频域神经网络在非线性结构系统谐波主动控制中的应用

T. J. Sutton, S. J. Elliott
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引用次数: 1

摘要

作者展示了如何使用准神经结构的非线性自适应控制器来控制谐波振动,即使它必须通过非线性执行器元件来控制。该控制器包括用于产生正弦参考信号谐波的固定非线性和线性自适应合成器。采用考虑被控非线性系统谐波产生的最陡下降算法对自适应组合器的系数进行调整。讨论了非线性系统的频域描述的神经模型,并表明在最陡下降算法中使用该模型导出的信息相当于通过植物模型反向传播误差信号。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of frequency-domain neural networks to the active control of harmonic vibrations in nonlinear structural systems
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.<>
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