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

  • Ruiyun Qi
  • Gang Tao
  • Bin Jiang
Part of the Communications and Control Engineering book series (CCE)


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.


  1. 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):484–498CrossRefGoogle Scholar
  2. 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):297–313CrossRefGoogle Scholar
  3. Feng G (2010) Analysis and synthesis of fuzzy control systems: a model-based approach. CRC Press, Boca RatonGoogle Scholar
  4. Franklin GF, Powell JD, Workman M (1998) Digit Control Dyn Syst. Addison-Wesley, ReadingGoogle Scholar
  5. Ghorbel F, Hung JH, Spong MW (1989) Adaptive control of flexible joint manipulators. IEEE Control Syst Mag 9(7):9–13CrossRefGoogle Scholar
  6. Goodwin GC, Sin KS (1984) Adaptive filtering prediction and control. Prentice-Hall, Englewood CliffsGoogle Scholar
  7. Ioannou PA, Sun J (1996) Robust adaptive control. Prentice-Hall, Englewood CliffsGoogle Scholar
  8. Qi R, Brdys M (2008) Stable indirect adaptive control based on discrete-time T–S fuzzy model. Fuzzy Sets Syst 159(8):900–925MathSciNetCrossRefGoogle Scholar
  9. 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 20:471–486CrossRefGoogle Scholar
  10. 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):560–575MathSciNetCrossRefGoogle Scholar
  11. Shi W (2008) Indirect adaptive fuzzy control for a class of nonlinear discrete-time systems. J Syst Eng Electron 19(6):1203–1207CrossRefGoogle Scholar
  12. Tanaka K, Wang HO (2001) Fuzzy control system design and analysis: a LMI approach. Wiley, New YorkCrossRefGoogle Scholar
  13. 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 4:1–13Google Scholar
  14. Tao G (2003) Adaptive control design and analysis. Wiley, New YorkCrossRefGoogle Scholar
  15. 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):58–70CrossRefGoogle Scholar
  16. 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):290–298Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ruiyun Qi
    • 1
  • Gang Tao
    • 2
  • Bin Jiang
    • 1
  1. 1.College of Automation EngineeringNanjing University of Aeronautics and AstronauticsNanjingChina
  2. 2.School of Engineering and Applied ScienceUniversity of VirginiaCharlottesvilleUSA

Personalised recommendations