Browsing by Author "Gresham, James L."

Now showing 1 - 6 of 6
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    Experimental Validation of Port-Hamiltonian-Based Control for Fixed-Wing Unmanned Aircraft
    Fahmi, Jean-Michel W.; Gresham, James L.; Woolsey, Craig A. (American Institute of Aeronautics and Astronautics, 2023-06)
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    Flight-Test System Identification Techniques and Applications for Small, Low-Cost, Fixed-Wing Aircraft
    Simmons, Benjamin M.; Gresham, James L.; Woolsey, Craig A. (American Institute of Aeronautics and Astronautics, 2023-09)
    This paper provides an overview of flight-test system identification methods applied in the Virginia Tech Nonlinear Systems Laboratory that focus on modeling small, inexpensive, fixed-wing aircraft controlled by a ground-based pilot. The general aircraft system identification approach is outlined with details provided on the flight-test facilities, experiment design methods, instrumentation systems, flight-test operations, data processing techniques, and model identification methods enabling small aircraft flight dynamics model development. Specific small aircraft system identification challenges are overcome, including low-cost control surface servo-actuators and instrumentation systems, as well as a greater sensitivity to atmospheric disturbances and limited piloting cues. Four recent system identification research advancements using the general system identification process are featured, including application of uncorrelated pilot inputs for remotely piloted aircraft, aero-propulsive model development for propeller aircraft, spin aerodynamic model development, and nonlinear dynamic modeling without mass properties information. Although this paper provides a summary of several research efforts, the core system identification approach is presented with sufficient detail to allow the methods to be readily adapted to other research efforts leveraging small, low-cost aircraft.
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    Nonlinear Dynamic Modeling for Aircraft with Unknown Mass Properties Using Flight Data
    Simmons, Benjamin M.; Gresham, James L.; Woolsey, Craig A. (American Institute of Aeronautics and Astronautics, 2023-05)
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    Remote Uncorrelated Pilot Input Excitation Assessment for Unmanned Aircraft Aerodynamic Modeling
    Gresham, James L.; Simmons, Benjamin M.; Fahmi, Jean-Michel W.; Hopwood, Jeremy W.; Woolsey, Craig A. (American Institute of Aeronautics and Astronautics, 2023-05)
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    Robust Stall Spin Flight Path Control with Flight Test Validation
    Hopwood, Jeremy W.; Gresham, James L.; Woolsey, Craig A. (American Institute of Aeronautics and Astronautics, 2023-03)
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    Spin Aerodynamic Modeling for a Fixed-Wing Aircraft Using Flight Data
    Gresham, James L.; Simmons, Benjamin M.; Hopwood, Jeremy W.; Woolsey, Craig A. (American Institute of Aeronautics and Astronautics, 2024-01)
    Novel techniques are used to identify a nonlinear, quasi-steady, coupled, spin aerodynamic model for a fixed-wing aircraft from flight-test data. Orthogonal phase-optimized multisine inputs are used as excitation signals while collecting spinning flight data. A novel vector decomposition of explanatory variables leads to an elegant model structure for spin flight data analysis. Results show good agreement between model predictions and validation flight data. This effort is motivated by interest in developing a flight termination system for a fixed-wing unmanned aircraft that controls a descending spiral trajectory flight path toward a designated impact area. While investigating the feasibility of a robust control method to guide the spinning trajectory, it was helpful to compare a level flight dynamic model with one of the aircraft dynamics and control authority in the neighborhood of a stable, oscillatory spin. In this paper, a nominal flight aerodynamic model is developed and compared to the stall spin model and the spin model outperforms the nominal model for spinning flight.