OnBoard Parameter Identification for a Small UAV

McGrail, Amanda K.

doi:10.33915/etd.492

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…Previous research established a nonlinear model of the Phastball aircraft dynamics using parameter identification [74]. These parameters were used to develop a Matlab/Simulink simulation as shown in…”

Section: Phastball Simulink Modelmentioning

confidence: 99%

Adaptation of Temporal Control to Unpredictable Mid-Session Changes in a Rapid-Acquisition Multiple Peak-Interval Procedure

Rice¹

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Control Design and Performance Analysis for Autonomous Formation Flight Experiments Caleb Michael Rice Autonomous Formation Flight is a key approach for reducing greenhouse gas emissions and managing traffic in future high density airspace. Unmanned Aerial Vehicles (UAV's) have made it possible for the physical demonstration and validation of autonomous formation flight concepts inexpensively and eliminates the flight risk to human pilots. This thesis discusses the design, implementation, and flight testing of three different formation flight control methods, Proportional Integral and Derivative (PID); Fuzzy Logic (FL); and NonLinear Dynamic Inversion (NLDI), and their respective performance behavior. Experimental results show achievable autonomous formation flight and performance quality with a pair of low-cost unmanned research fixed wing aircraft and also with a solo vertical takeoff and landing (VTOL) quadrotor.

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Section: Phastball Simulink Modelmentioning

confidence: 99%