Adaptive Fuzzy Full-State and Output-Feedback Control for Uncertain Robots with Output Constraint

Xinbo Yu, Wei He*, Hongyi Li, Jian Sun

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

183 Citations (Scopus)

Abstract

This article focuses on the tracking control issue of robotic systems with dynamic uncertainties. To enhance tracking accuracy in a robotic manipulator with uncertainties, an adaptive fuzzy full-state feedback control is proposed. In view of output-feedback control with unknown states, a high-gain observer is employed to estimate unknown states. Considering the particular requirement that output of systems should be constrained in some practical working fields, we further design adaptive fuzzy full-state and output-feedback control schemes with output constraint to ensure that output maintains in constrained regions. By applying the Lyapunov theory, it is guaranteed that closed-loop systems are semiglobally uniformly ultimately bounded (SGUUB). Tangent-type barrier Lyapunov function is used for the controller design with output constraint and ensure stability. Finally, the effectiveness of our proposed methods is shown through both simulation examples and experimental results, comparative experiments in Baxter robot are proposed for evaluating the practicability of our proposed methods in actual applications.

Original languageEnglish
Pages (from-to)6994-7007
Number of pages14
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume51
Issue number11
DOIs
Publication statusPublished - 1 Nov 2021

Keywords

  • Adaptive fuzzy full-state and output-feedback control
  • barrier Lyapunov functions (BLFs)
  • dynamic uncertainties
  • output constraint
  • robot

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