IBLF-based finite-time adaptive fuzzy output-feedback control for uncertain MIMO nonlinear state-constrained systems

Yan Wei, Yueying Wang, Choon Ki Ahn, Dengping Duan

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

This article considers the problem of finite-time adaptive fuzzy output-feedback control design for multi-input–multioutput uncertain nonlinear systems subject to full state constraints. By employing the finite-time stability theory, a new finite-time adaptive fuzzy output-feedback control approach is proposed. An integral barrier Lyapunov functional is utilized to prevent all states from violating their constraints. Fuzzy logic systems are developed to approximate the uncertainties. A fuzzy state observer is constructed to estimate the unmeasurable states. Moreover, to handle the “explosion of complexity” issue in the backstepping control technique, a finite-time convergent differentiator is introduced to estimate the time derivatives of virtual control signals. The stability analysis showed that the control approach guarantees that all closed-loop signals are bounded, and the tracking errors converge to a small neighborhood of the origin in a finite time. Finally, the effectiveness of the proposed control scheme is confirmed by numerical simulations.

Original languageEnglish
Pages (from-to)3389-3400
Number of pages12
JournalIEEE Transactions on Fuzzy Systems
Volume29
Issue number11
DOIs
Publication statusPublished - 2021

Keywords

  • Adaptive fuzzy control
  • Finite time
  • Integral barrier Lyapunov function (iBLF)
  • Nonlinear systems
  • State constraints

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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