Control Surface Faults Neural Adaptive Compensation Control for Tailless Flying Wing Aircraft with Uncertainties

  • Shaojie ZhangEmail author
  • Weifang Shuang
  • Qingkai Meng
Regular Papers Control Theory and Applications


A neural adaptive compensation tracking control scheme considering the prescribed tracking performance bound is proposed for a flying wing aircraft with control surface faults, actuator saturation and uncertainties of aerodynamic parameters. Second-order command filters are introduced to avoid the saturation of the actuators, prescribed performance bound strategy is designed to characterize the convergence rate and maximum overshoot of the tracking error, uncertainties of aerodynamic parameters are approximated by online RBF neural networks, and control allocation law is designed to reduce the coupling of the flight dynamics. The closed-loop control law is given based on adaptive backstepping compensation control scheme, and the stability of the closed-loop system is proved by Lyapunov based design. Simulation results are given to illustrate the effectiveness of the proposed neural adaptive compensation control scheme.


Command filter fault tolerant control flying wing aircraft neural network prescribed performance bound 


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  1. [1]
    B. F. Song, B. Q. Zhang, and Z. H. Han, “The study of concept design criteria for large-scale passenger aircraft with new technologies,” Acta Aeronautica et Astronautica Sinica, vol. 29, no. 3, pp. 583–595, May-June 2008.Google Scholar
  2. [2]
    B. Rose, Flying Wings and Tailless Aircraft, Midland, 2010.Google Scholar
  3. [3]
    T. I. Saeed, W. R. Graham, H. Babinsky, J. P. Eastwood, C. A. Hall, J. P. Jarrett, M. M. Lone, and K. A. Seffen. Conceptual Design for a Laminar-flying-wing Aircraft, University of Cambridge, 2012.CrossRefGoogle Scholar
  4. [4]
    X. R. Meng and H. Z. Ma, “Summary for control method of flying wing UAV,” Aerodynamic Missile Journal, vol. 5, pp. 25–28, 2015.Google Scholar
  5. [5]
    M. Tomac and G. Stenfelt, “Predictions of stability and control for a flying wing,” Aerospace Science and Technology, vol. 39, pp. 179–186, December 2014.CrossRefGoogle Scholar
  6. [6]
    Y. L. Wei, J. Qiu, and H. K. Lam, “A novel approach to reliable output feedback control of fuzzy-affine systems with time-delays and sensor faults,” IEEE Transactions on Fuzzy Systems, vol. 25, no. 6, pp. 1808–1823, December 2017.CrossRefGoogle Scholar
  7. [7]
    Y. L. Wei, J. Qiu, and H. R. Karimi, “Quantized H¥ filtering for continuous-time Markovian jump systems with deficient mode information,” Asian Journal of Control, vol. 17, no. 5, pp. 1914–1923, September 2015.MathSciNetCrossRefzbMATHGoogle Scholar
  8. [8]
    C. Edwards, T. Lombaerts, and H. Smaili, Fault Tolerant Flight Control: A Benchmark Challenge, Springer, Berlin, Germany, 2010.CrossRefGoogle Scholar
  9. [9]
    Y. M. Zhang and J. Jiang, “Bibliographical review on reconfigurable fault-tolerant control systems,” Annual Reviews in Control, vol. 32, no. 2, pp. 229–252, December 2008.CrossRefGoogle Scholar
  10. [10]
    J. Jiang and X. Yu, “Fault-tolerant control systems: a comparative study between active and passive approaches,” Annual Reviews in Control, vol. 36, no. 1, pp. 60–72, April 2012.CrossRefGoogle Scholar
  11. [11]
    M. Benosman and K. Y. Lum, “Passive actuators’ faulttolerant control for affine nonlinear systems,” IEEE Transactions on Control Systems Technology, vol. 18, no. 1, pp. 152–163, January 2010.CrossRefGoogle Scholar
  12. [12]
    Z. Gao, B. Jiang, P. Shi, J. Liu, and Y. Xu, “Passive faulttolerant control design for near-space hypersonic vehicle dynamical system,” Circuits, Systems, and Signal Processing,, vol. 31, no. 2, pp. 565–581, April 2012.MathSciNetCrossRefzbMATHGoogle Scholar
  13. [13]
    B. Jiang, Z. Gao, P. Shi, and Y. Xu, “Adaptive fault-tolerant tracking control of near-space vehicle using Takagi-Sugeno fuzzy models,” IEEE Transactions on Fuzzy Systems, vol. 18, no. 5, pp. 1000–1007, October 2010.CrossRefGoogle Scholar
  14. [14]
    B. Jiang and H Yang, “Survey of the active fault-tolerant control for flight control system,” Journal of Systems Engineering and Electronics, vol. 29, no. 12, pp. 2106–2110, December 2007.zbMATHGoogle Scholar
  15. [15]
    B. Xu, Y. Guo, Y. Yuan, Y. H. Fan, and D. W. Wang, “Fault-tolerant control using command-filtered adaptive back-stepping technique: application to hypersonic longitudinal flight dynamics,” International Journal of Adaptive Control and Signal Processing, vol. 30, no. 4, pp. 553–577, April 2016.MathSciNetCrossRefGoogle Scholar
  16. [16]
    G. Tao, “Direct adaptive actuator failure compensation control: a tutorial,” Control and Decision, vol. 1, no. 1, pp. 75–101, March 2014.CrossRefGoogle Scholar
  17. [17]
    Y. Ma, B. Jiang, G. Tao, and Y. Cheng, “A direct adaptive actuator failure compensation scheme for satellite attitude control systems,” Proceedings of the Institution of Mechanical Engineers, -Part G: Journal of Aerospace Engineering, vol. 228, no. 4, pp. 542–556, March 2014.CrossRefGoogle Scholar
  18. [18]
    X. D. Tang and G. Tao, “An adaptive nonlinear output feedback controller using dynamic bounding with an aircraft control application,” International Journal of Adaptive Control and Signal Processing, vol. 23, no. 7, pp. 609–639, June 2009.MathSciNetCrossRefzbMATHGoogle Scholar
  19. [19]
    S. J. Zhang, X. W. Qiu, C. S. Liu, and S. S. Hu, “Adaptive compensation control based on MMST grouping for a class of MIMO nonlinear systems with actuator failures,” Acta Automatica Sinica, vol. 40, no. 11, pp. 2445–2455, November 2014.zbMATHGoogle Scholar
  20. [20]
    S. J. Zhang, X. W. Qiu, B. Jiang, and C. S. Liu, “Adaptive actuator failure compensation control based on MMST grouping for a class of MIMO nonlinear systems with guaranteed transient performance,” International Journal of Control, vol. 88, no. 3, pp. 593–601, November 2014.MathSciNetCrossRefzbMATHGoogle Scholar
  21. [21]
    D. Efimov, J. Cieslak, and D. Henry. “Supervisory faulttolerant control with mutual performance optimization,” International Journal of Adaptive Control and Signal Processing, vol. 27, no. 4, pp. 251–279, April 2013.MathSciNetCrossRefzbMATHGoogle Scholar
  22. [22]
    X. D. Tang, G. Tao, and S. M. Joshi, “Adaptive actuator failure compensation for nonlinear MIMO systems with an aircraft control application,” Automatica, vol. 43, no. 11, pp. 1869–1883, November 2007.MathSciNetCrossRefzbMATHGoogle Scholar
  23. [23]
    Y. L. Wei, J. Qiu, and H. R. Karimi, “Reliable output feedback control of discrete-time fuzzy affine systems with actuator faults,” IEEE Transactions on Circuits & Systems I Regular Papers, vol. 64, no. 1, pp. 170–181, January 2017.CrossRefGoogle Scholar
  24. [24]
    Y. L. Wei, J. Qiu, H. K. Lam and L. Wu, “Approaches to TS fuzzy-affine-model-based reliable output feedback control for nonlinear Ito stochastic systems,” IEEE Transactions on Fuzzy Systems, vol. 25, no. 3, pp. 569–583, June 2017.CrossRefGoogle Scholar
  25. [25]
    Y. L. Wei, J. Qiu, and H. R. Karimi, “Fuzzy-affine-modelbased memory filter design of nonlinear systems with timevarying delay,” IEEE Transactions on Fuzzy Systems, vol. 26, no. 2, pp. 504–517, April 2018.CrossRefGoogle Scholar
  26. [26]
    M. Kim, T. Kuc, H. Kim, and J. S. Lee, “Adaptive iterative learning controller with input learning technique for a class of uncertain MIMO nonlinear systems,” International Journal of Control Automation and Systems, vol. 15, no. 1, pp. 315–328, February 2017.CrossRefGoogle Scholar
  27. [27]
    S. J. Zhang, X. W. Qiu, and C. S. Liu, “Neural adaptive compensation control for a class of MIMO uncertain nonlinear systems with actuator failures,” Circuits Systems and Signal Processing, vol. 33, no. 6, pp. 1971–1984, June 2014.MathSciNetCrossRefGoogle Scholar
  28. [28]
    J. Cai, C. Wen, and H. Su, “Adaptive inverse control for parametric strict feedback systems with unknown failures of hysteretic actuators,” International Journal of Robust and Nonlinear Control, vol. 25, no. 6,pp. 824–841, April 2015.MathSciNetCrossRefzbMATHGoogle Scholar
  29. [29]
    Z. T. Ding, Nonlinear and Adaptive Control Systems, IET Digital Library, 2013.CrossRefzbMATHGoogle Scholar
  30. [30]
    D. Swaroop, J. Hedrick, P. Yip, and J. Gerdes, “Dynamic surface control for a class of nonlinear systems,” IEEE Transactions on Automatic Control, vol. 45, no. 10, pp. 1893–1899, October 2000.MathSciNetCrossRefzbMATHGoogle Scholar
  31. [31]
    M. Peimani, M. J. Yazdanpanah, and N. Khaji, “Adaptive dynamic surface control of Bouc-Wen hysteretic systems,” Journal of Dynamic Systems, Measurement, and Control, vol. 138, no. 9, 091007, June 2016.Google Scholar
  32. [32]
    Y. Li, T. Li, and S. Tong, “Adaptive neural networks output feedback dynamic surface control design for MIMO pure-feedback nonlinear systems with hysteresis,” Neurocomputing, vol. 198, pp. 58–68, July 2016.CrossRefGoogle Scholar
  33. [33]
    B. Xu, C. Yang, and Y. Pan, “Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle,” IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 10, pp. 2563–2575, October 2015.MathSciNetCrossRefGoogle Scholar
  34. [34]
    J. A. Farrell, M. Polycarpou, M. Sharma, and W. J. Dong, “Command filtered backstepping,” IEEE Transactions on Automatic Control, vol. 54, no. 6, pp. 1391–1395, June 2009.MathSciNetCrossRefzbMATHGoogle Scholar
  35. [35]
    W. J. Dong, J. A. Farrell, M. Polycarpou, and M. Sharma, “Command filtered adaptive backstepping,” IEEE Transactions on Control Systems Technology, vol. 20, no. 3, pp. 566–580, May 2012.CrossRefzbMATHGoogle Scholar
  36. [36]
    Q.Wang, Q. Li, N. Chen, and J. Y. Song, “A nonlinear fault tolerant flight control method against structural damage,” Acta Aeronautica et Astronautica Sinica, 2015.Google Scholar
  37. [37]
    C. P. Bechlioulis and G. A. Rovithakis, “A low-complexity global approximation-free control scheme with prescribed performance for unknown pure feedback systems,” Automatica, vol. 50, no. 4, pp. 1217–1226, April 2014.MathSciNetCrossRefzbMATHGoogle Scholar
  38. [38]
    L. Sonneveldt, Q. P. Chu, and J. A. Mulder, “Nonlinear flight control design using constrained adaptive backstepping,” Journal of Guidance, Control, and Dynamics, vol. 30, no. 2, pp. 322–336, March-April 2007.CrossRefGoogle Scholar
  39. [39]
    F. S. Li, “Research on overall optimization design method for aggressive tailless flying wing UAV,” M.S. Dissertation, Aeronautic Department, Northwestern Polytechnical University, Xi-an, China, 2007.Google Scholar
  40. [40]
    H. K. Khalil. Nonlinear Systems, 3rd ed, Prentice Hall, New Jersey, 2002.zbMATHGoogle 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

  1. 1.College of Automation EngineeringNanjing University of Aeronautics and Astronautics211106China

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