压电智能结构振动系统未知扰动估计  

Unknown disturbance estimation for a vibration system of piezoelectric smart structures

作　　者：伍彬艺[1] 秦现生[1] 张顺琦[2] 王战玺[1] 白晶[1] 李靖[1] WU Binyi;QIN Xiansheng;ZHANG Shunqi;WANG Zhanxi;BAI Jing;LI Jing(School of Mechanical Engineering,Northwestern Polytechnical University,Xi’an 710072,China;School of Mechatronic Engineering and Automation,Shanghai University,Shanghai 200444,China)

机构地区：[1]西北工业大学机电学院,西安710072 [2]上海大学机电工程与自动化学院,上海200444

出　　处：《振动与冲击》2019年第16期37-41,共5页Journal of Vibration and Shock

基　　金：国家自然科学基金(11602193;51505380);陕西省重点研发计划科技攻关项目(2016KTZDGY4-03);南京航空航天大学机械结构力学及控制国家重点实验室开放课题(MCMS-0517G01);大连理工大学工业装备结构分析国家重点实验室开放基金(GZ15212)

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,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,该研究的扰动估计方法对于外部未知扰动具有更好的估计效果。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.

关 键 词：扰动估计 卡尔曼滤波 比例-积分观测器 压电传感器 

分 类 号：O327[理学—一般力学与力学基础] TB123[理学—力学]