Adaptive fuzzy finite-time command filtered tracking control for permanent magnet synchronous motors

Xueting Yang, Jinpeng Yu, Qing Guo Wang, Lin Zhao, Haisheng Yu, Chong Lin

Research output: Contribution to journalArticlepeer-review

56 Citations (Scopus)

Abstract

This paper studies the position tracking control problem for permanent magnet synchronous motors (PMSMs) with parameter uncertainties. Firstly, the command filtered method is employed to overcome the “explosion of complexity” in traditional backstepping method. Then, in order to reduce the errors produced by command filters, error compensation mechanism is adopted. In addition, the finite-time control method makes the tracking error converge to the smaller neighborhood in the finite time. The adaptive fuzzy control is used to approximate the nonlinear functions. Finally, the simulation results proved the designed control method can overcome the influence of parameter uncertainties and achieve the satisfactory position tracking control.

Original languageEnglish
Pages (from-to)110-119
Number of pages10
JournalNeurocomputing
Volume337
DOIs
Publication statusPublished - 14 Apr 2019

Keywords

  • Adaptive fuzzy control
  • Command filter
  • Finite-time
  • Permanent magnet synchronous motors

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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