Advertisement

Science China Information Sciences

, Volume 54, Issue 3, pp 460–468 | Cite as

Fuzzy dynamic characteristic modeling and adaptive control of nonlinear systems and its application to hypersonic vehicles

  • HongBo LiEmail author
  • ZengQi Sun
  • HaiBo Min
  • JianQiu Deng
Research Papers Special Focus

Abstract

In this paper, a fuzzy dynamic characteristic modeling and adaptive control method is proposed for a class of nonlinear systems. By employing fuzzy dynamic characteristic model, the controlled plant is described as a slowly time-varying fuzzy system, wherein the parameters are estimated online by using recursive Least-Squares algorithm. Under this framework, a fuzzy adaptive controller is constructed, and the stability condition of the closed-loop system is also derived. The main advantage of the proposed method lies in no requirement for the prior knowledge of system model and less parameters to tune, which allows engineers to operate it in a simple, straightforward manner. The proposed method is applied to the control of hypersonic vehicle, and simulation results are given to demonstrate the effectiveness of the obtained results.

Keywords

fuzzy control dynamic characteristic model adaptive control hypersonic vehicle 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ma X J, Sun Z Q, He Y. Analysis and design of fuzzy controller and fuzzy observer. IEEE Trans Fuzzy Syst, 1998, 6: 41–51CrossRefGoogle Scholar
  2. 2.
    Feng M, Harris C J. Piecewise Lyapunov stability conditions of fuzzy systems. IEEE Trans Syst Man Cybern B, 2001, 31: 259–262CrossRefGoogle Scholar
  3. 3.
    Tanaka K, Wang H O. Fuzzy Control Systems Design and Analysis: A LMI Approach. New York: Wiley, 2001CrossRefGoogle Scholar
  4. 4.
    Feng G. Stability analysis of discrete time fuzzy dynamic systems based on piecewise Lyapunov functions. IEEE Trans Fuzzy Syst, 2004, 12: 22–28CrossRefGoogle Scholar
  5. 5.
    Wang W J, Sun C H. Relaxed stability and stabilization conditions for a T-S fuzzy discrete system. Fuzzy Sets Syst, 2005, 156: 208–225zbMATHCrossRefGoogle Scholar
  6. 6.
    Feng G. A survey on analysis and design of model-based fuzzy control systems. IEEE Trans Fuzzy Syst, 2006, 14: 676–697CrossRefGoogle Scholar
  7. 7.
    Tanaka K, Hori T, Wang H O. A multiple Lyapunov function approach to stabilization of fuzzy control systems. IEEE Trans Fuzzy Syst, 2003, 11: 582–589CrossRefGoogle Scholar
  8. 8.
    Choi D J, Park P G. H-infinity state-feedback controller design for discrete-time fuzzy systems using fuzzy weighting-dependent Lyapunov functions. IEEE Trans Fuzzy Syst, 2003, 11: 271–278CrossRefGoogle Scholar
  9. 9.
    Chen B, Liu X P, Tong S C, et al. Observer-based stabilization of T-S fuzzy systems with input Delay. IEEE Trans Fuzzy Syst, 2008, 16: 652–663CrossRefGoogle Scholar
  10. 10.
    Zhang Y S, Xu S Y, Zhang B Y. Robust output feedback stabilization for uncertain discrete-time fuzzy markovian jump systems with time-varying delays. IEEE Trans Fuzzy Syst, 2009, 17: 411–420CrossRefGoogle Scholar
  11. 11.
    Gao H J, Zhao Y, Chen T W. H-infinity fuzzy control of nonlinear systems under unreliable communication links. IEEE Trans Fuzzy Syst, 2009, 17: 265–278CrossRefGoogle Scholar
  12. 12.
    Zhang T J, Feng G, Zeng X J. Output tracking of constrained nonlinear processes with offset-free input-to-state stable fuzzy predictive control. Automatica, 2009, 45: 900–909MathSciNetzbMATHCrossRefGoogle Scholar
  13. 13.
    Wu H X, Liu Y W, Liu Z H, et al. Characteristic modeling and the control of flexible structure. Sci China Ser F-Inf Sci, 2001, 44: 278–291zbMATHGoogle Scholar
  14. 14.
    Wu H X, Wang Y C, Xin Y. Intelligent control based on intelligent characteristic model and its application. Sci China Ser F-Inf Sci, 2003, 46: 225–241CrossRefGoogle Scholar
  15. 15.
    Lei Y J, Wu H X. Tracking control of robotic manipulators based on the all-coefficient adaptive control method. Int J Control Auto Syst, 2006, 4: 139–145Google Scholar
  16. 16.
    Wu H X, Wu J, Xie Y C. Characteristic model-based all-coefficient adaptive control method and its applications. IEEE Trans Syst Man Cyb C, 2007, 37: 213–221MathSciNetCrossRefGoogle Scholar
  17. 17.
    Wu H X, Wu J, Xie Y C. Intelligent Adaptive Control Based on Characteristic Model (in Chinese). Beijing: Chinese Science and Technology Press, 2009Google Scholar
  18. 18.
    Luo X, Sun Z Q, Sun F C. A new approach to fuzzy modeling and control for nonlinear dynamic systems: neuro-fuzzy dynamic characteristic modeling and adaptive control mechanism. Int J Control Auto Syst, 2009, 7: 123–132CrossRefGoogle Scholar
  19. 19.
    Constantin P, Jacob B, Silviu C. A robust variable forgetting factor recursive least-squares algorithm for system identification. IEEE Sig Proc Lett, 2008, 15: 597–600CrossRefGoogle Scholar
  20. 20.
    Xu H J, Mirmirani M, Ioannou P A. Robust neural adaptive control of a hypersonic aircraft. In: AIAA Guidance, Navigation, and Control Conference, AIAA, Austin, Texas, 2003. 1–11Google Scholar
  21. 21.
    Xu H J, Ioannou P A, Mirmirani M. Adaptive sliding mode control design for a hypersonic flight vehicle. J Guid Control Dyn, 2004, 27: 829–838CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • HongBo Li
    • 1
    Email author
  • ZengQi Sun
    • 1
  • HaiBo Min
    • 1
  • JianQiu Deng
    • 1
  1. 1.Department of Computer Science and TechnologyTsinghua UniversityBeijingChina

Personalised recommendations