An Aeroservoelastic Flapping Flexible Wing Model August 2, 2010Posted by thelifeexamined in Code.
Tags: aeroservoelasticity, Code, flapping wings
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An aeroservoelastic flapping flexible wing model has been created from experimental data obtained at the University of Florida to support the ideal of reproducible research. Please cite the paper below if you choose to use this model.
Love, R. and Lind, R. “Experimentally-Based Aeroservoelastic System Identification and Feedforward Control of Flexible Flapping Wings“, AIAA Atmospheric Flight Mechanics Conference, 2010.
The model takes inputs of flapping amplitude and flapping frequency to produce a simulation of the aeroservoelastic flapping based on experimental results. Download the zip file and run “WingModel.m” in Matlab. Feel free to try your own inputs for flapping amplitude and flapping frequency (it is initially set for +/-35 degree amplitude and 20Hz)! Please note that work is still in progress to model the exact flexible deformations. Please feel free to contact me if you have any issues after you’ve tried to figure it out yourself. Enjoy!
Update 8/26/2010: A newer, higher fidelity model which captures the wing flexibility has been formulated. Look for this to be published in the near future!
SIGVIZ: Time History, Fourier Transform and Wavelet Transform Analysis September 30, 2009Posted by thelifeexamined in Code.
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The Matlab Code SIGVIZ provides a quick way to visualize the Time history, Discrete Fourier Transform and Wavelet Transform (using the Morlet wavelet). This code should be useful for the analysis of systems with time and frequency dependent dynamics.
Initial investigations of flapping wing vehicles have demonstrated several characteristics in which wavelet analysis might prove useful. These include the presence of time-varying vortices, unknown time and frequency dependent lags in the system, and structural resonance while flapping. These features were demonstrated in the paper Time-Frequency Analysis of Aeroelastic Deflections of Flapping Wings (R. Love, R. Lind, AIAA ASM 2009).
2. Run simpleexample.m (Example: simple 20Hz sinusoid) to understand the effects of changing the various input parameters.
3. Modify simpleexample.m to include your input signal and corresponding time vector.