Skip to main content
SpringerLink
Log in

An adaptive fuzzy design for fault-tolerant control of MIMO nonlinear uncertain systems

  • Published:
Journal of Control Theory and Applications Aims and scope Submit manuscript

Abstract

This paper presents a novel control method for accommodating actuator faults in a class of multiple-input multiple-output (MIMO) nonlinear uncertain systems. The designed control scheme can tolerate both the time-varying lock-in-place and loss of effectiveness actuator faults. In each subsystem of the considered MIMO system, the controller is obtained from a backstepping procedure; an adaptive fuzzy approximator with minimal learning parameterization is employed to approximate the package of unknown nonlinear functions in each design step. Additional control effort is taken to deal with the approximation error and external disturbance together. It is proven that the closed-loop stability and desired tracking performance can be guaranteed by the proposed control scheme. An example is used to show the effectiveness of the designed controller.

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

Similar content being viewed by others

References

  1. J. D. Boskovic, R. K. Mehra. Stable multiple model adaptive flight control for accommodation of a large class of control effector failures[C]//Proceedings of the American Control Conference. New York: IEEE, 1999: 1920–1924.

    Google Scholar 

  2. X. D. Zhang, T. Parisini, M. M. Polycarpou. Adaptive faulttolerant control of nonlinear uncertain systems: an information-based diagnostic approach[J]. IEEE Transactions on Automatic Control, 2004, 49(8): 1259–1274.

    Article  MathSciNet  Google Scholar 

  3. X. Zhang, Y. Liu, R. Rysdyk, et al. An intelligent hierarchical approach to actuator fault diagnosis and accommodation[C]//IEEE Aerospace Conference. New York: IEEE, 2006: 1–14.

    Chapter  Google Scholar 

  4. H. Xue, J. G. Jiang. Fault detection and accommodation for nonlinear systems using fuzzy neural networks[C]//CES/IEEE 5th International Power Electronics and Motion Control Conference. New York: IEEE, 2006: 1–5.

    Chapter  Google Scholar 

  5. D. Ye, G. Yang. Adaptive fault-tolerant tracking control against actuator faults with application to flight control[J]. IEEE Transactions on Control Systems Technology, 2006, 14(6): 1088–1096.

    Article  Google Scholar 

  6. G. Tao, S. Chen, X. Tang, et al. Adaptive Control of Systems with Actuator Failures[M]. London: Springer-Verlag, 2004.

    Google Scholar 

  7. X. Tang, G. Tao, S. M. Joshi. Virtual grouping based adaptive actuator failure compensation for MIMO nonlinear systems[J]. IEEE Transactions on Automatic Control, 2005, 50(11): 1775–1780.

    Article  MathSciNet  Google Scholar 

  8. X. Tang, G. Tao, S. M. Joshi. Adaptive actuator failure compensation for nonlinear MIMO systems with an aircraft control application[J]. Automatica, 2007, 43(11): 1869–1883.

    Article  MathSciNet  MATH  Google Scholar 

  9. P. Li, G. Yang. Adaptive fuzzy control of unknown nonlinear systems with actuator failures for robust output tracking[C]//Proceedings of the American Control Conference. New York: IEEE, 2008: 4898–4903.

    Google Scholar 

  10. P. Li, G. Yang. Adaptive fuzzy fault-tolerant control for unknown nonlinear systems with disturbances[C]//Proceedings of the 47th IEEE Conference on Decision and Control. New York: IEEE, 2008: 417–422.

    Google Scholar 

  11. L. Wang. Stable adaptive fuzzy control of nonlinear systems[J]. IEEE Transactions on Fuzzy Systems, 1993, 1(2): 146–155.

    Article  Google Scholar 

  12. B. Chen, C. Lee, Y. Chang. H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach[J]. IEEE Transactions on Fuzzy Systems, 1996, 4(1): 32–43.

    Article  Google Scholar 

  13. T. J. Koo. Stable model reference adaptive fuzzy control of a class of nonlinear systems[J]. IEEE Transactions on Fuzzy Systems, 2001, 9(4): 624–636.

    Article  MathSciNet  Google Scholar 

  14. H. Han, C. Su, Y. Stepanenko. Adaptive control of a class of nonlinear systems with nonlinearly parameterized fuzzy approximators[J]. IEEE Transactions on Fuzzy Systems, 2001, 9(2): 315–323.

    Article  Google Scholar 

  15. M. Hojati, S. Gazor. Hybrid adaptive fuzzy identification and control of nonlinear systems[J]. IEEE Transactions on Fuzzy Systems, 2002, 10(2): 198–210.

    Article  Google Scholar 

  16. Y. Yang, G. Feng, J. Ren. A combined backstepping and smallgain approach to robust adaptive fuzzy control for strict-feedback nonlinear systems[J]. IEEE Transactions on Systems, Man and Cybernetics, Part A, 2004, 34(3): 406–420.

    Article  Google Scholar 

  17. Y. Yang, C. Zhou. Adaptive fuzzy H∞ stabilization for strictfeedback canonical nonlinear systems via backstepping and smallgain approach[J]. IEEE Transactions on Fuzzy Systems, 2005, 13(1): 104–114.

    Article  Google Scholar 

  18. S. Tong, Y. Li. Direct adaptive fuzzy backstepping control for nonlinear systems[C]//First International Conference on Innovative Computing, Information and Control. Los Alamitos, CA: IEEE Computer Society, 2006: 623–627.

    Chapter  Google Scholar 

  19. B. Chen, X. Liu, K. Liu, et al. Direct adaptive fuzzy control of nonlinear strict-feedback systems[J]. Automatica, 2009, 45(6): 1530–1535.

    Article  MATH  Google Scholar 

  20. H. Li, S. Tong. A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems[J]. IEEE Transactions on Fuzzy Systems, 2003, 11(1): 24–34.

    Article  Google Scholar 

  21. M. Zhang, H. Zhang, D. Liu. Robust adaptive fuzzy output control for nonlinear uncertain systems[C]//Proceedings of the 44th IEEE Conference on Decision and Control. New York: IEEE, 2005: 7846–7851.

    Chapter  Google Scholar 

  22. B. Chen, X. Liu, S. Tong. Adaptive fuzzy output tracking control of mimo nonlinear uncertain systems[J]. IEEE Transactions on Fuzzy Systems, 2007, 15(2): 287–300.

    Article  Google Scholar 

  23. B. Chen, X. Liu, K. Liu, et al. Novel adaptive neural control design for nonlinear MIMO time-delay systems[J]. Automatica, 2009, 45(6): 1554–1560.

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Information Science and Engineering, Huaqiao University, Xiamen Fujian, 361021, China

    Ping Li

  2. College of Information Science and Engineering, Northeastern University, Shenyang Liaoning, 110004, China

    Ping Li & Guanghong Yang

Authors
  1. Ping Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guanghong Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ping Li.

Additional information

This work was supported by the Research Start Project for Talents of Huaqiao University (No. 10BS108), the Project of Technology Plan of Fujian Province (No. 2009H0033), the Funds for Creative Research Groups of China (No. 60821063), and the National Natural Science Foundation of China (No. 60974043, 60904010).

Ping LI is a Ph.D. candidate at the College of Information Science and Engineering, Northeastern University. Her research interests include fault-tolerant control, adaptive fuzzy control and backstepping control.

Guanghong YANG is a professor at Northeastern University. His current research interests cover faulttolerant control, fault detection and isolation, and robust control. He is also a senior member of IEEE, an associate editor for the International Journal of Control, Automation and Systems (IJCAS), and an associate editor of the Conference Editorial Board of IEEE Control Systems Society.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Li, P., Yang, G. An adaptive fuzzy design for fault-tolerant control of MIMO nonlinear uncertain systems. J. Control Theory Appl. 9, 244–250 (2011). https://doi.org/10.1007/s11768-011-8167-x

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11768-011-8167-x

Keywords

Search

Navigation