DocumentCode :
2720372
Title :
Vibration cancellation at multiple locations using neurocontrollers with real-time learning
Author :
Bozich, Daniel J. ; MacKay, H. Bruce
Author_Institution :
Science Applications Int. Corp., San Diego, CA, USA
fYear :
1991
fDate :
8-14 Jul 1991
Firstpage :
775
Abstract :
The simultaneous control of vibration at multiple locations on a vibrating machine or structure has been accomplished through the application of artificial neural networks. Examples are discussed which demonstrate the simultaneous control of up to four vibration generators on a structure to reduce vibrations at up to four arbitrary locations. The real-time neurocontroller described utilizes multiple-input-multiple-output (MIMO) neural networks. Vibration sensors mounted at the desired cancellation locations are not necessarily colocated with the vibration generators. The neurocontroller adaptively learns to control the generators such that equal and opposite waveforms are applied at the sensor locations, reducing the existing vibration waveforms at the sensors. This results in true time-domain waveform cancellation. Reductions of up to 20 dB±10 dB of both discrete-frequency and swept-frequency vibrations have been observed
Keywords :
adaptive systems; computerised control; learning systems; neural nets; real-time systems; vibration control; MIMO neural networks; adaptive systems; discrete frequency vibration; learning systems; neurocontrollers; real-time learning; sensor locations; swept-frequency vibrations; time-domain waveform cancellation; vibration cancellation; vibration control; vibration waveforms; Adaptive control; Artificial neural networks; Damping; Instruments; MIMO; Machinery; Neurocontrollers; Programmable control; Time domain analysis; Vibration control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
Type :
conf
DOI :
10.1109/IJCNN.1991.155433
Filename :
155433
Link To Document :
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