-Wing UAV |
title_short |
System Identification of a Nonlinear Flight Dynamics Model for a Small, Fixed-Wing UAV |
title_full |
System Identification of a Nonlinear Flight Dynamics Model for a Small, Fixed-Wing UAV |
title_fullStr |
System Identification of a Nonlinear Flight Dynamics Model for a Small, Fixed-Wing UAV |
title_full_unstemmed |
System Identification of a Nonlinear Flight Dynamics Model for a Small, Fixed-Wing UAV |
title_sort |
system identification of a nonlinear flight dynamics model for a small, fixed-wing uav |
publisher |
Virginia Tech |
publishDate |
2019 |
url |
http://hdl.handle.net/10919/95324 |
work_keys_str_mv |
AT simmonsbenjaminmason systemidentificationofanonlinearflightdynamicsmodelforasmallfixedwinguav |
_version_ |
1719346374946848768 |