Skip to main content
SpringerLink
Log in

Fault Tolerant Control for Near Space Vehicles with Input Saturation Using Disturbance Observer and Neural Networks

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

In this paper, a fault tolerant sliding mode control scheme is derived for near space vehicles with actuator faults, unknown external disturbance, system uncertainty and input saturation based on disturbance observer and neural networks (NNs). To deal with actuator faults, the radial basis function NNs are employed. The nonlinear disturbance observer is designed to eliminate the effect of external disturbance and system uncertainty. To tackle input saturation, the known bound of saturation is used to design the control law such that the control input is within the bounded range. Lyapunov stability analysis shows that the closed-loop system is stable and all closed-loop signals are uniformly ultimately bounded. Simulation results demonstrate the effectiveness of the developed fault tolerant control scheme, when actuator faults, unknown external disturbance, system uncertainty and input saturation appear simultaneously.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. G. Bartolini, A. Ferrara, E. Usai, Chattering avoidance by second-order sliding mode control. IEEE Int. Autom. Control 43(2), 241–246 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  2. B. Beltran, T.A. Ali, High-order sliding-mode control of variable-speed wind turbines. IEEE Int. Ind. Electron. 56(9), 3314–3321 (2009)

    Article  Google Scholar 

  3. M. Chen, W.H. Chen, Sliding mode control for a class of uncertain nonlinear system based on disturbance observer. Int. J. Adapt. Control Signal Process. 24(1), 51–64 (2010)

    MATH  Google Scholar 

  4. M. Chen, S.S. Ge, B.B. Ren, Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints. Automatica 47(3), 452–465 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  5. M. Chen, R. Mei, B. Jiang, Sliding mode control for a class of uncetain MIMO nonlinear systems with application to near-space vehicles, Math. Probl. Eng. 2013, 9, Article ID 180589 (2013)

  6. M. Chen, Q.X. Wu, C.S. Jiang, B. Jiang, Guaranteed transient performance based control for near space vehicles with input saturation. Sci. China Inf. Sci. 57(5), 1–12 (2014)

  7. W.H. Chen, Nonlinear disturbance observer-enhanced dynamical inversion control of missiles. J. Guid. Control Dyn. 26(1), 161–166 (2003)

    Article  Google Scholar 

  8. W.H. Chen, Disturbance observer based control for nonlinear systems. IEEE Trans. Mechatron. 9(4), 706–710 (2004)

    Article  Google Scholar 

  9. W.S. Chen, L.C. Jiao, J.S. Wu, Globally stable adaptive robust tracking control using RBF neural networks as feedforward compensators. Neural Comput. Appl. 21(2), 351–363 (2012)

    Article  Google Scholar 

  10. L. Cheng, C.S. Jiang, Y.L. Du, The research of SMDO based NGPC method for NSV control system. J. Astronaut. 31(2), 424–431 (2010)

    Google Scholar 

  11. R. Cui, B. Ren, S.S. Ge, Synchronised tracking control of multi-agent system with high-order dynamics. IET Control Theory Appl. 5(6), 603–614 (2012)

    Article  MathSciNet  Google Scholar 

  12. B. Jiang, P. Shi, Z. Mao, Sliding mode observer-based fault estimation for nonlinear networked control systems. Circuits Syst. Signal Process. 30(1), 1–16 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  13. J.Y. Kuan, H.P. Huang, Independent joint dynamic sliding mode control of a humanoid robot arm. In: Robotics and Biomimetics, 2008. ROBIO 2008. IEEE International Conference on IEEE (2009), pp. 602–607

  14. S. Laghrouchea, F. Plestanb, A. Glumineau, Higher order sliding mode control based on integral sliding mode. Automatica 43(3), 531–537 (2007)

    Article  MathSciNet  Google Scholar 

  15. Y.M. Li, S.C. Tong, Robust adaptive fuzzy fault diagnosis and tolerant control for SISO unknown nonlinear systems. In: Proceedings of 2009 International Conference on Machine Learning and Cybernetics (2009), pp. 1–6

  16. Z.J. Li, S.S. Ge, S. Liu, Contact-force distribution optimization and control for quadruped robots using both gradient and adaptive neural networks. IEEE Trans. Neural Netw. Learn. Syst. 25(8), 1460–1473 (2014)

    Article  Google Scholar 

  17. Z.J. Li, C.Y. Su, Neural-adaptive control of single-master multiple slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainty, IEEE Trans. Neural Netw. Learn. Syst. 24(9), 1400–1413 (2013)

    Article  Google Scholar 

  18. Z.J. Li, C.G. Yang, Neural-adaptive output control of a class of transportation vehicles based on wheeled inverted pendulum models. IEEE Trans. Control Syst. Technol. 20(6), 1583–1591 (2012)

    Article  Google Scholar 

  19. W.S. Lin, C.S. Chen, Robust adaptive sliding mode control using fuzzy modelling for a class of uncertain mimo nonlinear systems. IEEE Proc. Control Theory Appl. 149(3), 193–201 (2002)

    Article  Google Scholar 

  20. Y.J. Liu, S.C. Tong, C.L.P. Chen, Adaptive fuzzy control via observer design for uncertain nonlinear systems with unmodeled dynamics. IEEE Trans. Fuzzy Syst. 21(2), 275–288 (2013)

  21. Y.J. Liu, S.C. Tong, D. Wang, Adaptive neural output feedback controller design with reduced-order observer for a class of uncertain nonlinear SISO systems. IEEE Int. Neural Netw. 22(8), 1328–1334 (2011)

    Article  Google Scholar 

  22. Y.J. Liu, G.X. Wen, S.C. Tong, Adaptive neural output feedback tracking control for a class of uncertain discrete-time nonlinear systems. IEEE Int. Neural Netw. 22(7), 1162–1167 (2011)

    Article  Google Scholar 

  23. T.R. Oliveira, A.J. Peixoto, E.V.L. Nunes, Control of uncertain nonlinear systems with arbitrary relative degree and unknown control direction using sliding modes. Int. J. Adapt. Control Signal Process. 21(8), 692–707 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  24. M. Pu, Q.X. Wu, New fast terminal sliding mode and its application to near space vehicles. Acta Aeronaut. Astronaut. Sin. 32(7), 1283–1291 (2011)

    Google Scholar 

  25. M. Pu, Q.X. Wu, C.S. Jiang, L. Cheng, Adaptive second-order dynamic sliding-mode control based on fuzzy disturbance-observer. Control Theory Appl. 28(6), 805–812 (2011)

    MATH  Google Scholar 

  26. M. Pu, Q.X. Wu, C.S. Jiang, J. Zhang, Near space vehicle control based on second-order dynamic terminal sliding mode. J. Astronaut. 31(4), 1056–1062 (2010)

    Google Scholar 

  27. M.S. Qian, B. Jiang, D.Z. Xu, Fault tolerant tracking control scheme for UAV using dynamic surface control technique. Circuits Syst. Signal Process. 31(5), 1713–1729 (2012)

    Article  MathSciNet  Google Scholar 

  28. W.C. Sun, Y. Zhao, J. Li, Active suspension control with frequency band constraints and actuator input delay. IEEE Trans. Ind. Electron. 59(1), 530–537 (2012)

    Article  Google Scholar 

  29. W.C. Sun, Z. Zhao, H. Gao, Saturated adaptive robust control for active suspension systems. IEEE Trans. Ind. Electron. 60(9), 3889–3896 (2013)

    Article  Google Scholar 

  30. S.C. Tong, Y.M. Li, H.G. Zhang, Adaptive neural network decentralized backstepping output-feedback control for nonlinear large-scale systems with time delays. IEEE Trans. Neural Netw. 22(7), 1073–1086 (2011)

    Article  Google Scholar 

  31. H.Q. Wang, B. Chen, C. Lin, Adaptive neural control for strict-feedback stochastic nonlinear systems with time-delay. Neurocomputing 77(1), 267–274 (2012)

    Article  Google Scholar 

  32. H.Q. Wang, B. Chen, C. Lin, Adaptive neural tracking control for a class of perturbed pure-feedback nonlinear systems. Nonlinear Dyn. 72(2), 207–220 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  33. Y.F. Xu, B. Jiang, G. Tao, Z. Gao, Fault tolerant control for a class of nonlinear systems with application to near space vehicle. Circuits Syst. Signal Process. 30(3), 655–672 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  34. S. Yin, S.X. Ding, A. Haghani et al., A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process. J. Process Control 22(9), 1567–1581 (2012)

    Article  Google Scholar 

  35. S. Yin, S.X. Ding, A.H. Abandan Sari et al., Data-driven monitoring for stochastic systems and its application on batch process. Int. J. Syst. Sci. 44(7), 1366–1376 (2013)

    Article  MATH  Google Scholar 

  36. S. Yin, H. Luo, S. Ding, Real-time implementation of fault-tolerant control systems with performance optimization. IEEE Trans. Ind. Electron. 61(5), 2402–2411 (2013)

    Article  Google Scholar 

  37. X. Zhao, L. Zhang, P. Shi et al., Robust control of continuous-time systems with state-dependent uncertainties and its application to electronic circuits. IEEE Trans. Ind. Electron. 61(8), 4161–4170 (2014)

    Article  MathSciNet  Google Scholar 

  38. X.D. Zhao, H. Liu, J. Zhang et al., Multiple-mode observer design for a class of switched linear systems. IEEE Trans. Autom. Sci. Eng. PP(99), 1–9 (2013)

    Google Scholar 

  39. Y.S. Zhong, Globally stable adaptive system design for minimum phase SISO plants with input saturation. Automatica 41(9), 1539–1547 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  40. L. Zhou, Robust adaptive control for near space vehicles based on backstepping approach. Ph.D. thesis, Nanjing University of Aeronautics and Astronautics, Nanjing (2008)

  41. Y. L. Zhou, M. Chen, Sliding mode control for NSVs with input constraint using neural network and disturbance observer. 2013, 12, Article ID 904830 (2013)

  42. L. Zhu, C.S. Jiang, C.Y. Zhang, Adaptive trajectory linearization control for aerospace vehicle based on RBFNN disturbance observer. Acta Aeronaut. Astronaut. Sin. 28(3), 673–677 (2007)

    Google Scholar 

Download references

Acknowledgments

This work was partially supported by Jiangsu Natural Science Foundation of China (Granted Number: SBK20130033), National Natural Science Foundation of China (Granted Number: 61174102), and NUAA Research Funding (Granted Number: NS2013028).

Author information

Authors and Affiliations

  1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Jing Yu & Mou Chen

Authors
  1. Jing Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mou Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mou Chen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yu, J., Chen, M. Fault Tolerant Control for Near Space Vehicles with Input Saturation Using Disturbance Observer and Neural Networks. Circuits Syst Signal Process 34, 2091–2107 (2015). https://doi.org/10.1007/s00034-014-9939-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-014-9939-6

Keywords

Search

Navigation