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Matthew Wilbur

Publications and source records attributed to Matthew Wilbur.

2 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Initial Characterization of the TiltRotor Aeroelastic Stability Testbed

This paper discusses the initial wind tunnel test of the TiltRotor Aeroelastic Stability Testbed (TRAST). TRAST is a generic tiltrotor testbed developed in collaboration between NASA and the Army. Ultimately, this test was a checkout of the model systems, functionality and familiarization, but also obtained subcritical whirl-flutter data in the terms of frequency and damping. Flutter data include two main configurations with different pitch spring stiffness, referred to as 4k and 8k, that were tested at various rotor speeds and airspeeds at the NASA Langley Transonic Dynamics Tunnel. The test included two modes of drivetrain operation: powered and windmilling. However, powered mode of operation was only conducted with the 8k pitch spring. This test reinforced the traditional knowledge of whirl-flutter trends such as flutter speed would decrease with an increase in rotor speed. The critical mode consistently being the wing vertical bending mode. The chord mode as expected was not affected by the pitch spring and was likely to go unstable at a tunnel airspeed slightly beyond the wing vertical bending mode. There were also test specific challenges such as the TRAST modal damping was more sensitive to temperature and amplitude motor than was expected. This test gathered valuable data on the baseline characterization of TRAST, how to improve the model and test practices for future wind tunnel testing. Additionally, a new more automated method for experimental subcritical damping determination based on the Stockwell transform has been demonstrated that may lead to more consistent whirl-flutter stability boundaries.

whirl flutter↗
NASA NTRSDate not supplied

Experimental Testing of Advanced Generalized Predictive Control for Stability Augmentation and Vibration Reduction of Tiltrotor Aircraft

Generalized Predictive Control (GPC) is an advanced form of an adaptive control algorithm that uses experimentally acquired data to determine the input-output relationship of complex systems through a process called system identification (system ID). GPC has historically been applied to wind tunnel tests of dynamically-scaled tiltrotor aircraft for stability augmentation and vibration reduction since the complex nature of these dynamic systems does not lend itself well to traditional control theory. Advanced GPC (AGPC) improves upon traditional GPC by enabling self-adaptation as conditions change from those used to acquire the system ID and controller performance would normally erode. The present research expands upon previous analytical development and demonstration of AGPC with experimental demonstration. To support AGPC, this present work also identifies and describes figures of merit that define a good working controller and quantifies the uniqueness of the control inputs and quality of the system ID parameters. The present research demonstrates that AGPC consistently performs better than traditional GPC and can successfully adapt to changing conditions.

Active Controls↗