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

doi:10.1016/j.neucom.2019.01.057

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

Electrical and Electronic Engineering Science

Qingdao University

Research output: Contribution to journal › Article › peer-review

61 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 language	English
Pages (from-to)	110-119
Number of pages	10
Journal	Neurocomputing
Volume	337
DOIs	https://doi.org/10.1016/j.neucom.2019.01.057
Publication status	Published - 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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10.1016/j.neucom.2019.01.057

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title = "Adaptive fuzzy finite-time command filtered tracking control for permanent magnet synchronous motors",

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.",

keywords = "Adaptive fuzzy control, Command filter, Finite-time, Permanent magnet synchronous motors",

author = "Xueting Yang and Jinpeng Yu and Wang, {Qing Guo} and Lin Zhao and Haisheng Yu and Chong Lin",

note = "Publisher Copyright: {\textcopyright} 2019 Elsevier B.V.",

year = "2019",

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AU - Yang, Xueting

AU - Yu, Jinpeng

AU - Wang, Qing Guo

AU - Zhao, Lin

AU - Yu, Haisheng

AU - Lin, Chong

PY - 2019/4/14

Y1 - 2019/4/14

N2 - 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.

AB - 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.

KW - Adaptive fuzzy control

KW - Command filter

KW - Finite-time

KW - Permanent magnet synchronous motors

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SN - 0925-2312

VL - 337

SP - 110

EP - 119

JO - Neurocomputing

JF - Neurocomputing

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

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