桥梁结构模糊神经控制的优化方案  

Optimization scheme of fuzzy neural control for bridge structure

作　　者：郑宗平[1] 何敏[1] 

机构地区：[1]合肥工业大学土木与水利工程学院,安徽合肥230009

出　　处：《南昌大学学报（工科版）》2017年第4期361-365,共5页Journal of Nanchang University(Engineering & Technology)

基　　金：国家自然科学基金资助项目(51308174)

摘　　要：为了进一步提高神经模糊控制器对地震激励下桥梁结构振动控制的稳定性,在传统控制的基础上,提出了分块控制的优化方案,并通过在桥梁Benchmark模型上的应用验证其控制效果。数值分析的结果表明:优化方案的峰值响应控制效果与样本主动控制近似,控制稳定性效果明显提升,由优化前未控状态的22%~29%提升到28%~31%,其中,跨中位移稳定性比优化前提升了9%,支座变形控制稳定性提升了7%。该方案还具有所需结构反馈信息少、构造简单、经济性好等优势。To further improve the stability of neural fuzzy controller for vibration control of bridge structures under seismic excitation,an optimal scheme of partitioning control was put forward on the basis of traditional fuzzy control.Meanwhile,the control effect was verified by the numerical analysis of bridge Benchmark model.The results of numerical analysis showed that the optimal scheme could realize the peak response control effect of approximate sample active control and control stability effect was improved obviously.The 22%-29% of the uncontrolled state increased to 28%-31%,and the stability of the midspan displacement increased by 9%.And then,the stability of bearing deformation improved by 7% according to the old scheme.The scheme also has the advantages of less structural feedback information,simple structure and better economic efficiency.

关 键 词：模糊控制 神经网络控制 BENCHMARK模型 结构控制 稳定性 

分 类 号：U441.3[建筑科学—桥梁与隧道工程] TU312[交通运输工程—道路与铁道工程]