Journal of Vibration Engineering & Technologies

, Volume 6, Issue 6, pp 429–439 | Cite as

Fault-Tolerant Control for Wing Flutter Under Actuator Faults and Time Delay

  • M. Z. Gao
  • G. P. CaiEmail author
Original Paper



Investigating the design of the controller stabilizing the wing flutter system, which is robust against actuator faults, actuator saturation, time delay, parameter uncertainties and external disturbances.


The model of the wing flutter system that considered the effects of actuator faults and saturation, time delay, parameter uncertainties and external disturbances is constructed by the Lagrange method. Then the finite-time fault-tolerant controller is derived, the stability of which is proved by the Lyapunov function.


The simulation results elucidate that, the proposed fault-tolerant controller can handle the actuator faults effectively, meanwhile the wing flutter of the reentry vehicle can be suppressed instantly. The robustness of the actuator against actuator saturation, time delay, parameter uncertainties and external disturbances is also demonstrated.


Active flutter suppression Fault-tolerant control Time delay Actuator fault Observer Actuator saturation 



This work was supported by the Natural Science Foundation of China [Grant number 11772187, 11802174], the China Postdoctoral Science Foundation [Grant number 2018M632104], and Shanghai Institute of Technical Physics of the Chinese Academy of Science [Grant number CASIR201702].


  1. 1.
    Zhao YH (2009) Flutter suppression of a high aspect-ratio wing with multiple control surfaces. J Sound Vib 324(3–5):490–513CrossRefGoogle Scholar
  2. 2.
    Yu ML, Wen H, Hu HY, Zhao YH (2007) Active flutter suppression of a two dimensional airfoil section using μ synthesis. Acta Aeronaut et Astronaut Sin 28(2):340–343Google Scholar
  3. 3.
    Prime Z, Cazzolato B, Doolan C, Strganac T (2010) Linear-parameter-varying control of an improved three-degree-of-freedom aeroelastic model. J Guid, Control, and Dyn 33(2):615–619CrossRefGoogle Scholar
  4. 4.
    Wang Z, Behal A, Marzocca P (2011) Model-free control design for multi-input multi-output aerolastic system subject to external disturbance. J Guid, Control, Dyn 34(2):446–458CrossRefGoogle Scholar
  5. 5.
    Wang Z, Behal A, Marzocca P (2012) Continuous robust control for two-dimensional airfoils with leading and trailing-edge flaps. J Guid, Control, Dyn 35(2):510–519CrossRefGoogle Scholar
  6. 6.
    Zhang K, Wang Z, Behal A, Marzocca P (2013) Novel nonlinear control design for a two-dimensional airfoil under unsteady flow. J Guid, Control, Dyn 36(6):1681–1694CrossRefGoogle Scholar
  7. 7.
    Castaldi P, Mimmo N, Simani S (2014) Differential geometry based active fault tolerant control for aircraft. Control Eng Pract 32:227–235CrossRefGoogle Scholar
  8. 8.
    Mahmoud M (2009) Sufficient conditions for the stabilization of feedback delayed discrete time fault tolerant control systems. Int J Innov Comput 5(5):1137–1146Google Scholar
  9. 9.
    Alwi H, Edwards C, Stroosma O, Mulder JA (2008) Fault tolerant sliding mode control design with piloted simulator evaluation. J Guid, Control, Dyn 31(5):1186–1201CrossRefGoogle Scholar
  10. 10.
    Jin XZ, Yang GH (2010) Robust fault-tolerant controller design for linear time-invariant systems with actuator failures: an indirect adaptive method. IET Control Theory Appl 8(4):471–478MathSciNetCrossRefGoogle Scholar
  11. 11.
    Xu DZ, Jiang B, Liu HT, Shi P (2013) Decentralized asymptotic fault tolerant control of near space vehicle with high order actuator dynamics. J Franklin Inst 350(9):2519–2534MathSciNetCrossRefGoogle Scholar
  12. 12.
    Huang R, Qian WM, Hu HY, Zhao YH (2015) Design of active flutter suppression and wind-tunnel tests of a wing model involving a control delay. J Fluids Struct 55:409–427CrossRefGoogle Scholar
  13. 13.
    Qian WM, Huang R, Hu HY, Zhao YH (2014) Active flutter suppression of a multiple-actuated-wing wind tunnel model. Chin J Aeronaut 27(6):1451–1460CrossRefGoogle Scholar
  14. 14.
    Singh KV (2015) Active aeroelastic control with time delay for targeted flutter modes. Aerosp Sci Technol 43:281–288CrossRefGoogle Scholar
  15. 15.
    Zhou LQ, Chen YS, Chen FQ (2013) Chaotic motions of a two-dimensional airfoil with cubic nonlinearity in supersonic flow. Aerosp Sci Technol 25(1):138–144CrossRefGoogle Scholar
  16. 16.
    Chen YM, Liu JK, Meng G (2011) Equivalent damping of aeroelastic system of an wing with cubic stiffness. J Fluids Struct 27(8):1447–1454CrossRefGoogle Scholar
  17. 17.
    Lu JN, Hu HP, Bai YP (2015) Generalized radial basis function neural network based on an improved dynamic particle swarm optimization and AdaBoost algorithm. Neurocomputing 152(25):305–315CrossRefGoogle Scholar
  18. 18.
    Amato F, Ariola M (2001) Finite-time control of linear systems subject to parametric uncertainties and disturbances. Automatica 37(9):1459–1463CrossRefGoogle Scholar
  19. 19.
    Meng QY, Shen YJ (2009) Finite-time H control for linear continuous system with norm-bounded disturbance. Commun Nonlinear Sci Numer Simul 14(4):1043–1049MathSciNetCrossRefGoogle Scholar
  20. 20.
    Zhang W, Su H, Wang H, Han Z (2012) Full-order and reduced-order observers for one-sided Lipschitz nonlinear systems using Riccati equations. Commun Nonlinear Sci Numer Simul 17(12):4968–4977MathSciNetCrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Department of Engineering MechanicsState Key Laboratory of Ocean Engineering, Shanghai Jiaotong UniversityShanghaiChina

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