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Texas A&M University College of Engineering

Research

Our research is focused on bridging the scientific gaps between traditional computer science topics and aerospace engineering topics, while achieving a high degree of closure between theory and experiment.  We focus on machine learning and multi-agent systems, intelligent autonomous control, nonlinear control theory, vision based navigation systems, fault tolerant adaptive control, and cockpit systems and displays.  What sets our work apart is a unique systems approach and an ability to seamlessly integrate different disciplines such as dynamics & control, artificial intelligence, and bio-inspiration.  Our body of work integrates these disciplines, creating a lasting impact on technical communities from smart materials to General Aviation flight safety to Unmanned Air Systems (UAS) to guidance, navigation & control theory.  Our research has been funded by AFOSR, ARO, ONR, AFRL, ARL, AFC, NSF, NASA, FAA, and industry.

Autonomous and Nonlinear Control of Cyber-Physical Air, Space and Ground Systems

Vision Based Sensors and Navigation Systems

Cybersecurity for Air and Space Vehicles

Air Vehicle Control and Management

Space Vehicle Control and Management

Advanced Cockpit/UAS Systems and Displays

Control of Bio-Nano Materials and Structures

Simulation

Optimal Six Degree-of-Freedom Maneuver Command Generator and Simulator Tools for Aircraft

L-3 Communications, Integrated Systems
15 February – 31 December 2009
Total award $89,000

The proposed work seeks to conduct applied research to support current and future L-3 IS goals in the area of trajectory design and generation. The focus of this work will be on investigating and implementing practical techniques for designing control inputs for complex aircraft trajectories, with an emphasis on evaluating dynamic loads and system identification. The objectives of the proposed effort are three fold. The first objective is to develop a MATLAB/SIMULINK flight simulation framework applicable to conventional transport airplane types. The second objective is to develop a simulated pilot that can be used for performing maneuvering flight and handling qualities analyses. The third objective is to develop methods for system identification using flight test data. Establishing a structured framework for aircraft data that will provide for modeling of a variety of transport aircraft types will facilitate new simulation developments. This effort will define an organized approach for defining, inputting and assembling the data needed for flight simulation.

Working with me on this program is Graduate Research Assistant:

  • Jim May, M.S. student

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