Skip to main content

Adaptive T–S Fuzzy Control Using Output Feedback: SISO Cases

  • Chapter
  • First Online:
  • 681 Accesses

Part of the book series: Communications and Control Engineering ((CCE))

Abstract

In Chaps. 5 and 6, we have presented adaptive state feedback control designs for state-space T–S fuzzy systems with unknown parameters to achieve state tracking and output tracking, respectively. However, in reality, many systems may have states that are unmeasurable. For this situation, output feedback designs are more practical than state feedback. In this chapter, we consider adaptive output feedback control for discrete-time single-input single-output (SISO) T–S fuzzy systems described by input–output models.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    \(\copyright \) [2012] IEEE. Parts of Sect. 7.2 are reprinted, with permission, from Qi et al. (2012a).

  2. 2.

    Parts of Sect. 7.3 are reproduced from Qi et al. (2012b) by permission of John Wiley & Sons Ltd.

References

  • Angelov PP, Filev DP (2004) An approach to online identification of Takagi–Sugeno fuzzy models. IEEE Trans Syst Man Cybern Part B Cybern 34(1):484–498

    Article  Google Scholar 

  • Barada S, Singh H (1998) Generating optimal adaptive fuzzy-neural models of dynamical systems with applications to control. IEEE Trans Syst Man Cybern Part C Appl Rev 28(3):297–313

    Article  Google Scholar 

  • Feng G (2010) Analysis and synthesis of fuzzy control systems: a model-based approach. CRC Press, Boca Raton

    Google Scholar 

  • Franklin GF, Powell JD, Workman M (1998) Digit Control Dyn Syst. Addison-Wesley, Reading

    Google Scholar 

  • Ghorbel F, Hung JH, Spong MW (1989) Adaptive control of flexible joint manipulators. IEEE Control Syst Mag 9(7):9–13

    Article  Google Scholar 

  • Goodwin GC, Sin KS (1984) Adaptive filtering prediction and control. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Ioannou PA, Sun J (1996) Robust adaptive control. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Qi R, Brdys M (2008) Stable indirect adaptive control based on discrete-time T–S fuzzy model. Fuzzy Sets Syst 159(8):900–925

    Article  MathSciNet  Google Scholar 

  • Qi R, Tao G, Jiang B, Tan C (2012a) Adaptive control schemes for discrete-time T–S fuzzy systems with unknown parameters and actuator failures. IEEE Trans Fuzzy Syst 20:471–486

    Article  Google Scholar 

  • Qi R, Tao G, Tan C, Yao X (2012b) Adaptive prediction and control of discrete-time T–S fuzzy systems. Int J Adapt Control Signal Process 26(7):560–575

    Article  MathSciNet  Google Scholar 

  • Shi W (2008) Indirect adaptive fuzzy control for a class of nonlinear discrete-time systems. J Syst Eng Electron 19(6):1203–1207

    Article  Google Scholar 

  • Tanaka K, Wang HO (2001) Fuzzy control system design and analysis: a LMI approach. Wiley, New York

    Book  Google Scholar 

  • Tanaka K, Ikeda T, Wang HO (1996) Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilizability, \(H^{\infty }\) control theory, and linear matrix inequalities. IEEE Trans Fuzzy Syst 4:1–13

    Google Scholar 

  • Tao G (2003) Adaptive control design and analysis. Wiley, New York

    Book  Google Scholar 

  • Tseng C-S (2006) Model reference output feedback fuzzy tracking control design for nonlinear discrete-time systems with time-delay. IEEE Trans Fuzzy Syst 14(1):58–70

    Article  Google Scholar 

  • Ying H (1999) Analytical analysis and feedback linearization tracking control of the general Takagi–Sugeno fuzzy dynamic systems. IEEE Trans Syst Man Cybern 29(1):290–298

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Qi, R., Tao, G., Jiang, B. (2019). Adaptive T–S Fuzzy Control Using Output Feedback: SISO Cases. In: Fuzzy System Identification and Adaptive Control. Communications and Control Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-19882-4_7

Download citation

Publish with us

Policies and ethics