基于融合智能算法斜拉桥振动控制Benchmark问题的混合控制策略研究

项目名称： 基于融合智能算法斜拉桥振动控制Benchmark问题的混合控制策略研究

项目编号： No.51308174

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 建筑科学

项目作者： 何敏

作者单位： 合肥工业大学

项目金额： 25万元

中文摘要： 以国际桥梁界地震激励下进行振动控制研究的斜拉桥Benchmark模型（Emerson memorial bridge）为研究对象，利用模糊神经网络模拟新型电磁驱动主动质量阻尼器（EMD）的力学特性，建立其力电关系的智能模型,为工程中的计算仿真以及实时在线控制实施提供有效保障；综合运用EMD系统及合成橡胶支座，形成主动控制+被动控制的混合控制策略；设计基于人工神经网络、模糊推理、遗传算法等智能算法的融合智能算法，选取目标控制函数，设计16项控制效果指标，使桥梁结构在每一时刻根据结构状态和所受外荷载情况进行最优控制，及时消减结构的动力响应，对比分析采用混合控制策略和单一控制策略的有效性；最后针对结构建模中由于刚度误差引起的控制系统鲁棒性问题,以某个或某几个Benchmark地震波输入为例，设计3种试验工况，刚度变异从-15%、0%到15% ，分别仿真结构动力响应，评价该振动控制系统的鲁棒性。

中文关键词： 结构振动控制；Benchmark斜拉桥模型；电磁驱动EMD阻尼器；智能算法；混合控制

英文摘要： Many control strategies and devices have been developed and investigated to protect structures against natural hazard such as earthquake.The control of very flexible and large structures such as cable-stayed bridges is a unique and challenging problem.Benchmark control problem for seismic response of cable-stayed brdige(Emerson memorial bridge) has been presented in the Second International Conference on Vibration Control. Researcher must define the devices, algorithms to be used in the proposed control strategy. This Benchmark model is used as the research object in the project.The aim of the study is to investigate the application of the hybrid control strategy and the hybrid intelligent control algorithm, in reducing the displacement of the deck as well as base shear and moments at the base of the towers. In the first part of the project, the mechanical properties of the new Electromagnetic drive active mass damper (EMD) is identified by the method of the fuzzy neural network, and the smart power-electric relation is established. A hybrid control strategy combining passive and active control systems is proposed for the benchmark bridge problem. In this hybrid control strategy, passive rubber bearings are used as passive control devices.The passive control strategy has a great role for the effectiveness of con

英文关键词： structural vibration control；Benchmark cable-stayed bridge；electromagnetic EMD damper；intelligent algorithm；hybrid control