• DocumentCode
    1386162
  • Title

    Data-Driven Model-Free Adaptive Control for a Class of MIMO Nonlinear Discrete-Time Systems

  • Author

    Hou, Zhongsheng ; Jin, ShangTai

  • Author_Institution
    Adv. Control Syst. Lab., Beijing Jiaotong Univ., Beijing, China
  • Volume
    22
  • Issue
    12
  • fYear
    2011
  • Firstpage
    2173
  • Lastpage
    2188
  • Abstract
    In this paper, a data-driven model-free adaptive control (MFAC) approach is proposed based on a new dynamic linearization technique (DLT) with a novel concept called pseudo-partial derivative for a class of general multiple-input and multiple-output nonlinear discrete-time systems. The DLT includes compact form dynamic linearization, partial form dynamic linearization, and full form dynamic linearization. The main feature of the approach is that the controller design depends only on the measured input/output data of the controlled plant. Analysis and extensive simulations have shown that MFAC guarantees the bounded-input bounded-output stability and the tracking error convergence.
  • Keywords
    MIMO systems; adaptive control; control system synthesis; convergence; discrete time systems; linearisation techniques; nonlinear control systems; stability; tracking; MFAC; MIMO nonlinear discrete-time system; bounded-input bounded-output stability; data-driven model-free adaptive control; dynamic linearization technique; multiple-input multiple-output nonlinear discrete-time system; pseudopartial derivative; tracking error convergence; Adaptive control; Discrete time systems; MIMO; Nonlinear dynamical systems; Compact form dynamic linearization; data-driven control; model-free adaptive control; multiple-input and multiple-output nonlinear system; partial form dynamic linearization; pseudo-partial derivative; stability; Artificial Intelligence; Data Mining; Databases, Factual; Feedback; Nonlinear Dynamics; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Neural Networks, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1045-9227
  • Type

    jour

  • DOI
    10.1109/TNN.2011.2176141
  • Filename
    6093751