斜拉桥-EMD系统智能模型及控制仿真研究
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摘要
基于智能算法建立斜拉桥-EMD控制系统的智能模型,并对其进行了智能主动控制的数值仿真。首先利用遗传算法优化BP神经网络的权值和阈值,由仿真数据建立斜拉桥-EMD控制系统的智能模型,代替传统的有限元模型对桥梁结构进行动力分析;然后综合模糊逻辑推理和神经网络理论设计智能主动控制策略,对智能模型进行智能主动控制,数值仿真结果表明:此方法振动控制效果良好,可以有效抑制桥梁结构地震波激励下的结构动力反应。
Intelligent model of a cable-stayed bridge with electromagnet-drived AMD control systems was proposed based on the intelligent algorithm,and the numerical simulation applying intelligent active control strategy was proposed.Firstly,the weights and the threshold values of the BP neural network were optimized using the genetic algorithm,and intelligent model of a cable-stayed bridge with EMD control systems was established by the simulated results extracted from the benchmark control problem of the Emerson Memorial Bridge.The innovation of the new intelligent model was to analyze the dynamic response of the bridge structure under seismic excitation,and to be substituted for conventional finite element model.Ultimately,the intelligent active control strategy was proposed adopting the fuzzy logic and the neural network.The control performance of the proposed methodology was evaluated for the Emerson Memorial Bridge.The simulated results show that the proposed intelligent active control technique can effectively mitigate the seismic response of cable-stayed bridges.
Intelligent model of a cable-stayed bridge with electromagnet-drived AMD control systems was proposed based on the intelligent algorithm,and the numerical simulation applying intelligent active control strategy was proposed.Firstly,the weights and the threshold values of the BP neural network were optimized using the genetic algorithm,and intelligent model of a cable-stayed bridge with EMD control systems was established by the simulated results extracted from the benchmark control problem of the Emerson Memorial Bridge.The innovation of the new intelligent model was to analyze the dynamic response of the bridge structure under seismic excitation,and to be substituted for conventional finite element model.Ultimately,the intelligent active control strategy was proposed adopting the fuzzy logic and the neural network.The control performance of the proposed methodology was evaluated for the Emerson Memorial Bridge.The simulated results show that the proposed intelligent active control technique can effectively mitigate the seismic response of cable-stayed bridges.
引文
[1]张春巍,欧进萍.电磁驱动AMD系统控制结构地震响应的振动台试验[J].地震工程与工程振动,2006,26(2):104-110.
[2]张春巍,欧进萍.电磁驱动惯性型作动器与结构耦合系统建模与试验研究[J].振动工程学报,2006,19(3):289-295.
[3]张春巍,欧进萍.电磁式惯性型作动器的闭环控制策略与性能试验[J].振动工程学报,2007,20(3):213-218.
[4]何敏,王建国.地震激励下斜拉桥电磁驱动AMD主动控制系统的系统参数优化[J].振动与冲击,2008,27(6):118-122.
[5]何敏,王建国.大跨桥梁结构电磁驱动AMD系统输入电压的在线控制研究[J].振动与冲击,2008,27(9):135-138.
[6]Dai Ze-bing,Huang Jin-zhi,Wang Hong-xia.Semi-active control of a cable-stayed bridge under multiple-support excitations[J].Journal of Zhejiang University,2004,5(3):317-325.
[7]代泽兵,黄金枝,王红霞.基于智能阻尼器的大跨度斜拉桥多支承激励地震振动控制[J].振动与冲击,2005,24(2):66-70.
[8]Gursoy Turan.Active control of a cable-stayed bridge against earthquake excitations[D].USA:University of Illinois,2001.
[9]曹承志,董梅,李敏,等.遗传BP神经网络转速辨识器的设计及在DTC中的应用[J].系统仿真学报,2007,19(4):925-927.(CAO Cheng-zhi,DONG Mei,LI Min.Design of Genetic BP Network Speed Identifier and Application in Direct Torque Control System[J].Journal of System Simulation(S1004-731X),2007,19(4):925-927.)
[10]王健,王昆,陈全世.风力发电和飞轮储能联合系统的模糊神经网络控制策略[J].系统仿真学报,2007,19(17):4017-40.(WANG Jian,WANG Kun,CHEN Quan-shi.Fuzzy Neural Network Control Strategy of Wind Generation and Flywheel Energy Storage Combined System[J].Journal of System Simulation(S1004-731X),2007,19(17):4017-40.)
[2]张春巍,欧进萍.电磁驱动惯性型作动器与结构耦合系统建模与试验研究[J].振动工程学报,2006,19(3):289-295.
[3]张春巍,欧进萍.电磁式惯性型作动器的闭环控制策略与性能试验[J].振动工程学报,2007,20(3):213-218.
[4]何敏,王建国.地震激励下斜拉桥电磁驱动AMD主动控制系统的系统参数优化[J].振动与冲击,2008,27(6):118-122.
[5]何敏,王建国.大跨桥梁结构电磁驱动AMD系统输入电压的在线控制研究[J].振动与冲击,2008,27(9):135-138.
[6]Dai Ze-bing,Huang Jin-zhi,Wang Hong-xia.Semi-active control of a cable-stayed bridge under multiple-support excitations[J].Journal of Zhejiang University,2004,5(3):317-325.
[7]代泽兵,黄金枝,王红霞.基于智能阻尼器的大跨度斜拉桥多支承激励地震振动控制[J].振动与冲击,2005,24(2):66-70.
[8]Gursoy Turan.Active control of a cable-stayed bridge against earthquake excitations[D].USA:University of Illinois,2001.
[9]曹承志,董梅,李敏,等.遗传BP神经网络转速辨识器的设计及在DTC中的应用[J].系统仿真学报,2007,19(4):925-927.(CAO Cheng-zhi,DONG Mei,LI Min.Design of Genetic BP Network Speed Identifier and Application in Direct Torque Control System[J].Journal of System Simulation(S1004-731X),2007,19(4):925-927.)
[10]王健,王昆,陈全世.风力发电和飞轮储能联合系统的模糊神经网络控制策略[J].系统仿真学报,2007,19(17):4017-40.(WANG Jian,WANG Kun,CHEN Quan-shi.Fuzzy Neural Network Control Strategy of Wind Generation and Flywheel Energy Storage Combined System[J].Journal of System Simulation(S1004-731X),2007,19(17):4017-40.)
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