TY - GEN
T1 - Propeller phase synchronization for small distributed electric vehicles
AU - Patterson, Andrew
AU - Gahlawat, Aditya
AU - Hovakimyan, Naira
N1 - Funding Information:
This work is supported by the National Aeronautics and Space Administration (NASA). The authors would like to thank Dr. Kyle Pascioni, Dr. Noah Schiller, and Dr. Stephen Rizzi of the NASA Langley Structural Acoustics Branch for their guidance on their acoustic models. Further, the authors would like to thank Dr. Irene Gregory and Kasey Ackerman of the NASA Lagley Dynamic Systems and Control Branch for their discussions on the GL-10 platform and suggestions on the testbed mechanical design. Finally, the authors thank Daniel Block of the University of Illinois for his contributions to the testbed electronic design.
Publisher Copyright:
© 2019 by Timothy K. Minton. Published by the American Institute of Aeronautics and Astronautics, Inc.
PY - 2019
Y1 - 2019
N2 - Noise restrictions are imposed on aircraft flying over urban environments to reduce annoy-ance and health problems. These restrictions are predicted to be a limiting factor in unmanned aerial vehicle (UAV) deployment, particularly in the target application of urban transportation. This paper presents the design, analysis and experimental results for a propeller phase synchronization algorithm for noise reduction in UAVs with distributed electric propulsion. The propeller phase, for each propeller, is the difference between a common virtual propeller position and the real propeller position. To verify the controller performance, a testbed is designed based on the NASA GL-10 demonstration aircraft. To meet the performance requirements in steady-state, the motor dynamics are identified and the controller is designed based on this model. The designed controller is then tested in simulation with realistic time delays, sensor errors and noise models. The controller is verified on the testbed, and the performance is quantified in terms of the mean and standard deviation of the steady-state phase error. For the range of motor speeds typical of the chosen UAV, the steady-state performance is shown to be suitable for sound suppression, with phase regulation errors less than 5◦ from a virtual phase target. These results are promising for noise reduction applications in urban transportation with distributed electric propulsion UAVs. In addition to static tests, the transient and steady-state tracking of the controller are demonstrated on the testbed to motivate future work for dynamic noise cancellation methods.
AB - Noise restrictions are imposed on aircraft flying over urban environments to reduce annoy-ance and health problems. These restrictions are predicted to be a limiting factor in unmanned aerial vehicle (UAV) deployment, particularly in the target application of urban transportation. This paper presents the design, analysis and experimental results for a propeller phase synchronization algorithm for noise reduction in UAVs with distributed electric propulsion. The propeller phase, for each propeller, is the difference between a common virtual propeller position and the real propeller position. To verify the controller performance, a testbed is designed based on the NASA GL-10 demonstration aircraft. To meet the performance requirements in steady-state, the motor dynamics are identified and the controller is designed based on this model. The designed controller is then tested in simulation with realistic time delays, sensor errors and noise models. The controller is verified on the testbed, and the performance is quantified in terms of the mean and standard deviation of the steady-state phase error. For the range of motor speeds typical of the chosen UAV, the steady-state performance is shown to be suitable for sound suppression, with phase regulation errors less than 5◦ from a virtual phase target. These results are promising for noise reduction applications in urban transportation with distributed electric propulsion UAVs. In addition to static tests, the transient and steady-state tracking of the controller are demonstrated on the testbed to motivate future work for dynamic noise cancellation methods.
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U2 - 10.2514/6.2019-1458
DO - 10.2514/6.2019-1458
M3 - Conference contribution
AN - SCOPUS:85083944004
SN - 9781624105784
T3 - AIAA Scitech 2019 Forum
BT - AIAA Scitech 2019 Forum
PB - American Institute of Aeronautics and Astronautics Inc, AIAA
T2 - AIAA Scitech Forum, 2019
Y2 - 7 January 2019 through 11 January 2019
ER -