Neural network based active vibration absorber with output feedback control

R. P. Ma; Alok Sinha

Neural network based active vibration absorber with output feedback control

Research output: Contribution to conference › Paper › peer-review

Abstract

A neural-network-based output feedback control system has been presented to suppress vibration in a flexible structure for a wide range of excitation frequencies. The control theory developed by Johnson (1971, 1972) is used; and a multi-layer neural network (MNN) is used to learn the mapping between the excitation frequency and optimal control gains. Numerical results are presented for a single-degree-of-freedom spring-mass system to illustrate the effectiveness of this neural network based output feedback vibration absorber.

Original language	English (US)
Pages	1023-1028
Number of pages	6
State	Published - 1994
Event	Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94) - St. Louis, MO, USA Duration: Nov 13 1994 → Nov 16 1994

Conference

Conference	Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94)
City	St. Louis, MO, USA
Period	11/13/94 → 11/16/94

All Science Journal Classification (ASJC) codes

General Engineering

Cite this

@conference{e68311d122e74a408d80d2974fd32001,

title = "Neural network based active vibration absorber with output feedback control",

abstract = "A neural-network-based output feedback control system has been presented to suppress vibration in a flexible structure for a wide range of excitation frequencies. The control theory developed by Johnson (1971, 1972) is used; and a multi-layer neural network (MNN) is used to learn the mapping between the excitation frequency and optimal control gains. Numerical results are presented for a single-degree-of-freedom spring-mass system to illustrate the effectiveness of this neural network based output feedback vibration absorber.",

author = "Ma, {R. P.} and Alok Sinha",

year = "1994",

language = "English (US)",

pages = "1023--1028",

note = "Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94) ; Conference date: 13-11-1994 Through 16-11-1994",

}

TY - CONF

T1 - Neural network based active vibration absorber with output feedback control

AU - Ma, R. P.

AU - Sinha, Alok

PY - 1994

Y1 - 1994

N2 - A neural-network-based output feedback control system has been presented to suppress vibration in a flexible structure for a wide range of excitation frequencies. The control theory developed by Johnson (1971, 1972) is used; and a multi-layer neural network (MNN) is used to learn the mapping between the excitation frequency and optimal control gains. Numerical results are presented for a single-degree-of-freedom spring-mass system to illustrate the effectiveness of this neural network based output feedback vibration absorber.

AB - A neural-network-based output feedback control system has been presented to suppress vibration in a flexible structure for a wide range of excitation frequencies. The control theory developed by Johnson (1971, 1972) is used; and a multi-layer neural network (MNN) is used to learn the mapping between the excitation frequency and optimal control gains. Numerical results are presented for a single-degree-of-freedom spring-mass system to illustrate the effectiveness of this neural network based output feedback vibration absorber.

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UR - http://www.scopus.com/inward/citedby.url?scp=0028732136&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0028732136

SP - 1023

EP - 1028

T2 - Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94)

Y2 - 13 November 1994 through 16 November 1994

ER -

Neural network based active vibration absorber with output feedback control

Abstract

Conference

All Science Journal Classification (ASJC) codes

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