Autors: Mesbah A., Roshanian J., Ginchev, D. G.
Title: A control barrier function-based approach for safe autonomous landing
Keywords:

Abstract: In recent years, the application of rigorous formal methods for guaranteeing the safety of control systems has received a great deal of interest in the control engineering community and become a subject of active, cutting-edge research. One such popular method of formal safety is that of control barrier functions (CBFs). CBFs whose functionality is based on Nagumo's theorem of invariance could be implemented in control systems using online optimization to serve as safety filters that - when needed - make modifications to the primary control signal to prevent unsafe behavior. Since their popularization in the mid-2010s, CBFs have been used in research concerning an extensive range of topics such as self-driving cars, aerial and walking robotics, multi-agent systems, etc. However, as it stands, aviation-related control problems remain as one of the fairly unexplored areas in the topic, especially when it comes to autonomous landing - one of the most safety-critical phases of flight. In this work, the fundamental theory and concepts relating to CBFs are first introduced; then, the considerations needed to apply CBFs in an aircraft control problem with a special focus on the requirements for the landing problem are presented. Finally, the results from implementation on a nonlinear three-degrees-of-freedom point mass model with an LQR-dynamic inversion primary controller are presented and the usefulness of the CBFs is shown in two scenarios. In the end, some remarks are given for potential future work.

References

  1. M. Nagumo, "Über die Lage der Integralkurven gewöhnlicher Differentialgleichungen," in Proceedings of the Physico-Mathematical Society of Japan 24, pp. 551-559 (1942).
  2. J.-M. Bony, "Principe du maximum, inégalité de Harnack et unicité du probleme de Cauchy pour les opérateurs elliptiques dégénérés," Annales de l'Institut Fourier 19 (1), pp. 277-304 (1969). 10.5802/aif.319
  3. A. D. Ames, J. W. Grizzle and P. Tabuada, "Control barrier function based quadratic programs with application to adaptive cruise control," in 53rd IEEE Conference on Decision and Control, (Los Angeles, CA, USA, 2014), pp. 6271-6278.
  4. A. D. Ames, X. Xu, J. W. Grizzle and P. Tabuada, "Control barrier function based quadratic programs for safety critical systems," IEEE Transactions on Automatic Control 62 (8), pp. 3861-3876 (2017). 10.1109/TAC.2016.2638961
  5. A. D. Ames, S. Coogan, M. Egerstedt, G. Notomista, K. Sreenath, P. Tabuada, "Control barrier functions: Theory and applications," in 18th European Control Conference (ECC), (Naples, Italy, 2019), IEEE, pp. 3420-3431.
  6. O. So et al., "How to train your neural control barrier function: learning safety filters for complex input-constrained systems," in IEEE International Conference on Robotics and Automation (ICRA), (Yokohama, Japan, 2024), pp. 11532-11539.
  7. T. G. Molnar, S. K. Kannan, J. Cunningham, K. Dunlap, K. L. Hobbs, A. D. Ames, "Collision avoidance and geofencing for fixed-wing aircraft with control barrier functions," 2024, Submitted to the IEEE Transactions on Control System Technology.
  8. H. Zhou, Z. Zheng, Z. Guan, Y. Ma, "Control Barrier Function Based Nonlinear Controller for Automatic Carrier Landing," in 16th International Conference on Control, Automation, Robotics and Vision (ICARCV), (Shenzhen, China, 2020), IEEE, pp. 584-589.
  9. Q. Nguyen and K. Sreenath, "Exponential Control Barrier Functions for enforcing high relative-degree safety-critical constraints," in American Control Conference (ACC), (Boston, MA, USA, 2016), IEEE, pp. 322-328.
  10. A. J. Taylor, P. Ong, T. G. Molnar, A. D. Ames, "Safe backstepping with control barrier functions," in IEEE 61st Conference on Decision and Control (CDC), (Cancun, Mexico, 2022), pp. 5775-5782.
  11. F. Blanchini, S. Miani, Set-Theoretic Methods in Control (Springer, 2008), 2 nd edition, pp. 123-140.
  12. J. A. Grauer, E. A. Morelli, "A generic nonlinear aerodynamic model for aircraft," in AIAA Atmospheric Flight Mechanics Conference, (13-17 January 2014, National Harbor, Maryland).
  13. D.M.K.K. Venkateswara Rao, T. H. Go, "Automatic landing system design using sliding mode control," Aerospace Science and Technology 32 (1), pp. 180-187 (2014). 10.1016/j.ast.2013.10.001
  14. H. K. Khalil, Nonlinear Systems (Prentice Hall, 2002), p. 750.
  15. D. S. Naidu, Optimal Control Systems (CRC Press, 2018), p. 464.

Issue

AIP Conference Proceedings, vol. 3339, 2025, Bulgaria, https://doi.org/10.1063/5.0297786

Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus