权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

VIBRATION CONTROL OF HIGH-RISE BUILDINGS USING NEURAL NETWORK TOKYO DENKI UNIVERSITY, DEPARTMENT OF MECHANICAL ENGINEERING

使用神经网络进行高层建筑的振动控制东京电机大学机械工程系

基本信息

批准号：
03650218
负责人：
FUJITA Satoshi
金额：
$ 1.28万
依托单位：
TOKYO DENKI UNIVERSITY
依托单位国家：
日本
项目类别：
Grant-in-Aid for General Scientific Research (C)
财政年份：
1991
资助国家：
日本
起止时间：
1991 至 1992
项目状态：
已结题

项目摘要

For mitigation of vibration induced in high-rise buildings subjected to wind or earthquake, an active mass damper was manufactured for a building model, which was equipped with a linear moter as an actuator and was digitally controlled by means of optimal feedback theory. In addition, an alternative control method using neural network model was considered in this program. In the first year of this project, the dynamic tests for the three story steel framed building model uisng a shaking table were carried out to investigate the performance of the optimally controlled active mass damper. The results showed that the responses of the building model were sufficiently reduced to about a half of the uncontrolled responses due to earthquake inputs. In the following year, an analytical model with the building model for the active mass damper was established to examine the dynamic responses of that subjected to several types of wind and earthquake. As a result, the fundamental design data on the active mass damper were obtained. Consequently, a neural network control system was built system was built on a 32 bit personal computer. This system comprises System Neural Network for system identification and Control Neural Network for obtaining optimal control forces by means of minimizing a criterion function in quadratic form. In computer simulation, even though the performance of vibration control was still worse than the result obtained by applying the optimal control theory, the usefulness of the present system was verified.

针对高层建筑在风或地震作用下产生的振动，研制了一种以直线电机为作动器，采用最优反馈理论进行数字控制的主动质量阻尼器。此外，还考虑了一种基于神经网络模型的替代控制方法。在该项目的第一年，采用振动台对三层钢框架建筑模型进行了动力试验，以研究最优控制主动质量阻尼器的性能。结果表明，该建筑模型的响应已充分减小到地震输入引起的非控制响应的一半左右。第二年，建立了主动质量阻尼器的解析模型，并结合建筑模型，研究了主动质量阻尼器在几种风和地震作用下的动力响应。得到了主动质量阻尼器的基本设计数据。因此，在32位个人计算机上建立了一个神经网络控制系统。该系统包括用于系统辨识的系统神经网络和通过最小化二次型准则函数获得最优控制力的控制神经网络。在计算机仿真中，尽管振动控制的性能仍不如应用最优控制理论得到的结果，但也验证了该系统的实用性。