基于自适应逆控制的液压振动台功率谱复现
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摘要
为了改善液压振动台功率谱密度复现的精度和实时性,引入了自适应逆控制的系统辨识技术。在分析液压振动台功率谱密度均衡原理的基础上,推导时域自适应逆控制(Adaptive inverse control-AIC)和频域逆控制来实时获得振动系统的阻抗函数用以高精度实时修正控制谱密度。文中给出一种多处理器协同工作的硬件平台方案,将实时控制的任务进行分解;最后通过双端口RAM实现数据共享,从而实现功率谱密度的实时复现。仿真实验结果表明:频域自适应逆控制较时域自适应逆控制更利于改善功率谱密度复现的精度和实时性。
Adaptive inverse control( AIC) method was introduced to identify the impedance function of a hydraulic shaking table online,it was also beneficial to improve the accuracy and real-time processing of its power spectral density( PSD) replication. The AIC system identification technology in both time domain and frequency domain was deduced after the introduction of power spectral density equalization principle. The inverse computation to obtain the system impedance function often applied in traditional methods was not employed in this technology. The control power spectral density was modified using the results of the system impedance function estimated with the proposed technology more efficiently than with traditional methods. A hardware platform with multi-processor was introduced to accomplish the proposed algorithm.The different real time tasks were assigned to different processors. The dual port RAM was applied to fulfill the data sharing among the processors. The results of simulation showed that the proposed algorithm is efficient in PSD replication process of the shaking table. Meanwhile,the result of AIC in frequency domain is more desirable than that in time domain.
Adaptive inverse control( AIC) method was introduced to identify the impedance function of a hydraulic shaking table online,it was also beneficial to improve the accuracy and real-time processing of its power spectral density( PSD) replication. The AIC system identification technology in both time domain and frequency domain was deduced after the introduction of power spectral density equalization principle. The inverse computation to obtain the system impedance function often applied in traditional methods was not employed in this technology. The control power spectral density was modified using the results of the system impedance function estimated with the proposed technology more efficiently than with traditional methods. A hardware platform with multi-processor was introduced to accomplish the proposed algorithm.The different real time tasks were assigned to different processors. The dual port RAM was applied to fulfill the data sharing among the processors. The results of simulation showed that the proposed algorithm is efficient in PSD replication process of the shaking table. Meanwhile,the result of AIC in frequency domain is more desirable than that in time domain.
引文
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[10]Mansour D,Gray A H.Unconstrained frequency-domain adaptive filter[J].IEEE Trans.on ASSP,1982,30(5):726-734.
[11]刘小勇,杨清宇,施仁.基于X滤波最小均方算法的冲击振动自适应逆控制[J].西安交通大学学报,2004,38(2):144-148.Liu Xiao-yong,Yang Qing-yu,Shi Ren.Adaptive inverse control of shock vibration based on filter-X least mean square algorithm[J].Journal of Xi'an Jiaotong University,2004,38(2):144～148.
[12]Yang Z D,Huang Q T,Han J W,et al.Adaptive inverse control of random vibration based on the filtered-X LMS algorithm[J].Earthquake Engineering and Engineering Vibration,2010,9:141-146.
[13]Liu X Y,Luo Z L,Yi M Z.New frequency-domain method for shock vibration control[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2008,47(5):49-53.
[14]叶凌云.多轴向多激励随机振动高精度控制研究[D].杭州:浙江大学,2006.
[2]杨志东.液压振动台振动环境模拟的控制技术研究[D].哈尔滨:哈尔滨工业大学,2009.
[3]Smallwood D O,Paez T L.A frequency domain method for the generation of partially coherent normal stationary time domain signals[J].Shock and Vibration,1994,1(1):373-382.
[4]杨志东,关广丰,丛大成,等.基于Hv方法的三轴液压振动系统频响函数估计的研究[J].地震工程与工程振动,2007,27(3):83-87.YANG Zhi-dong,GUAN Guang-feng,CONG Da-cheng,et al.Frequency response function estimation for three axes hydraulic shaking system by using Hv algorithm[J].Journal of Earthquake Engineering and Engineering Vibration,2007,27(3):83-87.
[5]Stroud R C,Hamma G A.Multiexciter and multiaxis vibration exciter control systems[J].Sound and Vibration,1988,22(4):18-28.
[6]威德罗B,瓦莱斯E.自适应逆控制[M].刘树棠,韩崇昭,译.西安:西安交通大学出版社,2000:133-173.
[7]威德罗B,斯特恩斯S D.自适应信号处理(英文版)[M].北京:机械工业出版社,2008:99-103.
[8]何振亚.自适应信号处理[M].北京:科学出版社,2003:21-62.
[9]Chen Wei-dong,Gu Zhong-quan.Frequency domain implementation of filtered-x algorithm with on line system identification for vibration control[J].Transaction of Nanjing University of Aeronautics&Astronautics,1995,12(1):100-103.
[10]Mansour D,Gray A H.Unconstrained frequency-domain adaptive filter[J].IEEE Trans.on ASSP,1982,30(5):726-734.
[11]刘小勇,杨清宇,施仁.基于X滤波最小均方算法的冲击振动自适应逆控制[J].西安交通大学学报,2004,38(2):144-148.Liu Xiao-yong,Yang Qing-yu,Shi Ren.Adaptive inverse control of shock vibration based on filter-X least mean square algorithm[J].Journal of Xi'an Jiaotong University,2004,38(2):144～148.
[12]Yang Z D,Huang Q T,Han J W,et al.Adaptive inverse control of random vibration based on the filtered-X LMS algorithm[J].Earthquake Engineering and Engineering Vibration,2010,9:141-146.
[13]Liu X Y,Luo Z L,Yi M Z.New frequency-domain method for shock vibration control[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2008,47(5):49-53.
[14]叶凌云.多轴向多激励随机振动高精度控制研究[D].杭州:浙江大学,2006.
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