Date of Graduation

2017

Document Type

Thesis

Degree Type

MS

College

Statler College of Engineering and Mineral Resources

Department

Mechanical and Aerospace Engineering

Committee Chair

Mario G Perhinschi

Committee Co-Chair

Patrick Browning

Committee Member

Christopher Griffin

Abstract

The use of autonomous unmanned aerial vehicles (UAV) has increased greatly over the years and is predicted to increase even more in the future. Thus, it is essential that these vehicles are able to fly safely with adequate performance under normal and abnormal conditions. In this research effort, the objective was to create a wind model to analyze the effects of atmospheric phenomena on trajectory tracking control of UAVs. A simplified model was developed and implemented within the WVU UAV simulation environment in order to simulate atmospheric phenomena, such as, constant wind with turbulence, wind gust and wind shear. Graphical user interfaces allow the setup of diverse simulation scenarios including constant wind and gusts in any direction and of any magnitude, different levels of turbulence and spatial variation of wind vector components in any direction (wind shear). The factors of the experimental grid also include, fixed parameter and adaptive trajectory tracking control laws, different 2-dimensional and 3-dimensional commanded trajectories and aircraft actuator failures.;Analysis of trajectory tracking performance relied on using composite indices based on trajectory tracking errors and control activity. Results show that, as the magnitude of the wind phenomena increases, the trajectory tracking degrades significantly for both adaptive and fixed parameter control laws, up to the point of loss of control. Control activity exhibits much less sensitivity. While adaptive control laws generally perform better, they present a greater degradation relative to nominal conditions than their fixed parameter counterpart. These results lead to the observation that specific adaptive mechanisms successful in handling a variety of other abnormal flight conditions may be less effective under wind. The direction of the wind relative to the aircraft proved important. In particular, downward wind components degrade significantly trajectory tracking and can easily lead to loss of control especially in combination with severe turbulence. The combination of actuator failures and wind conditions demonstrated that the adaptive controller presents higher performance than the fixed parameter controller.;This study reveals that UAV flight under wind phenomena may pose specific challenges in terms of trajectory tracking control laws design. Due to their typically reduced size, UAVs possess increased sensitivity to wind phenomena, which must be specifically addressed to improve safety and performance.

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