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Flight Results of Autonomous Fixed-Wing UAV Transitions to and from Stationary Hover
(Georgia Institute of Technology, 2006-08)
Fixed-wing unmanned aerial vehicles (UAVs) with the ability to hover have significant
potential for applications in urban or other constrained environments where the
combination of fast speed, endurance, and stable ...
Modeling, Control, and Flight Testing of a Small Ducted Fan Aircraft
(Georgia Institute of Technology, 2006-07)
Small ducted fan autonomous vehicles have potential for several applications, especially
for missions in urban environments. This paper discusses the use of dynamic inversion with
neural network adaptation to provide an ...
Adaptive Trajectory Control for Autonomous Helicopters
(Georgia Institute of Technology, 2005)
For autonomous helicopter flight, it is common to separate the flight control problem into an inner loop that
controls attitude and an outer loop that controls the translational trajectory of the helicopter. In previous ...
A Process to Obtain Robustness Metrics for Adaptive Flight Controllers
(Georgia Institute of Technology, 2009-08)
This research effort seeks a process to draw parallels between the classical stability
metrics of gain and phase margins for classical linear control systems with stability margins
for adaptive controllers. The method ...
Command Governor-Based Adaptive Control of an Autonomous Helicopter
(Georgia Institute of Technology, 2012-08)
This paper presents an application of a recently developed command governor-based
adaptive control framework to a high-fidelity autonomous helicopter model. This framework
is based on an adaptive controller, but the ...
Improving Uniform Ultimate Bounded Response of Neuroadaptive Control Approaches Using Command Governors
(Georgia Institute of Technology, 2013-08)
In this paper, we develop a command governor-based architecture in order to improve the response of neuroadaptive control approaches. Specifically, a command governor is
a linear dynamical system that modifies a given ...
Adaptive Neural Network Flight Control Using both Current and Recorded Data
(Georgia Institute of Technology, 2007-08)
Modern aerospace vehicles are expected to perform beyond their conventional flight
envelopes and exhibit the robustness and adaptability to operate in uncertain environments.
Augmenting proven lower level control algorithms ...