• DocumentCode
    3601573
  • Title

    Relative Degrees and Adaptive Feedback Linearization Control of T–S Fuzzy Systems

  • Author

    Yanjun Zhang ; Gang Tao ; Mou Chen

  • Author_Institution
    Coll. of Autom. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China
  • Volume
    23
  • Issue
    6
  • fYear
    2015
  • Firstpage
    2215
  • Lastpage
    2230
  • Abstract
    This paper presents a new study on the relative degrees of single-input and single-output T-S fuzzy systems in general noncanonical forms, and proposes a feedback linearization-based control design method for such systems. The study extends the system relative degree concepts, commonly used for the control of nonlinear systems, to general T-S fuzzy systems, derives various relative degree conditions for general T-S fuzzy systems, and establishes the relative degree dependent normal forms. A feedback linearization-based control design framework is developed for general T-S fuzzy systems using its normal form, to achieve closed-loop stability and asymptotic output tracking under relaxed design conditions. A new adaptive feedback linearization-based control scheme for T-S fuzzy systems in general noncanonical forms with parameter uncertainties is designed and analyzed. Some extensions of relative degrees and their possible application to robust adaptive control for noncanonical form T-S fuzzy systems are also demonstrated. An illustrative example is presented with simulation results to demonstrate the control system design procedure and to show the effectiveness of the proposed control scheme.
  • Keywords
    adaptive control; closed loop systems; control system synthesis; feedback; fuzzy control; linearisation techniques; multivariable control systems; robust control; T-S fuzzy systems; adaptive feedback linearization control; asymptotic output tracking; closed-loop stability; feedback linearization-based control system design; noncanonical form T-S fuzzy system; relative degree conditions; relaxed design conditions; robust adaptive control; single-input single-output T-S fuzzy system; Adaptation models; Adaptive systems; Approximation methods; Bismuth; Control systems; Fuzzy systems; Nonlinear systems; Feedback linearization; T-S fuzzy systems.; T???S fuzzy systems; normal form; output tracking; relative degree;
  • fLanguage
    English
  • Journal_Title
    Fuzzy Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-6706
  • Type

    jour

  • DOI
    10.1109/TFUZZ.2015.2412138
  • Filename
    7058407