ICA Based Vibration Detection of Unknown Systems and Its Active Suppression via Online Learning

基于ICA的未知系统振动检测及其在线学习主动抑制

• 批准号: 15560379
• 负责人: SUGIMOTO Kenji
• 金额: $ 2.37万
• 依托单位: Nara Institute of Science and Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2003
• 资助国家: 日本
• 起止时间: 2003 至 2004
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-15560379/
• 关键词: Independent Component Analysis; System Identification; Vibration Detection; Unknown Input; Mechanical Vibration

The objective of this research lies in introducing Independent Component Analysis(ICA), a new framework of methods for multivariable analysis, to identification or design of control systems. At this moment, frequency domain approaches are mainly adopted in ICA for dynamical systems. In control systems, however, it is more desirable if we can process in time domain. In view of this, the basic idea of this research is 1)to confine ourselves to the vector AR model, 2)expand the discrete-time signal to time series, 3)express the input-output relations in terms of algebraic equation with fixed elements (which is extended state space representation), and then 4)apply ICA in a transparent way.We first completed this basic idea as an algorithm and proposed it as a blind system identification technique. Then we verified the effectiveness of the proposed method by means of both theoretical analysis and numerical simulation. The result was presented in domestic and international conferences, and then in a journal paper.We further apply this method to two practical issues, namely detection of structure change and rejection of unknown disturbance. Concerning detection of change, we fabricated an experimental system with flexible structure and performed detection of a change due to a virtual fault. The result was successful and we presented it in domestic and international conferences. We have also submitted a paper to a journal.Concerning disturbance rejection, we verified the effectiveness by means of simulation and the result was presented in domestic and international conferences. Now we are preparing a paper for a journal. However, we have not yes succeeded in on-line suppression of vibration, which was mentioned in our original research plan. This is due to lack of a real-time performance in our method. It is our current research theme to overcome this difficulty.

本研究的目的在于将独立分量分析（ICA）这一多变量分析方法的新框架引入控制系统的识别或设计中。目前，动力系统ICA主要采用频域方法。然而，在控制系统中，如果我们能够在时域中进行处理，那就更理想了。鉴于此，本研究的基本思想是：1）将我们局限于向量AR模型，2）将离散时间信号扩展到时间序列，3）用固定的代数方程表达输入输出关系元素（扩展的状态空间表示），然后4）以透明的方式应用ICA。我们首先将这一基本思想作为算法完成，并将其提出作为盲系统识别技术。然后通过理论分析和数值模拟验证了所提方法的有效性。该结果在国内和国际会议上发表，然后发表在期刊论文中。我们进一步将该方法应用于两个实际问题，即结构变化的检测和未知扰动的拒绝。关于变化检测，我们制作了一个结构灵活的实验系统，并进行了虚拟故障引起的变化检测。结果是成功的，我们在国内和国际会议上展示了它。我们也向期刊投了一篇论文。关于抗扰性，我们通过仿真的方式验证了有效性，结果在国内和国际会议上进行了展示。现在我们正在为期刊准备一篇论文。然而，我们原来的研究计划中提到的在线抑制振动并没有成功。这是由于我们的方法缺乏实时性能。克服这一困难是我们当前的研究主题。

项目成果

A.Satoh, K.Sugimoto: "Partial Eigenstructure Assignment Approach for Robust Flight Control"AIAA Journal of Guidance, Control and Dynamics. 27・1. 145-150 (2004)

A.Satoh、K.Sugimoto：“鲁棒飞行控制的部分特征结构分配方法”AIAA 制导、控制和动力学杂志 27・1（2004 年）。

独立成分分析による機械システムの異状検出

使用独立组件分析检测机械系统异常

• 发表时间: 2004
• 期刊: 第48回システム制御情報学会研究発表講演会
• 作者: 鈴木 新;新田 益大;杉本 謙二
• 通讯作者: 杉本 謙二

K.Sugimoto, Y.Kikkawa: "Control Systems Analysis via Blind Source Deconvolution"4-th and International Symposium on Independent Component Analysis and Blind Signal Separation. (CD-ROM). (2003)

K.Sugimoto、Y.Kikkawa：“通过盲源反卷积进行控制系统分析”第四届独立分量分析和盲信号分离国际研讨会。

独立成分分析を用いた自己回帰モデルの未知入力同定法

基于独立成分分析的自回归模型未知输入识别方法

• 发表时间: 2005
• 期刊: 計測自動制御学会論文集 41
• 作者: 新田益大;杉本謙二;佐藤淳
• 通讯作者: 佐藤淳

H infinity Design with Loose Eigenstructure Assignment--A rank-one LMI Approach

松散特征结构分配的H无穷设计--一种一级LMI方法

• 发表时间: 2005
• 期刊: Transactions of the Society of Instrument and Control Engineers Vol.41
• 作者: A.Satoh;K.Sugimoto;M.Sebek
• 通讯作者: M.Sebek