航空学报 > 2020, Vol. 41 Issue (2): 223000-223000   doi: 10.7527/S1000-6893.2019.23000

MIMO随机振动试验控制的逆多步预测模型法

郑威, 陈怀海   

  1. 南京航空航天大学 机械结构力学及控制国家重点实验室, 南京 210016
  • 收稿日期:2019-03-14 修回日期:2019-09-17 出版日期:2020-02-15 发布日期:2019-10-24
  • 通讯作者: 陈怀海 E-mail:chhnuaa@nuaa.edu.cn
  • 基金资助:
    江苏高校优势学科建设工程资助项目

Inverse multi-step prediction model method for MIMO random vibration test control

ZHENG Wei, CHEN Huaihai   

  1. State Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2019-03-14 Revised:2019-09-17 Online:2020-02-15 Published:2019-10-24
  • Supported by:
    The Priority Academic Program Development of Jiangsu Higher Education Institutions

摘要: 多输入多输出(MIMO)随机振动试验在产品可靠性验证中扮演重要角色。逆系统方法作为一种时域方法,直接由参考信号(即期望得到的响应信号)生成驱动信号,但容易产生不稳定的结果。本文以系统的有限差分模型为基础,推导了逆多步预测模型,并建立了该逆模型与矩阵幂次算法结合的MIMO随机振动试验方法。通过悬臂梁模型进行双输入双输出仿真试验,验证了逆多步预测模型进行MIMO随机振动试验驱动生成的可行性。在三轴振动台上进一步验证该方法进行MIMO随机振动试验控制的能力。

关键词: 逆系统, 多步预测模型, MIMO, 随机振动, 环境试验

Abstract: Multi Input Multi Output (MIMO) random vibration test is of utter importance in product validation. As a type of time domain method, inverse system methods are capable of generating drive signals directly from reference ones (i.e., the desired response signals). However, in practice, these methods are prone to produce unstable results. To address this issue, an inverse multi-step prediction model is induced from the finite difference model of the system, and a MIMO random vibration test control scheme utilizing both the inverse multi-step prediction model and matrix power algorithm are proposed. First, a simulation of double-input-double-output-random-vibration test on a cantilever beam is conducted to show that the inverse multi-step prediction model can generate drive signals needed to satisfy the control requirement. After that, the capability of the proposed MIMO random vibration test control scheme is further validated in a test performed on a three-axis shaker.

Key words: inverse system, multi-step prediction model, MIMO, random vibration, environmental test

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