Skip to main content
Log in

Limit cycle oscillation suppression controller design and stability analysis of the periodically time-varying flapping flight dynamics in hover

  • Original Paper
  • Published:
Nonlinear Dynamics Aims and scope Submit manuscript

Abstract

The periodically time-varying forces make the equilibrium state of Beihawk, an X-shaped flapping-wing aircraft, to be a periodic limit cycle oscillation. However, traditional controllers based on averaging theory fail to suppress this oscillation and the derived stability result may be inaccurate. In this study, a period-based method is proposed to design the oscillation suppression controller, locate the corresponding cycle and analyze its stability. A periodically time-varying wing-tail interaction model is built and Discrete Fourier Transform is applied to adapt the model for controller design. The harmonics less than quintuple flapping frequency account for more than 96 percent of the total harmonics and are reserved to present a concise model. Based on this model, active disturbance rejection controller (ADRC) is designed and its Extended State Observer can observe the disturbance to suppress the oscillation. Poincaré map is introduced to convert the stability analysis of the cycle to a fixed point. A multiple shooting method is adopted to locate several points on the cycle and the map is obtained by calculating the submaps between the adjacent points with the Floquet theory. The located points are proved to be accurate compared with the numerical solved cycle and the stability analysis result of the cycle is verified by the dynamic evolution. Compared with the State Feedback Controller, the ADRC performs better in suppressing the limit cycle oscillation and eliminating the attitude control error. The oscillation suppression is meaningful in maintaining a stable flight and capturing high quality images.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

Data availability

All data used to support the findings of this study are available from the corresponding author upon request.

Code availability

This work is done using custom code.

References

  1. Taha, H.E., Kiani, M., Hedrick, T.L., Greeter, J.S.M.: Vibrational control: a hidden stabilization mechanism in insect flight. Sci. Robot. 5, 1–12 (2020). https://doi.org/10.1126/SCIROBOTICS.ABB1502

    Article  Google Scholar 

  2. Lee, J., Ryu, S., Kim, H.J.: Stable flight of a flapping-wing micro air vehicle under wind disturbance. IEEE Robot. Autom. Lett. 5, 5685–5692 (2020). https://doi.org/10.1109/LRA.2020.3009064

    Article  Google Scholar 

  3. Warrick, D.R., Tobalske, B.W., Powers, D.R.: Aerodynamics of the hovering hummingbird. Nature 435, 1094–1097 (2005). https://doi.org/10.1038/nature03647

    Article  Google Scholar 

  4. De Croon, G.C.H.E., Groen, M.A., De Wagter, C., Remes, B., Ruijsink, R., Van Oudheusden, B.W.: Design, aerodynamics and autonomy of the DelFly. Bioinspir. Biomimet. 7, 025003 (2012). https://doi.org/10.1088/1748-3182/7/2/025003

    Article  Google Scholar 

  5. Wood, R., Nagpal, R., Wei, G.Y.: Flight of the robobees. Sci. Am. 308(3), 60–65 (2013)

    Article  Google Scholar 

  6. Jiao, Z., Wang, L., Zhao, L., Jiang, W.: Hover flight control of X-shaped flapping wing aircraft considering wing–tail interactions. Aerosp. Sci. Technol. 116, 106870 (2021). https://doi.org/10.1016/j.ast.2021.106870

    Article  Google Scholar 

  7. Sane, S.P.: The aerodynamics of insect flight. J. Exp. Biol. 206, 4191–4208 (2003). https://doi.org/10.1242/jeb.00663

    Article  Google Scholar 

  8. Shyy, W., Berg, M., Ljungqvist, D.: Flapping and flexible wings for biological and micro air vehicles. Progr Aerosp Sci 35, 455–505 (1999)

    Article  Google Scholar 

  9. Wang, Z.J.: Dissecting insect flight. Annu. Rev. Fluid Mech. 37, 183–210 (2005). https://doi.org/10.1146/annurev.fluid.36.050802.121940

    Article  MathSciNet  MATH  Google Scholar 

  10. Xuan, H., Hu, J., Yu, Y., Zhang, J.: Recent progress in aerodynamic modeling methods for flapping flight. AIP Adv. 10, 020701 (2020). https://doi.org/10.1063/1.5130900

    Article  Google Scholar 

  11. Terze, Z., Pandža, V., Kasalo, M., Zlatar, D.: Optimized flapping wing dynamics via DMOC approach. Nonlinear Dyn. 103, 399–417 (2021). https://doi.org/10.1007/s11071-020-06119-y

    Article  Google Scholar 

  12. Deng, X., Schenato, L., Sastry, S.S.: Flapping flight for biomimetic robotic insects: Part I—system modeling. IEEE Trans. Robot. 22, 776–788 (2006)

    Article  Google Scholar 

  13. He, W., Yan, Z., Sun, C., Chen, Y.: Adaptive neural network control of a flapping Wing micro aerial vehicle with disturbance observer. IEEE Trans. Cybern. 47, 3452–3465 (2017). https://doi.org/10.1109/TCYB.2017.2720801

    Article  Google Scholar 

  14. Maggia, M., Eisa, S.A., Taha, H.E.: On higher-order averaging of time-periodic systems: reconciliation of two averaging techniques. Nonlinear Dyn. 99, 813–836 (2020). https://doi.org/10.1007/s11071-019-05085-4

    Article  MATH  Google Scholar 

  15. Deng, X., Schenato, L., Sastry, S.S.: Flapping flight for biomimetic robotic insects: Part II—flight control design. IEEE Trans. Robot. 22, 789–803 (2006). https://doi.org/10.1109/TRO.2006.875483

    Article  Google Scholar 

  16. Cheng, B., Deng, X.: A neural adaptive controller in flapping flight. J. Robot. Mechatron. 24, 602–611 (2012). https://doi.org/10.20965/jrm.2012.p0602

    Article  Google Scholar 

  17. Zhang, J., Tu, Z., Fei, F., Deng, X.: Geometric flight control of a hovering robotic hummingbird. In: Proc.—IEEE Int. Conf. Robot. Autom. 5415–5421 (2017). https://doi.org/10.1109/ICRA.2017.7989638

  18. Fei, F., Tu, Z., Zhang, J., Deng, X.: Learning extreme hummingbird maneuvers on flapping wing robots. In: Proc.—IEEE Int. Conf. Robot. Autom. 2019-May, 109–115 (2019). https://doi.org/10.1109/ICRA.2019.8794100

  19. Wissa, B.E., Elshafei, K.O., El-Badawy, A.A.: Lyapunov-based control and trajectory tracking of a 6-DOF flapping wing micro aerial vehicle. Nonlinear Dyn. 99, 2919–2938 (2020). https://doi.org/10.1007/s11071-020-05487-9

    Article  Google Scholar 

  20. Chirarattananon, P., Ma, K.Y., Wood, R.J.: Adaptive control of a millimeter-scale flapping-wing robot. Bioinspir. Biomimet. 9, 025004 (2014). https://doi.org/10.1088/1748-3182/9/2/025004

    Article  Google Scholar 

  21. Taha, H.E., Hajj, M.R., Nayfeh, A.H.: Flight dynamics and control of flapping-wing MAVs: a review. Nonlinear Dyn. 70, 907–939 (2012). https://doi.org/10.1007/s11071-012-0529-5

    Article  MathSciNet  Google Scholar 

  22. Hassan, A.M., Taha, H.E.: Combined averaging-shooting approach for the analysis of flapping flight dynamics. J. Guid. Control. Dyn. 41, 538–545 (2018). https://doi.org/10.2514/1.G002795

    Article  Google Scholar 

  23. Taha, H.E., Hajj, M.R., Nayfeh, A.H.: Longitudinal flight dynamics of hovering MAVs/Insects. J. Guid. Control. Dyn. 37, 970–978 (2014). https://doi.org/10.2514/1.62323

    Article  Google Scholar 

  24. Taha, H.E., Tahmasian, S., Woolsey, C.A., Nayfeh, A.H., Hajj, M.R.: The need for higher-order averaging in the stability analysis of hovering, flapping-wing flight. Bioinspir. Biomimet. 10, 016002 (2015). https://doi.org/10.1088/1748-3190/10/1/016002

    Article  Google Scholar 

  25. Taha, H., Kiani, M., Navarro, J.: Experimental demonstration of the vibrational stabilization phenomenon in bio-inspired flying robots. IEEE Robot. Autom. Lett. 3, 643–647 (2018). https://doi.org/10.1109/LRA.2017.2778759

    Article  Google Scholar 

  26. Taha, H.E., Woolsey, C.A., Hajj, M.R.: Geometric control approach to longitudinal stability of flapping flight. J. Guid. Control. Dyn. 39, 214–226 (2016). https://doi.org/10.2514/1.G001280

    Article  Google Scholar 

  27. Taylor, G.K., Zbikowski, R.: Nonlinear time-periodic models of the longitudinal flight dynamics of desert locusts Schistocerca gregaria. J. R. Soc. Interfaces 2, 197–221 (2005). https://doi.org/10.1098/rsif.2005.0036

    Article  Google Scholar 

  28. Nogar, S.M., Gogulapati, A., McNamara, J.J., Serrani, A., Oppenheimer, M.W., Doman, D.B.: Control-oriented modeling of coupled electromechanical-aeroelastic dynamics for flapping-wing vehicles. J. Guid. Control. Dyn. 40, 1664–1679 (2017). https://doi.org/10.2514/1.G002503

    Article  Google Scholar 

  29. Biswal, S., Mignolet, M., Rodriguez, A.A.: Modeling and control of flapping wing micro aerial vehicles. Bioinspir. Biomimet. 14, 026004 (2019). https://doi.org/10.1088/1748-3190/aafc3c

    Article  Google Scholar 

  30. Hassan, A.M., Taha, H.E.: Differential-geometric-control formulation of flapping flight multi-body dynamics. J. Nonlinear Sci. 29, 1379–1417 (2019). https://doi.org/10.1007/s00332-018-9520-8

    Article  MathSciNet  MATH  Google Scholar 

  31. Mouy, A., Rossi, A., Taha, H.E.: Coupled unsteady aero-flight dynamics of hovering insects/flapping micro air vehicles. J. Aircr. 54, 1738–1749 (2017). https://doi.org/10.2514/1.C034205

    Article  Google Scholar 

  32. Su, W., Cesnik, C.E.S.: Flight dynamic stability of a flapping wing micro air vehicle in hover. Collect. Tech. Pap.—AIAA/ASME/ASCE/AHS/ASC Struct. Struct. Dyn. Mater. Conf. 1–17 (2011). https://doi.org/10.2514/6.2011-2009

  33. Dietl, J.M., Garcia, E.: Stability in hovering ornithopter flight. Ind. Commer. Appl. Smart Struct. Technol. (2008). https://doi.org/10.1117/12.776482

    Article  Google Scholar 

  34. Kamankesh, Z., Banazadeh, A.: Stability analysis for design improvement of bio-inspired flapping wings by energy method. Aerosp. Sci. Technol. 111, 106558 (2021). https://doi.org/10.1016/j.ast.2021.106558

    Article  Google Scholar 

  35. Sane, S.P., Dickinson, M.H.: The aerodynamic effects of wing rotation and a revised quasi-steady model of flapping flight. J. Exp. Biol. 205, 1087–1096 (2002)

    Article  Google Scholar 

  36. Banazadeh, A., Taymourtash, N.: Adaptive attitude and position control of an insect-like flapping wing air vehicle. Nonlinear Dyn. 85, 47–66 (2016). https://doi.org/10.1007/s11071-016-2666-8

    Article  MathSciNet  Google Scholar 

  37. Harmon, R.L.: Aerodynamic modelling of a flapping membrane wing using motion tracking experiments (2008)

  38. Dickinson, M.H., Lehmann, F., Sane, S.P., Dickinson, M.H., Lehmann, F., Sane, S.P.: Wing rotation and the aerodynamic basis of insect flight. Science 80(284), 1954–1960 (1999)

    Article  Google Scholar 

  39. Fung, Y.: An Introduction to the Theory of Aeroelasticity. Dover, New York (1969)

    Google Scholar 

  40. Sane, S.P., Dickinson, M.H.: Erratum: The control of flight force by a flapping wing: Lift and drag production (Journal of Expiremental Biology (2001) 204 (2607–2626)). J. Exp. Biol. 204, 3401 (2001)

    Article  Google Scholar 

  41. Shkarayev, S., Moschetta, J.M., Bataille, B.: Aerodynamic design of micro air vehicles for vertical flight. J. Aircr. 45, 1715–1724 (2008). https://doi.org/10.2514/1.35573

    Article  Google Scholar 

  42. Longfei, Z., Wenshuo, W., Yuxin, C., Zongxia, J.: Analytical modeling of a hoverable X-shape flapping wing aircraft considering wing-tail interaction. In: 32nd Congress of the international council of the aeronautical sciences, ICAS. pp. 1–11. , Shanghai, China (2021)

  43. Anderson, J.D.: Fundamentals of Aerodynamics, Sixth Edition (2017)

  44. Oppermann, R.H.: The elements of aerofoil and airscrew theory (1943)

  45. Han, J.: From PID to active disturbance rejection control. IEEE Trans. Ind. Electron. 56, 900–906 (2009). https://doi.org/10.1109/TIE.2008.2011621

    Article  Google Scholar 

  46. Madonski, R., Shao, S., Zhang, H., Gao, Z., Yang, J., Li, S.: General error-based active disturbance rejection control for swift industrial implementations. Control Eng. Pract. 84, 218–229 (2019). https://doi.org/10.1016/j.conengprac.2018.11.021

    Article  Google Scholar 

  47. Wang, C., Chen, Z., Sun, Q., Qing, Z.: Design of PID and ADRC based quadrotor helicopter control system. Proc. 28th Chinese Control Decis. Conf. CCDC 2016. 5860–5865 (2016). https://doi.org/10.1109/CCDC.2016.7532046

  48. Kuznetsov, Y.A.: Elements of Applied Bifurcation Theory, Second Edition. 614 (1998)

  49. Amin, M.A., Hertzberg, M.P., Kaiser, D.I., Karouby, J.: Nonperturbative dynamics of reheating after inflation: a review. Int. J. Mod. Phys. D. 24, 1–46 (2015). https://doi.org/10.1142/S0218271815300037

    Article  MATH  Google Scholar 

  50. Dednam, W., Botha, A.E.: Optimized shooting method for finding periodic orbits of nonlinear dynamical systems. Eng. Comput. 31, 749–762 (2015). https://doi.org/10.1007/s00366-014-0386-6

    Article  Google Scholar 

  51. Dietl, J.M., Garcia, E.: Stability in ornithopter longitudinal flight dynamics. J. Guid. Control. Dyn. 31, 1157–1162 (2008). https://doi.org/10.2514/1.33561

    Article  Google Scholar 

  52. Gao, Z.: Scaling and bandwidth-parameterization based controller tuning. Proc. Am. Control Conf. 6, 4989–4996 (2003). https://doi.org/10.1109/acc.2003.1242516

    Article  Google Scholar 

Download references

Acknowledgements

The authors acknowledge the financial support from the National Natural Science Foundation of China under Grants 51905014. The authors would also like to thank the editors and reviewers for their critical review of this manuscript.

Funding

The research is supported by Innovative Research Group Project of the National Natural Science Foundation of China Grant No. 51905014

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Longfei Zhao.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interest regarding the publication of this paper.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix

Algorithm description of the LMA: Solving the located points on the circle.

Initialization

Indicative values for the user-defined parameters: \(\tau = 10^{ - 3} ,\varepsilon_{1} = \varepsilon_{2} = \varepsilon_{3} = 10^{ - 15} ,k_{\max } = 100\).

Input: A target error function \(g(\hat{x})\) and an initial state vector \( \hat{x}_{0} \in R^{(m + 1)n}\).

Output: A vector \( \hat{x}^{ + } \in R^{(m + 1)n}\) minimizing \(\chi^{2} (\hat{x})\).

figure a

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, L., Jiang, W., Jiao, Z. et al. Limit cycle oscillation suppression controller design and stability analysis of the periodically time-varying flapping flight dynamics in hover. Nonlinear Dyn 107, 3385–3405 (2022). https://doi.org/10.1007/s11071-021-07145-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11071-021-07145-0

Keywords

Navigation