Organizational Unit:

Daniel Guggenheim School of Aerospace Engineering

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https://hdl.handle.net/1853/70742

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College of Engineering

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Aerospace Design Group

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Aerospace Systems Design Laboratory (ASDL)

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Air Transportation Laboratory

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Cognitive Engineering Center

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Space Systems Design Laboratory (SSDL)

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https://finding-aids.library.gatech.edu/agents/corporate_entities/106

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Publication Search Results

Now showing 1 - 10 of 157

Flight Test Validation of a Neural Network based Long Term Learning Adaptive Flight Controller

(Georgia Institute of Technology, 2009-08) Chowdhary, Girish ; Johnson, Eric N.

The purpose of this paper is to present and analyze flight test results of a Long Term Learning Adaptive Flight Controller implemented on a rotorcraft and a fixed wing Unmanned Aerial Vehicle. The adaptive control architecture used is based on a proven Model Reference Adaptive Control (MRAC) architecture employing a Neural Network as the adaptive element. The method employed for training the Neural Network for these flight tests is unique since it uses current (online) as well as stored (background) information concurrently for adaptation. This ability allows the adaptive element to simulate long term memory by retaining specifically stored input output data pairs and using them for concurrent adaptation. Furthermore, the structure of the adaptive law ensures that concurrent training on past data does not affect the responsiveness of the adaptive element to current data. The results show that the concurrent use of current and background data does not affect the practical stability properties of the MRAC control architecture. The results also confirm expected improvements in performance.
Vortex Model Based Adaptive Flight Control Using Synthetic Jets

(Georgia Institute of Technology, 2009-08) Muse, Jonathan A. ; Tchieu, Andrew A. ; Kutay, Ali T. ; Chaundramohan, Rajeev ; Leonard, Anthony

A simple low-order model is derived for developing flight control laws for controlling the longitudinal dynamics of an aircraft using synthetic jet type actuators. Bi-directional changes in the pitching moment over a range of angles of attack are effected by controllable, nominally-symmetric trapped vorticity concentrations on both the suction and pressure surfaces near the trailing edge. Actuation is applied on both surfaces by hybrid actuators that are each comprised of a miniature obstruction integrated with a synthetic jet actuator to manipulate and regulate the vorticity concentrations. In previous work, a simple model was derived from a reduced order vortex model that includes one explicit nonlinear state for fluid variables and can be easily coupled to the rigid body dynamics of an aircraft. This paper further simplifies this model for control design. The control design is based on an output feedback adaptive control methodology that illustrates the effectiveness of using the model for achieving flight control at a higher bandwidth than achievable with typical static actuator assumptions. A unique feature of the control design is that the control variable is a pseudo-control based on regulating a control vortex strength. Wind tunnel experiments on a unique dynamics traverse verify that tracking performance is indeed better than control designs employing standard actuator modeling assumptions.
Real-Time System Identification of a Small Multi-Engine Aircraft

(Georgia Institute of Technology, 2009-08) DeBusk, Wesley M. ; Chowdhary, Girish ; Johnson, Eric N.

In-flight identification of an aircraft's dynamic model can benefit adaptive control schemes by providing estimates of aerodynamic stability derivatives in real time. This information is useful when the dynamic model changes severely in flight such as when faults and failures occur. Moreover a continuously updating model of the aircraft dynamics can be used to monitor the performance of onboard controllers. Flight test data was collected using a sum of sines input implemented in closed loop on a twin engine, fixed wing, Unmanned Aerial Vehicle. This data has been used to estimate a complete six degree of freedom aircraft linear model using the recursive Fourier Transform Regression method in frequency domain. The methods presented in this paper have been successfully validated using computer simulation and real flight data. This paper shows the feasibility of using the frequency domain Fourier Transform Regression method for real time parameter identification.
3D Obstacle Detection Using a Single Camera

(Georgia Institute of Technology, 2009-08) Shah, Syed Irtiza Ali ; Johnson, Eric N.

This paper aims at detecting obstacles using a single camera in an unknown three dimensional world, for 3D motion of an unmanned air vehicle. Obstacle detection is a pre-requisite for collision-free motion of a UAV through 3D space. Most research towards vision based obstacle detection and avoidance has been done for 2D planar motion of ground robots and using active sensors like laser range finders, sonar, radar etc. Passive camera based research has mostly been done, either using stereo vision (multiple cameras) or, by developing a prior expectation map of the world and its comparison with the new image data. In this paper, an attempt has been made to find a 3D solution of the obstacle detection problem using a single camera in an unknown world. The equations developed and the simulations results presented here, show that a 3D model of the scene can be generated from 2D image information from a single camera flying through a very small arc of lateral flight around the object, without the need of capturing images from all sides as in a typical 'structures from motion' problem. The forward flight simulation results show that the depth extracted from forward motion is in fact usable for large part of the image, which is a significant contribution of this work.
Indoor Navigation for Unmanned Aerial Vehicles

(Georgia Institute of Technology, 2009-08) Sobers, D. Michael Jr. ; Chowdhary, Girish ; Johnson, Eric N.

The ability for vehicles to navigate unknown environments is critical for autonomous operation. Mapping of a vehicle's environment and self-localization within that environ- ment are especially difficult for an Unmanned Aerial Vehicle (UAV) due to the complexity of UAV attitude and motion dynamics, as well as interference from external influences such as wind. By using a stable vehicle platform and taking advantage of the geometric structure typical of most indoor environments, the complexity of the localization and mapping problem can be reduced. Interior wall and obstacle location can be measured using low-cost range sensors. Relative vehicle location within the mapped environment can then be determined. By alternating between mapping and localization, a vehicle can explore its environment autonomously. This paper examines available low-cost range sensors for suitability in solving the mapping and localization problem. A control system and navigation algorithm are developed to perform mapping of indoor environments and localization. Simulation and experimental results are provided to determine feasibility of the proposed approach to indoor navigation.
Georgia Tech Aerial Robotics Team: 2009 International Aerial Robotics Competition Entry

(Georgia Institute of Technology, 2009-07) Chowdhary, Girish ; Christmann, Hans Claus ; Johnson, Eric N. ; Salaün, Erwan ; Sobers, D. Michael Jr.

This paper examines the use of low-cost range and target identification sensors on a stable flying vehicle for suitability in solving the 5th Mission proposed for the 2009 International Aerial Robotics Competition. The ability for vehicles to navigate unknown environments is critical for autonomous operation. Mapping of a vehicle's environment and self-localization within that environment are especially difficult for an Unmanned Aerial Vehicle (UAV) due to the complexity of UAV attitude and motion dynamics. Using a stable vehicle platform and taking advantage of the geometric structure typical of most indoor environments reduces the complexity of the localization and mapping problem to the point that wall and obstacle location can be determined using low-cost range sensors. Target identification is accomplished remotely using an onboard video camera with a radio transmitter. Thus complex and time-consuming image processing routines are run on a more powerful computer, enabling further miniaturization of the flight vehicle.
An LMI-based Stability Analysis for Adaptive Controllers

(Georgia Institute of Technology, 2009-06) Yang, Bong-Jun ; Yucelen, Tansel ; Calise, Anthony J. ; Shin, Jong-Yeob

We develop a Linear Matrix Inequality (LMI) tool for analyzing the stability and performance of adaptive controllers that employ σ−modification. The formulation involves recasting the error dynamics composed of the tracking error and the weight estimator error into a linear parameter varying form. We show how stability, convergence rate, domain of attraction, and the transient and steady state behavior of the adaptive control system can be analyzed using the developed LMI tool. It is guaranteed that less conservative estimates for the convergence rate and the size of the ultimate bound for the tracking error are obtained compared to the standard analysis in the literature.
Modeling Cockpit Interface Usage During Lunar Landing Redesignation

(Georgia Institute of Technology, 2009) Chua, Zarrin K. ; Major, Laura M. ; Feigh, Karen M.

Fulfilling NASA's space exploration objectives requires precision landing to reach lunar sites of interest. During the approach and landing stages, a landing point redesignation (LPR) display will provide information to the crew regarding the characteristics of alternate touchdown points. Building on a previous study which examined crew tasks during LPR but did not account for the specialized behavior of experts, this investigation will present a new task sequence model, specific to expert decision-making. This analysis furthers the development of a predictive task execution model, which is used to test the efficacy of alternate information display and operator actuator design concepts. The task model and cockpit display recommendations presented in this study provide a significant improvement in LPR task execution time. This paper examines the task sequence during lunar landing, describes the predictive task execution process model, and recommends cockpit display requirements for effective decision making.
Methods for Localization and Mapping Using Vision and Inertial Sensors

(Georgia Institute of Technology, 2008-08) Wu, Allen D. ; Johnson, Eric N.

The problems of vision-based localization and mapping are currently highly active areas of research for aerial systems. With a wealth of information available in each image, vision sensors allow vehicles to gather data about their surrounding environment in addition to inferring own-ship information. However, algorithms for processing camera images are often cumbersome for the limited computational power available onboard many unmanned aerial systems. This paper therefore investigates a method for incorporating an inertial measurement unit together with a monocular vision sensor to aid in the extraction of information from camera images, and hence reduce the computational burden for this class of platforms. Feature points are detected in each image using a Harris corner detector, and these feature measurements are statistically corresponded across each captured image using knowledge of the vehicle's pose. The investigated methods employ an Extended Kalman Filter framework for estimation. Real-time hardware results are presented using a baseline configuration in which a manufactured target is used for generating salient feature points, and vehicle pose information is provided by a high precision motion capture system for comparison purposes.
UAS Reference Scenarios for MANET Development

(Georgia Institute of Technology, 2008-08) Christmann, Hans Claus ; Johnson, Eric N.

After autonomous flight for Unmanned Aerial Vehicles (UAVs) has been accomplished, research was stipulated to look into application related challenges in connection with Unmanned Aerial Systems (UAS). As one possible scenario, swarms of collaborating UAVs can be envisioned and allow for more complex missions and scenarios. One essential building block in simultaneously operating several UAVs is the UAS internal and external communication. Ground control station operators need to communicate guidance, navigation, and control (GNC) data, external beneficiaries of the UAS operation need to be provided with obtained sensor data and intelligence. All this requires sophisticated wireless communication networks and Mobile Ad-hoc Networks (MANETs) step into the picture. However, evaluating the performance of different MANETs in a UAS environment is non-trivial: relevant metrics and evaluation procedures have to be established for a simulation based performance prediction during the design phase of a MANET. Unfortunately, published results on MANET performance are not necessarily comparable across different papers, due to differences in the underlying assumptions. Some findings might not even be applicable to a UAS environment. This paper proposes a set of reference scenarios in order to allow for comparable and applicable results in MANET simulations. The presented scenarios mimic realistic UAS missions, both, on the operational side of the participating network nodes, as well as on the network traffic side. The reference scenarios capture the essence of current UAVs and UAS missions in a civil, research, or military context, hence providing the means to simulate different MANET protocols in a UAS setting.