Active control of turbulence-induced helicopter vibration

Anderson, David (1999) Active control of turbulence-induced helicopter vibration. PhD thesis, University of Glasgow.

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Helicopter vibration signatures induced by severe atmospheric turbulence have been shown to differ considerably from nominal, still air vibration. The perturbations of the transmission frequency have significant implications for the design of passive and active vibration alleviation devices, which are generally tuned to the nominal vibration frequency. This thesis investigates the existence of the phenomena in several realistic atmospheric turbulence environments, generated using Computational Fluid Dynamic (CFD) engineering software and assimilated within a high-fidelity rotorcraft simulation, RASCAL. The RASCAL simulation is modified to calculate blade element sampling of the gust, enabling thorough, high frequency analyses of the rotor response. In a final modification, a numerical, integration-based inverse simulation algorithm, GENISA is incorporated and the augmented simulation is henceforth referred to as HISAT. Several implementation issues arise from the symbiosis, principally because of the modelling of variable rotorspeed and lead-lag motion. However, a novel technique for increasing the numerical stability margins is proposed and tested successfully.

Two active vibration control schemes, higher harmonic control 'HHC' and individual blade control 'IBC', are then evaluated against a 'worst-case' sharp-edged gust field. The higher harmonic controller demonstrates a worrying lack of robustness, and actually begins to contribute to the vibration levels. Several intuitive modifications to the algorithm are proposed but only disturbance estimation is successful. A new simulation model of coupled blade motion is derived and implemented using MATLAB and is used to design a simple IBC compensator. Following bandwidth problems, a redesign is proposed using H theory which improves the controller performance. Disturbance prediction/estimation is attempted using artificial neural networks to limited success. Overall, the aims and objectives of the research are met.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Subjects: T Technology > TL Motor vehicles. Aeronautics. Astronautics
Colleges/Schools: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
Supervisor's Name: Houston, Dr. Stewart
Date of Award: 1999
Depositing User: Elaine Ballantyne
Unique ID: glathesis:1999-2175
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 12 Oct 2010
Last Modified: 10 Dec 2012 13:52

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