The system identification for the hydrostatic drive system of secondary regulation using neural networks

Guangqiang Wu; Qinghe Liu; Keding Zhao; Shangyi Li; Shenglin Wu

doi:10.4271/962231

The system identification for the hydrostatic drive system of secondary regulation using neural networks

Guangqiang Wu^*
, Qinghe Liu
, Keding Zhao
, Shangyi Li
, Shenglin Wu

^*Corresponding author for this work

School of Automotive Engineering

Tongji University
Harbin Institute of Technology

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

In this paper, the system identification theory and method using dynamic neural networks are presented, the multilayer feedforward networks employed, the backpropagation with adaptive learning rate algorithms proposed. Finally the comparision of network output with that of the hydrostatic drive system of secondary regulation is given, and output error, sum-squared error et al, or the results that embody the effect of system identification given sine input to it are provided.

Original language	English
Journal	SAE Technical Papers
DOIs	https://doi.org/10.4271/962231
State	Published - 1996
Event	International Truck and Bus Meeting and Exposition - Detroit, MI, United States Duration: 14 Oct 1996 → 16 Oct 1996

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@article{635b5a18b2b847bca664121aafd13df9,

title = "The system identification for the hydrostatic drive system of secondary regulation using neural networks",

abstract = "In this paper, the system identification theory and method using dynamic neural networks are presented, the multilayer feedforward networks employed, the backpropagation with adaptive learning rate algorithms proposed. Finally the comparision of network output with that of the hydrostatic drive system of secondary regulation is given, and output error, sum-squared error et al, or the results that embody the effect of system identification given sine input to it are provided.",

author = "Guangqiang Wu and Qinghe Liu and Keding Zhao and Shangyi Li and Shenglin Wu",

year = "1996",

doi = "10.4271/962231",

language = "英语",

journal = "SAE Technical Papers",

issn = "0148-7191",

publisher = "SAE International",

note = "International Truck and Bus Meeting and Exposition ; Conference date: 14-10-1996 Through 16-10-1996",

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TY - JOUR

T1 - The system identification for the hydrostatic drive system of secondary regulation using neural networks

AU - Wu, Guangqiang

AU - Liu, Qinghe

AU - Zhao, Keding

AU - Li, Shangyi

AU - Wu, Shenglin

PY - 1996

Y1 - 1996

N2 - In this paper, the system identification theory and method using dynamic neural networks are presented, the multilayer feedforward networks employed, the backpropagation with adaptive learning rate algorithms proposed. Finally the comparision of network output with that of the hydrostatic drive system of secondary regulation is given, and output error, sum-squared error et al, or the results that embody the effect of system identification given sine input to it are provided.

AB - In this paper, the system identification theory and method using dynamic neural networks are presented, the multilayer feedforward networks employed, the backpropagation with adaptive learning rate algorithms proposed. Finally the comparision of network output with that of the hydrostatic drive system of secondary regulation is given, and output error, sum-squared error et al, or the results that embody the effect of system identification given sine input to it are provided.

UR - https://www.scopus.com/pages/publications/85072458576

U2 - 10.4271/962231

DO - 10.4271/962231

M3 - 会议文章

AN - SCOPUS:85072458576

SN - 0148-7191

JO - SAE Technical Papers

JF - SAE Technical Papers

T2 - International Truck and Bus Meeting and Exposition

Y2 - 14 October 1996 through 16 October 1996

ER -

The system identification for the hydrostatic drive system of secondary regulation using neural networks

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