Neural network based active vibration absorber with output feedback control

R. P. Ma, Alok Sinha

Research output: Contribution to conferencePaper

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 languageEnglish (US)
Pages1023-1028
Number of pages6
StatePublished - Dec 1 1994
EventProceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94) - St. Louis, MO, USA
Duration: Nov 13 1994Nov 16 1994

Conference

ConferenceProceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94)
CitySt. Louis, MO, USA
Period11/13/9411/16/94

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Ma, R. P., & Sinha, A. (1994). Neural network based active vibration absorber with output feedback control. 1023-1028. Paper presented at Proceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94), St. Louis, MO, USA, .