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Adaptive fuzzy asymptotical tracking control of nonlinear systems with unmodeled dynamics and quantized actuator

  • Huanqing Wang
  • , Peter Xiaoping Liu
  • , Xuejun Xie
  • , Xiaoping Liu
  • , Tasawar Hayat
  • , Fuad E. Alsaadi
  • Bohai University
  • Carleton University
  • Qufu Normal University
  • Lakehead University
  • Quaid-I-Azam University
  • Faculty of Engineering, King Abdulaziz University

Research output: Contribution to journalArticlepeer-review

80 Scopus citations

Abstract

This paper studies the problem of adaptive fuzzy asymptotical quantized tracking control of non-strict-feedback systems with unmodeled dynamics. A dynamic signal is used to cope with the unmodeled dynamics and fuzzy systems are introduced to approximate the packaged unknown nonlinearities. Based on backstepping technique and fuzzy approximation property, a systemic fuzzy adaptive control scheme is proposed. By the utilization of Lyapunov theory, the semi-globally uniformly ultimate boundedness of all closed-loop system signals and asymptotical tracking performance are guaranteed. The main contributions of this work are two aspects: (i) a backstepping-based quantized control algorithm is firstly extended to nonlinear systems with unmodeled dynamics and non-strict-feedback structure; (ii) the semi-globally asymptotic tracking control scheme is independent of the quantized parameter. Simulation results verify the presented control approach.

Original languageEnglish
Pages (from-to)779-792
Number of pages14
JournalInformation Sciences
Volume575
DOIs
StatePublished - Oct 2021
Externally publishedYes

Keywords

  • Adaptive fuzzy control
  • Input quantization
  • Non-strict-feedback systems
  • Unmodeled dynamics

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