电磁驱动主动质量阻尼器控制系统的智能模型
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摘要
利用模糊神经网络理论的非线性处理能力,以试验数据作为网络训练及验证数据,找出电磁驱动主动质量阻尼器控制系统在更为广泛的条件下其线圈输入电压、质量块相对运动速度和系统输出电磁力之间的关系,建立EMD系统的智能模型,仿真结果表明可以有效改善现有力电关系模型的计算效果。
An intelligent model of the electromagnet-drived active mass damper(EMD) system was proposed,taking advange of the good capability of fuzzy neural network(FNN) to process nonlinear problems.When the input voltage of EMD system goes beyond some limits of frequency or magnitude,a series of performance tests has verified that the experimental results can't agree well with the predications according to the conventional theoretical model of force-electricity relationship of EMD system.Considering the driving principles of EMD system,the active control force of the system is mainly relevant to the voltage of electromagnetic coil and the velocity of EMD equipment.So,a FNN was utilized to identify the relationship between voltage,velocity and active control force of EMD system in the paper.A group of test results was taken as the training data of the FNN to model the dynamic behavior of a bench scale EMD.Then,another group of test results was taken to check the effect of the proposed model.The simulation results indicate that the predications based on the proposed intelligent model of EMD system agree well with the experimental results under the generalized condition,and the intelligent model is of better performance than the current model of force-electricity relationship.
An intelligent model of the electromagnet-drived active mass damper(EMD) system was proposed,taking advange of the good capability of fuzzy neural network(FNN) to process nonlinear problems.When the input voltage of EMD system goes beyond some limits of frequency or magnitude,a series of performance tests has verified that the experimental results can't agree well with the predications according to the conventional theoretical model of force-electricity relationship of EMD system.Considering the driving principles of EMD system,the active control force of the system is mainly relevant to the voltage of electromagnetic coil and the velocity of EMD equipment.So,a FNN was utilized to identify the relationship between voltage,velocity and active control force of EMD system in the paper.A group of test results was taken as the training data of the FNN to model the dynamic behavior of a bench scale EMD.Then,another group of test results was taken to check the effect of the proposed model.The simulation results indicate that the predications based on the proposed intelligent model of EMD system agree well with the experimental results under the generalized condition,and the intelligent model is of better performance than the current model of force-electricity relationship.
引文
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[2]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.
[3]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.
[4]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.
[5]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.
[6]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.
[7]张春巍.结构振动的电磁驱动AMD控制系统及其相关理论与试验研究[D].哈尔滨:哈尔滨工业大学,2005.
[8]代泽兵.大跨度斜拉桥地震振动半主动控制应用研究[D].上海:上海交通大学,2003.
[9]胡玉玲,曹建国.基于模糊神经网络的动态非线性系统辨识研究[J].系统仿真学报,2007,19(3):560-562.
[10]吴晓莉,林哲辉.MATLAB辅助模糊系统设计[M].西安:西安电子科技大学出版社,2002.
[11]许东,吴铮.基于MATLAB 6.x的系统分析与设计—神经网络[M].西安:西安电子科技大学出版社,2002.
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