Abstract
This paper provides details on best practices for vehicle design for BVLOS missions, with a focus on robust control links and real-time health monitoring.The development work presented herein focuses on a specific mission to set the speed and distance world record for a fully autonomous vehicle, requiring development of analytic tools for estimating vehicle range and endurance, as well as models for predicting command and control link integrity while operating BVLOS. Range and endurance estimates are developed using a novel real-time system identification algorithm onboard the vehicle for aerodynamic parameter estimation, and propulsion system characterization. Flight-testing methods and results are presented demonstrating the capabilities of these algorithms, with results from a unique test-case involving an unintended fault during the record flight. In addition to the vehicle performance assessment, Friis-based models are introduced to provide a pseudo real-time communications link range assessment. The predictive communications range models were refined using specific antenna and system characterization data measured in a compact range facility resulting in a detailed link budget useful for addressing BVLOS command and control requirements. The combination of aircraft and radio-frequency performance prediction models with supporting flight-testing techniques applied to small unmanned aerial systems provides critical insight into the design of future vehicles, and validation of existing systems tasked with performing BVLOS missions.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Atkins, E.: Autonomy as an Enabler of Economically-Viable, beyond-Line-of-Sight, Low-Altitude UAS Applications with Acceptable Risk, AUVSI Unmanned Systems, 2014
da Silva, Antonio Lamounier Soares Lira, de Carvalho Bertoli, G., Tosta, R.P., Ribeiro, M.A., and Adabo, G.J.: Beyond line-of-sight UAS communication link simulation, 2016 International Conference on Unmanned Aircraft Systems (ICUAS), IEEE, June, 2016, pp. 135–143. doi:https://doi.org/10.1109/ICUAS.2016.7502601
Gupta, S.G., Ghonge, M.M., Jawandhiya, P.: Review of unmanned aircraft system (UAS). International Journal of Advanced Research in Computer Engineering & Technology (IJARCET). 2(4), 1646–1658 (2013)
Floreano, D., Wood, R.J.: Science, technology and the future of small autonomous drones. Nature. 521(7553), 460–466 (2015). https://doi.org/10.1038/nature14542
FAA, "Part 107," Title 14, Chapter 1, Subchapter F, Part 107, Federal Aviation Administration, Washington DC, 2017
McCrink, M.H., and Gregory, J.W.: Flight test protocol for electric powered small unmanned aerial systems, AIAA Atmospheric Flight Mechanics Conference, AIAA Aviation, Atlanta, Georgia, June 2014, doi:https://doi.org/10.2514/6.2014-2814
McCrink, M.H.: Development of Flight-Test Performance Estimation Techniques for Small Unmanned Aerial Systems, Dissertation, The Ohio State University, 2015
Tavakolpour-Saleh, A., Nasib, S., Sepasyan, A., Hashemi, S.: Parametric and nonparametric system identification of an experimental turbojet engine. Aerosp. Sci. Technol. 43, 21–29 (2015)
Gu, Y.: Design and Flight Testing Actuator Failure Accommodation Controllers on WVU YF-22 Research UAVs, Dissertation, Department of Mechanical and Aerospace Engineering, West Virginia University, 2004
Ivancic, W.D., Kerczewski, R.J., Murawski, R.W., Matheou, K., and Downey, A.N.: Flying Drones Beyond Visual Line of Sight Using 4g LTE: Issues and Concerns, 2019 Integrated communications, navigation and surveillance conference (ICNS), IEEE, 2019, pp. 1–13
Stansbury, R.S., Vyas, M.A., and Wilson, T.A.: A Survey of UAS Technologies for Command, Control, and Communication (C3), Unmanned Aircraft Systems, Springer, 2008. pp. 61–78
Fédération Aéronautique Internationale, "FAI Sporting Code: Section 12 – Unmanned Aerial Vehicles, Class U," Lausanne, Switzerland, 2001
Julier, S.J., and Uhlmann, J.K.: A New Extension of the Kalman Filter to Nonlinear Systems, International Symposium on Aerospace/Defense Sensing, Simulation, and Controls, Vol. 3, Orlando, FL, 1997, pp. 182–193. doi:https://doi.org/10.1117/12.280797
Kong, X., Nebot, E.M., and Durrant-Whyte, H.: Development of a nonlinear psi-angle model for large misalignment errors and its application in INS alignment and calibration, IEEE International Conference on Robotics and Automation, Vol. 2, IEEE, 1999, pp. 1430–1435. doi:https://doi.org/10.1109/robot.1999.772561
Savage, P.G.: Strapdown inertial navigation integration algorithm design part 1: attitude algorithms. J. Guid. Control. Dyn. 21(1), 19–28 (January 1998). https://doi.org/10.2514/2.4228
Savage, P.G.: Strapdown inertial navigation integration algorithm design part 2: velocity and position algorithms. J. Guid. Control. Dyn. 21(2), 208–221 (March 1998). https://doi.org/10.2514/2.4242
Wendel, J., Maier, A., Metzger, J., and Trommer, G.: Comparison of Extended and Sigma-Point Kalman Filters for Tightly Coupled GPS/INS Integration, AIAA 2005–6055, AIAA Guidance, Navigation, and Control Conference and Exhibit, San Francisco CA, August 2005, pp. 1–15. doi:https://doi.org/10.2514/6.2005-6055
Musoff, H., Murphy, J.H.: Study of Strapdown navigation attitude algorithms. J. Guid. Control. Dyn. 18(2), 287–290 (March 1995). https://doi.org/10.2514/3.21382
Khosravian, A., Trumpf, J., Mahony, R., and Hamel, T.: Recursive attitude estimation in the presence of multi-rate and multi-delay vector measurements, 2015 American Control Conference (ACC), IEEE, 2015, pp. 3199–3205. doi:https://doi.org/10.1109/acc.2015.7171825
McCrink, M.H., and Gregory, J.W.: Aerodynamic Parameter Estimation for Derived Angle of Attack Systems, AIAA 2017–4061, AIAA Atmospheric Flight Mechanics Conference, AIAA AVIATION Forum, AIAA, Denver, CO, 2017, pp. 4061. doi:https://doi.org/10.2514/6.2017-4061
Phillips, W.F.: Mechanics of Flight. John Wiley & Sons, Hoboken (2004)
Hoerner, S.F.: Fluid-Dynamic Drag: Practical Information on Aerodynamic Drag and Hydrodynamic Resistance, 2nd edn. Hoerner Fluid Dynamics, Alburqueque (1965)
Raymer, D.P.: Aircraft Design: a Conceptual Approach, 4th edn. American Institute of Aeronautics and Astronautics, Reston (2006). https://doi.org/10.2514/4.869211
Friis, H.T.: A note on a simple transmission formula, Proceedings IRE, 34, 1946, 254–256. doi:https://doi.org/10.1109/JRPROC.1946.234568
Shaw, J.A.: Radiometry and the Friis transmission equation. Am. J. Phys. 81(1), 33–37 (2013). https://doi.org/10.1119/1.4755780
Hristov, H.D.: Fresnal Zones in Wireless Links, Zone Plate Lenses and Antennas, Artech House, Inc., 2000. pp. 345
Morelli, E.A., Klein, V.: Accuracy of aerodynamic model parameters estimated from flight test data. J. Guid. Control. Dyn. 20(1), 74–80 (1997). https://doi.org/10.2514/2.3997
Murphy, P.C., and Brandon, J.: Efficient Testing Combining Design of Experiment and Learn-to-fly Strategies, AIAA 2017–0696, AIAA Atmospheric Flight Mechanics Conference, AIAA, Grapevine, TX, 2017, pp. 1–21. doi:https://doi.org/10.2514/6.2017-0696
Kimberlin, R.D.: Flight testing of fixed-wing aircraft, American Institute of Aeronautics and Astronautics, Reston, VA, January 2003. doi:https://doi.org/10.2514/4.861840
Woolf, R.K.: Applications of Statistically Defensible Test and Evaluation Methods to Aircraft Performance Flight Testing, AIAA 2012–2723, 28th Aerodynamic Measurement Technology, Ground Testing, and Flight Testing Conference, New Orleans LA, June 2012, pp. 1–15. doi:https://doi.org/10.2514/6.2012-2723
Lane, S.H., Stengel, R.F.: Flight control design using non-linear inverse dynamics. Automatica. 24(4), 471–483 (1988). https://doi.org/10.1016/0005-1098(88)90092-1
Reiner, J., Balas, G.J., Garrard, W.L.: Robust dynamic inversion for control of highly maneuverable aircraft. J. Guid. Control. Dyn. 18(1), 18–24 (1995). https://doi.org/10.2514/3.56651
Singh, S., and Padhi, R.: Automatic Path Planning and Control Design for Autonomous Landing of UAVs Using Dynamic Inversion, American Control Conference, IEEE, 2009, pp. 2409–2414. doi:https://doi.org/10.1109/acc.2009.5160444
Sieberling, S., Chu, Q., and Mulder, J.: Robust flight control using incremental nonlinear dynamic inversion and angular acceleration prediction, Journal of Guidance, Control, and Dynamics, Vol. 33, No. 6, 2010, pp. 1732. doi:https://doi.org/10.2514/1.49978
Sujit, P., Saripalli, S., Sousa, J.B.: Unmanned aerial vehicle path following: a survey and analysis of algorithms for fixed-wing unmanned aerial vehicles. IEEE Control. Syst. 34(1), 42–59 (2014). https://doi.org/10.1109/mcs.2013.2287568
Grauer, J., and Morelli, E.A.: Real-Time Frequency Response Estimation Using Multi-Sine Inputs and Recursive Fourier Transform, AIAA Atmospheric Flight Mechanics Conference, AIAA 2012–4409, Minneapolis, Minnesota, 2012, pp. 1–16. doi:https://doi.org/10.2514/6.2012-4409
Acknowledgments
The authors wish to thank Ligado Networks (Mike Gagne, Sam Welch, David Nance, and Illya Ziskind) for their generous donations in time and resources for the satellite communication system. Additionally, the students of the Aerospace Research Center UAS Laboratory at the Ohio State University, Ross Heidersbach, Rokhaya Diawara, Madhav Shah, and Braxton Harter, assisted with aircraft fabrication and renovation. The ground crew during flight operations was Daniel Applebaum, Ryan Thorpe, Mark Sutkowy, and Wenbo Zhu. And finally, we wish to thank the chase plane crew of Ryan Smith, Jamie Struewing, and Ross Heidersbach.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
McCrink, M.H., Gregory, J.W. Design and Development of a High-Speed UAS for beyond Visual Line-of-Sight Operations. J Intell Robot Syst 101, 31 (2021). https://doi.org/10.1007/s10846-020-01300-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10846-020-01300-2