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[期刊论文]

Neural Network-Based Co-Simulation Technology for Intelligent Contactors

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author:

Longfei, Tang (Longfei, Tang.) [1] | Zhiping, Han (Zhiping, Han.) [2] | Zhihong, Xu (Zhihong, Xu.) [3]

Indexed by:

EI

Abstract:

A simulation method of an intelligent contactor is presented by using a neural network to fit the proven relationship among the flux linkage, the electrical current, and the moving core displacement of a contactor in this article. First, the neural network algorithm is trained by the operational data of a contactor driven by a basic training circuit to solve the coil current. Then, a dynamic simulation program of the contactor model is constructed via combining the algorithm and dynamic differential equations. On this basis, by means of the co-simulation technology, the point-by-point closed-loop simulation between the control module and the contactor model is carried out. Accordingly, the co-simulation of an intelligent contactor based on a neural network is completed. The simulation method can avoid the complex finite-element modeling of a contactor and realize the model extraction of an arbitrary contactor. The extracted model can be combined with a drive circuit and any control strategy to perform the co-simulation, which is convenient for the flexible design of hardware control circuits and software control strategies of various intelligent contactors. © 1965-2012 IEEE.

Keyword:

Computer software Differential equations Digital storage Electric contactors Flexible electronics Intelligent control Neural networks

Community:

  • [ 1 ] [Longfei, Tang]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 2 ] [Zhiping, Han]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 3 ] [Zhihong, Xu]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China

Reprint 's Address:

  • [longfei, tang]school of electrical engineering and automation, fuzhou university, fuzhou; 350108, china

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Related Article:

Source :

IEEE Transactions on Magnetics

ISSN: 0018-9464

Year: 2020

Issue: 2

Volume: 56

1 . 7

JCR@2020

2 . 1 0 0

JCR@2023

ESI HC Threshold:115

JCR Journal Grade:3

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 20

30 Days PV: 2

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