A Neural Network for Feedforward Controlled Smart Structures

Author:

Snyder Scott D.1,Tanaka Nobuo1

Affiliation:

1. Vibration Engineering Division Mechanical Engineering Laboratories Ministry of International Trade and Industry 1-2 Namiki, Tsukuba Science City, Ibaraki 305, Japan

Abstract

A neural network and adaptive algorithm suitable for driving non-linear feedforward control systems used with "smart" structures to actively control sound and vibration is presented. The neural network/algorithm combination can be viewed as an extension to the commonly used transversal filter/filtered-x LMS algorithm combination, in that the neural network is essentially a transversal filter with a non-linear hidden layer placed between the input delay chain and output ac cumulator. The algorithm accommodates the transfer function and time delay between the control signal output and error signal input. The arrangement is shown in simulation to be capable of sup pressing a primary distrubance, which is a non-linear function of the reference signal fed to the con trol filter, and of suppressing harmonics introduced into a system by a control actuator exhibiting non-linear performance characteristics. The results are compared to those similarly obtained using a linear adaptive control arrangement, which is incapable of providing attenuation in either case.

Publisher

SAGE Publications

Subject

Mechanical Engineering,General Materials Science

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Active Vibration Control for Lathe Based Neural Network;Applied Mechanics and Materials;2011-08

2. Precision control of piezoelectric actuated mechanism in scanning tunneling microscope;2010 8th World Congress on Intelligent Control and Automation;2010-07

3. NEURAL ADAPTIVE CONTROL FOR VIBRATION SUPPRESSION IN COMPOSITE FIN-TIP OF AIRCRAFT;International Journal of Neural Systems;2008-06

4. Vibration Control of Smart Composite Laminated Spherical Shell using Neural Network;Journal of Intelligent Material Systems and Structures;2007-10-17

5. Variable semi-active TLCD damper applying artifical neural networks;SPIE Proceedings;2003-07-31

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