DocumentCode :
3416380
Title :
Application of frequency-domain neural networks to the active control of harmonic vibrations in nonlinear structural systems
Author :
Sutton, T.J. ; Elliott, S.J.
Author_Institution :
Inst. of Sound & Vibration Res., Southampton Univ., UK
fYear :
1992
fDate :
31 Aug-2 Sep 1992
Firstpage :
474
Lastpage :
483
Abstract :
The authors show how a nonlinear adaptive controller of quasi-neural architecture can be used to control harmonic vibrations even when it has to act through a nonlinear actuator element. The controller comprises a fixed nonlinearity to generate harmonics of the sinusoidal reference signal and a linear adaptive combiner. The coefficients in the adaptive combiner are adjusted using a steepest descent algorithm in which harmonic generation in the nonlinear system under control is taken into account. A neural model for this frequency domain description of a nonlinear system is discussed, and it is shown that using information derived from this model in the steepest descent algorithm amounts to backpropagating the error signal through the plant model
Keywords :
adaptive control; backpropagation; frequency-domain analysis; harmonics; neural nets; nonlinear control systems; vibration control; active control; backpropagating; coefficients; error signal; frequency-domain neural networks; harmonic generation; harmonic vibrations; linear adaptive combiner; neural model; nonlinear actuator element; nonlinear adaptive controller; nonlinear structural systems; plant model; sinusoidal reference signal; steepest descent algorithm; Actuators; Adaptive control; Control systems; Frequency conversion; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Signal generators; Vibration control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks for Signal Processing [1992] II., Proceedings of the 1992 IEEE-SP Workshop
Conference_Location :
Helsingoer
Print_ISBN :
0-7803-0557-4
Type :
conf
DOI :
10.1109/NNSP.1992.253665
Filename :
253665
Link To Document :
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