基于扩展最小资源分配神经网络的主动隔振控制器

J. D. Fadly, M. Wahyudi, W. Faris
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引用次数: 4

摘要

本文采用已有的扩展最小资源分配网络(EMRAN)作为控制器,主动隔离震源对地基的振动。该源安装在源的前后两个被动弹性隔振器上,与被动隔振器平行放置一个作为反作用力的主动力致动器来抵消振动。假设振动源为正弦波,当向基础传递的总力最小时,即可实现隔振。通过在线训练控制器,EMRAN能够根据需要满足的特定标准来增加和减少其网络中隐藏层神经元的数量。该振动模型可以表示安装在底盘上的发动机,需要隔振以提高乘客的乘坐舒适性,或者在生产工厂中将机械安装到刚性地板上,其中隔振是必不可少的,不能影响其他机械。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Active vibration isolation controller using extended minimal resource allocation neural network (EMRAN)
In this paper a previously developed extended minimal resource allocation network (EMRAN) is applied as a controller to actively isolate the vibration from a source to the foundation. The source is mounted by using two passive elastomeric vibration isolators located at the front and rear of the source and an active force actuator acted as counter force to cancel the vibration is placed in parallel with the passive isolators. The source of vibration is assumed to be sinusoidal and vibration isolation is achieved when the total transmitted force to the foundation is minimized. By training the controller online EMRAN has the ability to add and prune the number of hidden layer neurons of its network based on a certain criteria that needs to be satisfied. This vibration model can be a representation of an engine mounted to its chassis and vibration isolation is needed to improve the passengerspsila ride comfort or the mounting of machinery to a rigid floor in a production plant where vibration isolation is essential not to influence other machineries.
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