System Identification of practical plants for control and diagnosis

用于控制和诊断的实际设备的系统识别

基本信息

  • 批准号:
    08650517
  • 负责人:
  • 金额:
    $ 0.7万
  • 依托单位:
  • 依托单位国家:
    日本
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
  • 财政年份:
    1996
  • 资助国家:
    日本
  • 起止时间:
    1996 至 1997
  • 项目状态:
    已结题

项目摘要

This project treated several types of system identification from the point of their practical applications. To estimate available model to its purpose, which may be control, prediction or diagnosis, one should select its model structure appropriately. We mainly considered system identification in the case when the plant was controlled by feedback loop, or the plant was nonlinear system. We used linear time series model, neuro model and fuzzy model as identification models, and investigated the method to make appropriate models from the data. Some procedures for estimating orders and delay-time were proposed by using input and output data. Research results are summarized as follows :1.We proposed a system identification procedure useful for practical data observed by closed-loop experiments. It includes several steps, aiming for model selection and order estimation. Simulation experiment showed usefulness of the procedure.2.We applied 4SID (Subspace based State-Space System IDentification) method to order estimation, and showed usefulness of the method even if the plant is noisy, by using comparatively long data.3.We used recurrent neural network for system identification and proposed a line to construct an appropriate neuro model for the data.4.We proposed a procedure to construct a fuzzy control system, typically on the selection of model structures by considering the influence of noisy data.
本课题从实际应用的角度出发,对几种类型的系统辨识进行了研究。为了评估可用的模型以达到控制、预测或诊断的目的,应该适当地选择模型结构。主要考虑了被控对象为反馈控制或非线性系统时的系统辨识问题。采用线性时间序列模型、神经网络模型和模糊模型作为辨识模型,研究了从数据中建立合适模型的方法。提出了利用输入输出数据估计阶数和延迟时间的方法。主要研究成果如下:1.提出了一种适用于实际闭环实验数据的系统辨识方法。它包括几个步骤,针对模型选择和阶估计。仿真实验表明了该方法的有效性(基于子空间的状态空间系统辨识)方法来进行阶次估计,并且即使在被控对象有噪声的情况下也显示出该方法的有用性,3.利用递归神经网络进行系统辨识,并提出了一种构造神经网络模型的方法; 4.提出了构造模糊控制器的方法系统,通常通过考虑噪声数据的影响来选择模型结构。

项目成果

期刊论文数量(20)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
K.Oura, K.Akizuki, I.Hanazaki: "A Study on Selecting Model Structures in Identification of Closed-Loop System" Proceedings of the 4th ICARCV. 2365-2369 (1996)
K.Oura、K.Akizuki、I.Hanazaki:“闭环系统辨识中模型结构选择的研究”第四届 ICARCV 会议论文集。
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
  • 通讯作者:
K.Oura, K.Akizuki I.Hanazaki, M.Miyazaki: "A Study on System Identification Procedure for the Data Set Observed by Closed-Loop Experiments" Proceedings of MIC'98. (in Press). (1998)
K.Oura、K.Akizuki I.Hanazaki、M.Miyazaki:“闭环实验观察到的数据集的系统识别程序的研究”MIC98 论文集。
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
  • 通讯作者:
S.G.Lee, K.Akizuki: "Automatic Tuning of Fuzzy Controller for Unknown Systems" Journal of Fuzzy Logic and Intelligent Systems(Korea). Vol.4 No.4. 11-18 (1997)
S.G.Lee、K.Akizuki:“未知系统模糊控制器的自动调整”模糊逻辑与智能系统杂志(韩国)。
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
  • 通讯作者:
秋月影雄ほか: "逆問題としてとらえた産業プロセス異常予測" 電気学会, 70 (1997)
Kageo Akizuki 等人:“将工业过程异常预测为反问题”,日本电气工程师学会,70 (1997)
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
  • 通讯作者:
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

AKIZUKI Kageo其他文献

AKIZUKI Kageo的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('AKIZUKI Kageo', 18)}}的其他基金

Establishment of Total Information System for Management of Factory
工厂管理全面信息系统的建立
  • 批准号:
    05650372
  • 财政年份:
    1993
  • 资助金额:
    $ 0.7万
  • 项目类别:
    Grant-in-Aid for General Scientific Research (C)
Development of Control System Design Supporting System Including Knowledge Based Treatment.
控制系统设计支持系统的开发,包括基于知识的处理。
  • 批准号:
    63550320
  • 财政年份:
    1988
  • 资助金额:
    $ 0.7万
  • 项目类别:
    Grant-in-Aid for General Scientific Research (C)

相似海外基金

Development of closed-loop identification algorithms and system identification based on statistical methods
基于统计方法的闭环辨识算法和系统辨识的开发
  • 批准号:
    20K04535
  • 财政年份:
    2020
  • 资助金额:
    $ 0.7万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
On estimating a ship maneuverability based on closed-loop identification approach
基于闭环辨识方法的船舶操纵性估计
  • 批准号:
    21656226
  • 财政年份:
    2009
  • 资助金额:
    $ 0.7万
  • 项目类别:
    Grant-in-Aid for Challenging Exploratory Research
Continuous-time closed-loop identification based on the iterative learning control
基于迭代学习控制的连续时间闭环辨识
  • 批准号:
    19760295
  • 财政年份:
    2007
  • 资助金额:
    $ 0.7万
  • 项目类别:
    Grant-in-Aid for Young Scientists (B)
DDDAS-SMRP: Development of a closed-loop identification machine for bionetworks (CLIMB) and its application to nucleotide metabolism
DDDAS-SMRP:生物网络闭环识别机(CLIMB)的开发及其在核苷酸代谢中的应用
  • 批准号:
    0540181
  • 财政年份:
    2005
  • 资助金额:
    $ 0.7万
  • 项目类别:
    Continuing Grant
Stochastic Subspace Identification Method and its Applications to Closed-Loop Identification
随机子空间辨识方法及其在闭环辨识中的应用
  • 批准号:
    15560376
  • 财政年份:
    2003
  • 资助金额:
    $ 0.7万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Joint Design Method of Closed-loop Identification for System with Time Delay
时滞系统闭环辨识联合设计方法
  • 批准号:
    14550454
  • 财政年份:
    2002
  • 资助金额:
    $ 0.7万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了