Adaptive Fault-tolerant Neural Control for Large-scale Systems with Actuator Faults

  • Jian-Ye Gong
  • Bin Jiang
  • Qi-Kun ShenEmail author


The active adaptive fault-tolerant neural control problem is discussed for large-scale uncertain systems against actuator faults. The unknown interconnections among subsystems are assumed to be nonlinear, not traditional linear. A general actuator fault model is proposed, which integrates bias and gain time-varying faults. Then, based on Lyapunov stability theory, a novel fault diagnostic algorithm and accommodation scheme are proposed, where the assumptions in the existing works are removed and fault-tolerant controller singularity problem is avoided. Finally, simulation results of near space vehicle show the efficiency of the presented control approach.


Adaptive control fault diagnosis fault-tolerant control neural control 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Q. Fu, P. P. Gu, and J. R. Wu, “Decentralized iterative learning control for large-scale interconnected linear systems with fixed initial shifts,” International Journal of Control, Automation, and Systems, vol. 15, no. 5, pp. 1991–2000, October 2017.CrossRefGoogle Scholar
  2. [2]
    Z. P. Jiang, “Decentralized control for large-scale nonlinear systems: a review of recent results,” Dynamics of Continuous, Discrete and Impulsive Systems Series B: Algorithms and Applications, vol. 11, no. 4-5, pp. 537–552, January 2004.MathSciNetzbMATHGoogle Scholar
  3. [3]
    H. Wu, “Decentralized adaptive robust control for a class of large-scale systems including delayed state perturbations in the interconnections,” IEEE Trans. on Automatic Control, vol. 47, no. 10, pp. 1745–1751, October 2002.MathSciNetCrossRefzbMATHGoogle Scholar
  4. [4]
    C. H. Chou and C. C. Chen, “A decentralized model reference adaptive variable structure controller for large-scale time-varying delay systems,” IEEE Trans. on Automatic Control, vol. 48, no. 7, pp. 1213–1217, July 2003.MathSciNetCrossRefzbMATHGoogle Scholar
  5. [5]
    X. W. Liu and H. B. Zhang, “Delay-dependent robust stability of uncertain fuzzy large-scale systems with timevarying delays,” Automatica, vol. 44, pp. 193–198, January 2008.MathSciNetCrossRefzbMATHGoogle Scholar
  6. [6]
    Y. Wang, Q. X. Wu, C. H. Jiang, and G. Y. Huang, “Reentry attitude tracking control based on fuzzy feedforward for reusable launch vehicle,” International Journal of Control, Automation, and Systems, vol. 7, no. 4, pp. 503–511, August 2009.CrossRefGoogle Scholar
  7. [7]
    Q. Zhou, P. Shi, H. H. Liu, and S. Y. Xu, “Neural-networkbased decentralized adaptive output-feedback control for large-scale stochastic nonlinear systems,” IEEE Trans. on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 42, no. 6, pp. 1608–1619, December 2012.CrossRefGoogle Scholar
  8. [8]
    P. Shi, Y. Q. Xia, G. P. Liu, and D. Rees, “On designing of sliding mode control for stochastic jump systems,” IEEE Trans. on Automatic Control, vol. 51, no. 1, pp. 97–103, January 2006.MathSciNetCrossRefzbMATHGoogle Scholar
  9. [9]
    S. C. Tong, C. L. Liu, Y. M. Li, and H. G. Zhang, “Adaptive fuzzy decentralized control for large-Scale nonlinear systems with time-varying delays and unknown highfrequency gain sign,” IEEE Trans. on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 41, no. 2, pp. 474–485, April 2011.CrossRefGoogle Scholar
  10. [10]
    Q. K. Shen, P. Shi, T. P. Zhang, and C. C. Lim, “Novel neural control for a class of uncertain pure-feedback systems,” IEEE Trans. on Neural Networks and Learning Systems, vol. 25, no. 4, pp. 718–727, April 2014.CrossRefGoogle Scholar
  11. [11]
    Q. K. Shen and T. P. Zhang, “Adaptive variable structure control for large-scale time-delayed systems with unknown nonlinear dead-zone,” Journal of Systems Engineering and Electronics, vol. 18, no. 4, pp. 865–870, December 2007.CrossRefzbMATHGoogle Scholar
  12. [12]
    Q. K. Shen, T. P. Zhang, and C. Y. Zhou, “Decentralized adaptive fuzzy control of time-delayed interconnected systems with unknown backlash-like hysteresis,” Journal of Systems Engineering and Electronics, vol. 19, no. 6, pp. 865–870, December 2008.zbMATHGoogle Scholar
  13. [13]
    M. S. Mahmoud, “Reliable decentralized control of interconnected discrete delay systems,” Automatica, vol. 48, no.5, pp. 986–990, May 2012.MathSciNetCrossRefzbMATHGoogle Scholar
  14. [14]
    B. Jiang, Z. F. Gao, P. Shi, and Y. F. Xu, “Adaptive fault-tolerant tracking control of near-space vehicle using Takagi-Sugeno fuzzy models,” IEEE Trans. on Fuzzy Systems, vol. 18, no. 5, pp. 1000–1007, October 2010.CrossRefGoogle Scholar
  15. [15]
    Y. Q. Wang, S. X. Ding, H. Ye, and G. Z. Wang, “A new fault detection scheme for networked control systems subject to uncertain time varying delay,” IEEE Trans. on Signal Processing, vol. 56, pp. 5258–5268, October 2008.MathSciNetCrossRefzbMATHGoogle Scholar
  16. [16]
    Q. K. Shen, B. Jiang, and P, Shi, Fault Diagnosis and Faulttolerant Control Based on Adaptive Control Approach, Springer, 2017.CrossRefGoogle Scholar
  17. [17]
    D. Wang, W. Wang, and P. Shi, “Robust fault detection for switched linear systems with state delays,” IEEE Trans. on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 39, no. 3, pp. 800–805, June 2009.CrossRefGoogle Scholar
  18. [18]
    C. C. Hua and S. X. Ding, “Decentralized networked control system design using T-S fuzzy approach,” IEEE Trans. on Fuzzy Systems, vol. 20, no. 1, pp. 9–21, February 2012.MathSciNetCrossRefGoogle Scholar
  19. [19]
    Q. K. Shen, B. Jiang, and P. Shi, “Adaptive fault diagnosis for T-S fuzzy systems with sensor faults and system performance analysis,” IEEE Trans. on Fuzzy Systems, vol. 22, no. 2, pp. 274–285, April 2014.CrossRefGoogle Scholar
  20. [20]
    Q. K. Shen, B. Jiang, and V. Cocquempot, “Adaptive faulttolerant backstepping control against actuator gain faults and its applications to an aircraft longitudinal motion dynamics,” International Journal of Robust and Nonlinear Control, vol. 23, no. 15, pp. 1753–1779, April 2013.MathSciNetzbMATHGoogle Scholar
  21. [21]
    I. Shames, A. H. Teixeira, H. Sandberg, and K. H. Johansson, “Distributed fault detection for interconnected secondorder systems,” Automatica, vol. 47, no. 12, pp. 2757–2764, December 2011.MathSciNetCrossRefzbMATHGoogle Scholar
  22. [22]
    K. Zhang, B. Jiang, and P. Shi, “Adjustable parameterbased distributed fault estimation observer design for multiagent systems with directed graphs,” IEEE Trans. on Cybernetics, vol. 47, no. 2, pp. 306–314, February 2017.Google Scholar
  23. [23]
    F. Y. Chen, R. Q. Jiang, K. K. Zhang, B. Jiang, and G. Tao, “Robust backstepping sliding-mode control and observerbased fault estimation for a quadrotor UAV,” IEEE Trans. on Industrial Electronics, vol. 63, no. 8, pp. 5044–5056, August 2016.CrossRefGoogle Scholar
  24. [24]
    D. L. Yu, T. K. Chang, and D. W. Yu, “Fault tolerant control of multivariable processes using auto-tuning PID controller,” IEEE Trans. on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 35, no. 1, pp. 32–43, February 2005.MathSciNetCrossRefGoogle Scholar
  25. [25]
    Q. K. Shen, B. Jiang, and V. Cocquempot, “Fuzzy logic system-based adaptive fault tolerant control for near space vehicle attitude dynamics with actuator faults,” IEEE Trans. on Fuzzy Systems, vol. 21, no. 2, pp. 289–300, April 2013.CrossRefGoogle Scholar
  26. [26]
    W. Li, Z. Zhu, and S. X. Ding, “Fault detection design of networked control systems,” IET Control Theory and Applications, vol. 5, no. 12, pp. 1439–1449, August 2011.MathSciNetCrossRefGoogle Scholar

Copyright information

© ICROS, KIEE and Springer 2019

Authors and Affiliations

  1. 1.College of Information EngineeringYangzhou UniversityYangzhouChina
  2. 2.College of Automation EngineeringNanjing University of Aeronautics and AstronauticsNanjingChina

Personalised recommendations