This paper describes a novel multirotor unmanned aerial vehicle aerodynamic force model with the aim of creating a multirotor simulation that is suitable for the evaluation of station-keeping performance in turbulent wind. It fills the gap between simple models that ignore important aerodynamic effects and other more comprehensive but computationally expensive models. The model is synthesized from static wind tunnel test data and accounts for variations in angular rotor speed, apparent wind speed, and angle of attack on the vehicle’s rotors. Experimental validation is performed through indoor free-flight pitch step responses. On average, the simulated root mean square pitch tracking error is found to be within 31% of the experiment. The usefulness of the whole system to determine station-keeping performance is assessed by free-flight station-keeping experiments in a wind tunnel environment. The tracking error along all three axes is found to increase with increasing mean wind speed. The simulated standard deviation of errors along the wind direction is on average within 7% of the experiment, whereas those of the errors along axes perpendicular to the wind direction are found to be within 56%. Overall trends are similar in all cases, making the model suitable for performance comparisons of flight controllers.

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Copyright © 2018 by Jérémie X. J. Bannwarth, Z. Jeremy Chen, Karl A. Stol, Bruce A. MacDonald, and Peter J. Richards. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com; employ the ISSN 0001-1452 (print) or 1533-385X (online) to initiate your request. See also AIAA Rights and Permissions www.aiaa.org/randp.

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Acknowledgments

This research was made possible thanks to a University of Auckland Doctoral Scholarship and a Faculty Research Development Fund Grant. The authors thank the University of Auckland’s Aerodynamics Laboratory staff for their help operating the wind tunnel and Nick Velychko in particular for providing the logging software used for the static experiments.

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Received4 March 2018
Accepted17 October 2018
Published online27 December 2018

Aerodynamic Force Modeling of Multirotor Unmanned Aerial Vehicles

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