高层建筑横风向反应的模糊神经网络控制
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摘要
介绍了第3代结构风振控制基准问题的定义。通过观测部分楼层加速度和控制力输出,建立了模糊神经网络控制器,解决了传统控制中有限的传感器数目对系统振动状态估计的困难;利用模糊神经网络预测结构的控制行为,消除了闭环控制系统中存在的时滞;通过模糊神经网络控制器的学习功能,解决了土木工程复杂结构模糊控制中难以依据专家的主观经验来确定模糊控制规则和语言变量隶属函数等困难。以风振控制的基准问题为研究对象,编制了程序对受控系统进行数值仿真分析。分析表明,模糊神经网络控制策略能有效地抑制高层建筑的风振反应。
The definition of a benchmark control problem for wind-induced tall buildings was presented.A fuzzy neural network controller,in which few sensors and no observer were needed,was designed on the basis of the measurement of floor accelerations and control forces.The fuzzy neural network controller to predict control action eliminated the effects of time delay in the control loop.With a fuzzy logic control strategy,it's difficult to obtain an appropriate set of rules and membership functions.But it's easy to solve these problems utilizing the ability of adaptive learning of the fuzzy neural network controller.Numerical simulation was carried out for analyzing the wind-induced responses of the benchmark building.The analysis results show that the control strategy using fuzzy neural network has good performance in reducing across wind response of the benchmark building.
The definition of a benchmark control problem for wind-induced tall buildings was presented.A fuzzy neural network controller,in which few sensors and no observer were needed,was designed on the basis of the measurement of floor accelerations and control forces.The fuzzy neural network controller to predict control action eliminated the effects of time delay in the control loop.With a fuzzy logic control strategy,it's difficult to obtain an appropriate set of rules and membership functions.But it's easy to solve these problems utilizing the ability of adaptive learning of the fuzzy neural network controller.Numerical simulation was carried out for analyzing the wind-induced responses of the benchmark building.The analysis results show that the control strategy using fuzzy neural network has good performance in reducing across wind response of the benchmark building.
引文
[1]阎石,林皋,李宏男.相邻建筑结构的模糊振动控制[J].地震工程与工程振动,2000,20(2):39-43.
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[2]陈勇,孙炳楠,楼文娟,等.基于降阶模型的斜拉索振动的半主动神经网络控制[J].控制理论与应用,2004,21(2):211-216.
[3]Aldawod M,Samali B,Naghdy F.Active control of along wind response of all building using a fuzzy controller[J].Engineering Structures,2001,23:1512-1522.
[4]王德山,陈水生,卢其发.工程结构地震响应模糊半主动控制[J].地震工程与工程振动,2005,25(4):149-154.
[5]Yang J N,Agrawak AK,Samali B.Benchmark problem for response control of wind-excited tall buildings[J].Journal of Engineering Mechan-ics,2004,130(4):437-446.
[6]Yang J N,Agrawak AK,Samali B.Abenchmark problemfor response control of wind-excited tall Buildings[R/OL].1999,World Wide Web-site http://www.eng.uci.edu/~jnyang/bench-mark.html.
[7]Samali B,Kwok K G,Yang J N.Wind tunnel tests for wind-excited benchmark problem[R].Technical Note,1999.
[8]张智星,孙春在,(日)水谷英二,等.神经.模糊和软计算[M].西安:西安交通大学出版社,2000.
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