Improvement of Shipboard Landing Performance of Fixed-wing UAV Using Model Predictive Control

  • Soyeon Koo
  • Seungkeun KimEmail author
  • Jinyoung Suk
  • Youdan Kim
  • Jongho Shin
Regular Papers Control Theory and Applications


This paper investigates automatic UAV carrier landing using model predictive control that considers carrier deck motions. With dynamic models of a medium-altitude, long-endurance UAV and an aircraft carrier, the proposed guidance and control approach takes the relative geometry between the UAV and the carrier deck into account for safer shipboard landings. Automatic carrier landing is performed sequentially by two types of control systems. A linear quadratic regulator with an integral term is applied up to a few seconds before touchdown followed by a model predictive controller. At this time, optimal control input sequences over a certain time horizon are calculated in real time by predicting the motions of the carrier deck and the UAV. Numerical simulations are performed for a UAV and a carrier with heave motion to verify the feasibility of the proposed approach.


Automatic carrier landing linear quadratic tracker with integral model predictive control unmanned aerial vehicles 


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  1. [1]
    US Navy, “X-47b makes first arrested landing at sea,” http: //, July 10, 2013.Google Scholar
  2. [2]
    J. Whittenbury, “Configuration design development of the navy ucas-d x-47b,” AIAA Centennial of Naval Aviation Forum" 100 Years of Achievement and Progress, p. 7041, 2011.Google Scholar
  3. [3]
    D. Smith, One Hundred Years of US Navy Air Power, Naval Institute Press, 2013.Google Scholar
  4. [4]
    BBC News, “US unmanned drone jet makes first carrier landing,”, 2013.Google Scholar
  5. [5]
    M. Steinberg and A. Page, “A comparison of neural, fuzzy, evolutionary, and adaptive approaches for carrier landing,” Tech. Rep., DTIC Document, 2001.Google Scholar
  6. [6]
    N. A. Denison, “Automated carrier landing of an unmanned combat aerial vehicle using dynamic inversion,” Tech. Rep., DTIC Document, 2007.Google Scholar
  7. [7]
    Y. Zhang, Y. Yang, and Y. Yu, “Integrated flight thrust control via LMI-based H¥ synthesis in automatic carrier landing system,” Proc. of International Conference on Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, vol. 1, pp. 1147–1152, IEEE, 2005.Google Scholar
  8. [8]
    Y. Kang and J. K. Hedrick, “Linear tracking for a fixedwing uav using nonlinear model predictive control,” IEEE Transactions on Control Systems Technology, vol. 17, no. 5, pp. 1202–1210, 2009.CrossRefGoogle Scholar
  9. [9]
    Z. Chao, S.-L. Zhou, L. Ming, and W.-G. Zhang, “UAV formation flight based on nonlinear model predictive control,” Mathematical Problems in Engineering, vol. 2012, 2012.Google Scholar
  10. [10]
    M. Iskandarani, S. Givigi, G. Fusina, and A. Beaulieu, “Unmanned aerial vehicle formation flying using linear model predictive control,” Proc. of 8th Annual IEEE Systems Conference (SysCon), pp. 18–23, IEEE, 2014.Google Scholar
  11. [11]
    S. Kim, H. Oh, and A. Tsourdos, “Nonlinear model predictive coordinated standoff tracking of a moving ground vehicle,” Journal of Guidance, Control, and Dynamics, vol. 36, no. 2, pp. 557–566, 2013.CrossRefGoogle Scholar
  12. [12]
    J. A. de Bonfim Gripp and U. P. Sampaio, “Automatic landing of a uav using model predictive control for the surveillance of internal autopilot’s controls,” Proc. of International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1219–1224, IEEE, 2014.Google Scholar
  13. [13]
    J. Boskovic and J. Redding, “An autonomous carrier landing system for unmannned aerial vehicles,” Proc. of AIAA Guidance, Navigation, and Control Conference, p. 6264, 2009.Google Scholar
  14. [14]
    S. Koo, D. Lee, K. Kim, C.-G. Ra, S. Kim, and J. Suk, “Guidance and control system design for automatic carrier landing of a UAV,” Journal of Institute of Control, Robotics and Systems, vol. 20, no. 11, pp. 1085–1091, 2014.CrossRefGoogle Scholar
  15. [15]
    M. Triantafyllou, M. Bodson, and M. Athans, “Real time estimation of ship motions using kalman filtering techniques,” IEEE Journal of Oceanic Engineering, vol. 8, no. 1, pp. 9–20, 1983.CrossRefGoogle Scholar
  16. [16]
    “Marine systems simulator (MSS).” http://www., Accessed: 2017-01-23.Google Scholar
  17. [17]
    N88-NTSP-A-50-8622D/D, “Navy training system plan for the pioneer unmanned aerial vehicle system,” Tech. Rep., US Navy, 1999.Google Scholar
  18. [18]
    “RUAG.”, Accessed: 2017-01-23.Google Scholar
  19. [19]
    C. M. Deppe and T. Benedik, “Joint precision approach and landing system (JPALS),” 2007.Google Scholar
  20. [20]
    B. L. Stevens, F. L. Lewis, and E. N. Johnson, Aircraft Control and Simulation: Dynamics, Controls Design, and Autonomous Systems, John Wiley & Sons, 2015.CrossRefGoogle Scholar
  21. [21]
    J. Jeong, S. Kim, and J. Suk, “Control system design for a ducted-fan unmanned aerial vehicle using linear quadratic tracker,” International Journal of Aerospace Engineering, vol. 2015, 2015.Google Scholar
  22. [22]
    Z. Lin, Q. Yang, Z. Guo, and J. Li, “An improved autoregressive method with kalman filtering theory for vessel motion predication,” International Journal of Intelligent Engineering and Systems, vol. 4, no. 4, 2011.Google Scholar

Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Soyeon Koo
    • 1
  • Seungkeun Kim
    • 2
    Email author
  • Jinyoung Suk
    • 2
  • Youdan Kim
    • 3
  • Jongho Shin
    • 4
  1. 1.Korea Aerospace Industries, LTD.Sacheon, Gyeongsangnam-doKorea
  2. 2.Department of Aerospace EngineeringChungnam National UniversityDaejeonRepublic of Korea
  3. 3.School of Mechanical and Aerospace Engineering, Institute of Advanced Aerospace TechnologySeoul National UniversitySeoulKorea
  4. 4.5th R&D Institute 2nd Directorate at Agency for Defense DevelopmentDaejeonKorea

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