压电智能结构振动系统未知扰动估计

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摘要外部扰动极易导致结构振动，从而引起结构的疲劳损伤乃至破坏,降低了使用寿命。然而在很多实际的工程应用中,扰动是未知的且很难测量。为此，本文提出一种基于卡尔曼滤波器的智能结构比例积分扰动观测器。该观测器使用分布式压电传感器对外部的未知扰动进行估计,并通过仿真获得了不同测量位置的扰动估计数据。仿真结果表明,在考虑测量噪声的情况下,与传统的比例积分扰动观测器相比,本文的扰动估计方法对于外部未知扰动具有更好的估计效果。

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	伍彬艺1
	秦现生1
	张顺琦2
	王战玺1
	白晶1
	李靖1

关键词 ：扰动估计, 卡尔曼滤波, 比例-积分观测器, 压电传感器

Abstract：Vibration is easily caused by external disturbances, which may lead to fatigue damage and reduce the service life.However, in many practical engineering applications, disturbances are unknown or difficult to be measured directly.In this paper, a proportional-integral (PI) observer based on the Kalman filter was developed for smart structures using multiple distributed piezoelectric sensors, and the data of estimated disturbance with different positions were obtained through simulation test.The simulation results show that the proposed method has better dynamic performance for the external unknown disturbances with measurement noises compared to traditional proportional-integral observers.

Key words： disturbance estimation Kalman filter proportional integral observer piezoelectric sensors

收稿日期: 2017-11-28 出版日期: 2019-08-15

引用本文:

伍彬艺1，秦现生1，张顺琦2,王战玺1, 白晶1, 李靖1. 压电智能结构振动系统未知扰动估计[J]. 振动与冲击, 2019, 38(16): 37-41.
WU Binyi1,QIN Xiansheng1,ZHANG Shunqi2,WANG Zhanxi1,BAI Jing1,LI Jing1. Unknown disturbance estimation for a vibration system of piezoelectric smart structures. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(16): 37-41.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2019/V38/I16/37

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