logo
言語
ブックマーク
ログアウト

ジャーナル

論文検索サイト

アカウント

© 2022 Steel Science Portal

ヘルプ

詳細検索

論文検索サイト

site
site
site
site

システム/制御/情報 Vol. 10 (1997), No. 6

ISIJ International
belloff
オンライン版ISSN: 2185-811X
冊子版ISSN: 1342-5668
発行機関: THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)

Backnumber

  1. Vol. 37 (2024)

    1. No.8
    2. No.7
    3. No.6
    4. No.5
    5. No.4
    6. No.3
    7. No.2
    8. No.1

  2. Vol. 36 (2023)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  3. Vol. 35 (2022)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  4. Vol. 34 (2021)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  5. Vol. 33 (2020)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  6. Vol. 32 (2019)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  7. Vol. 31 (2018)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  8. Vol. 30 (2017)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  9. Vol. 29 (2016)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  10. Vol. 28 (2015)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  11. Vol. 27 (2014)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  12. Vol. 26 (2013)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  13. Vol. 25 (2012)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  14. Vol. 24 (2011)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  15. Vol. 23 (2010)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  16. Vol. 22 (2009)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  17. Vol. 21 (2008)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  18. Vol. 20 (2007)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  19. Vol. 19 (2006)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  20. Vol. 18 (2005)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  21. Vol. 17 (2004)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  22. Vol. 16 (2003)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  23. Vol. 15 (2002)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  24. Vol. 14 (2001)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  25. Vol. 13 (2000)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  26. Vol. 12 (1999)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  27. Vol. 11 (1998)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  28. Vol. 10 (1997)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  29. Vol. 9 (1996)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  30. Vol. 8 (1995)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  31. Vol. 7 (1994)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  32. Vol. 6 (1993)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  33. Vol. 5 (1992)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  34. Vol. 4 (1991)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  35. Vol. 3 (1990)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  36. Vol. 2 (1989)

    1. No.12
    2. No.11
    3. No.10
    4. No.9
    5. No.8
    6. No.7
    7. No.6
    8. No.5
    9. No.4
    10. No.3
    11. No.2
    12. No.1

  37. Vol. 1 (1988)

    1. No.7
    2. No.6
    3. No.5
    4. No.4
    5. No.3
    6. No.2
    7. No.1

キーワードランキング

23 Nov. (Last 30 Days)

システム/制御/情報 Vol. 10 (1997), No. 6

ネットワーク構造の自己選択能力を備えたニューラルネットワークによる河川水質の非線形定常モデルの同定

近藤 正

pp. 277-286

DOI:

10.5687/iscie.10.277

抄録

This paper deals with a nonlinear steady state modeling of river quality by a neural network which has a self-selection ability of network structure. This neural network algorithm is a revised one of the neural network which can identify a nonlinear system whose structure is very large and complex. By using measured data of river quality such as BOD and DO concentrations, a nonlinear steady state model of river quality is identified by the neural network and the results are compared with the results which are obtained by a physical model and a GMDH model. And it is shown that the neural network in this paper gives better prediction results as compared with a physical model and a GMDH model.

mendeley

ブックマーク

詳細

PDFダウンロード

SNSによる共有

論文タイトル

ネットワーク構造の自己選択能力を備えたニューラルネットワークによる河川水質の非線形定常モデルの同定

twitter
facebook
mendeley

Bibtex

Ris

網膜と皮質間の写像関係に基づく両眼追跡

大城 尚紀, 丸 典明, 西川 敦, 宮崎 文夫

pp. 287-296

DOI:

10.5687/iscie.10.287

抄録

This paper describes a new binocular tracking method using Log Polar Mapping (LPM) which approximately represents the mapping of the retina into the visual cortex in primate vision : Using LPM makes it possible not only to obtain both a high central resolution and a wide field of view, but also to significantly reduce processing image data. In this paper, LPM is performed in software by lookup table method. Our tracking method utilizes zero disparity filter (ZDF) for extracting the target object and virtual horopter method for estimating binocular disparities, respectively. The performance of both target extraction and disparity estimation is improved in comparison with the conventional methods, by using LPM. Some experimental results are also shown to demonstrate the effectiveness of the proposed method.

mendeley

ブックマーク

詳細

PDFダウンロード

SNSによる共有

論文タイトル

網膜と皮質間の写像関係に基づく両眼追跡

twitter
facebook
mendeley

Bibtex

Ris

むだ時間システムの外乱抑制と目標値追従性を改善する一般化予測制御の構成方法

中本 政志, 小久保 隆, 清水 佳子, 舟城 純子

pp. 297-303

DOI:

10.5687/iscie.10.297

抄録

This paper presents a two-degree freedom configuration of Generalized Predictive Control in order to increase the ability of the disturbance rejection and the setpoint tracking for a dead time system. The controller which is designed with the plant model including the feedforward control can prevent the undesirable action which is caused by the feedforward control. Numerical and experimental results demonstrate the effectiveness and the practicableness.

他の人はこちらも検索

mendeley

ブックマーク

詳細

PDFダウンロード

SNSによる共有

論文タイトル

むだ時間システムの外乱抑制と目標値追従性を改善する一般化予測制御の構成方法

twitter
facebook
mendeley

Bibtex

Ris

遺伝アルゴリズムによるリカレントニューラルネットを用いた時系列信号のパターン認識

金城 寛, 中園 邦彦, 山本 哲彦

pp. 304-314

DOI:

10.5687/iscie.10.304

抄録

This paper presents a method of time series pattern recognition using recurrent neural networks (RNN) based on the genetic algorithms (GAs). The RNN could have dynamical characteristics because the RNN has feedback connections with time delay. The connection weights of the RNN transform into the gene which described by 16 bits binary code. In order to acquire the dynamics of the time series patterns, GAs operators which are a selection, a crossover and a mutation are applied to the gene of the RNN. In the numerical simulations, the training convergence of the RNN for some time series patterns are investigated. The simulation results show that the RNN evolved by the GAs has good performances of the training for time series patterns which generated from sine functions and for some pulse patterns. Finally, it is shown that the new method could determine some suitable network structures for time series training.

mendeley

ブックマーク

詳細

PDFダウンロード

SNSによる共有

論文タイトル

遺伝アルゴリズムによるリカレントニューラルネットを用いた時系列信号のパターン認識

twitter
facebook
mendeley

Bibtex

Ris

厳密な線形化の自由度を用いたマニピュレータの障害物回避制御

藤本 健治, 木村 健二, 杉江 俊治

pp. 315-320

DOI:

10.5687/iscie.10.315

抄録

This paper is concerned with an application of the use of freedom in the coordinates transformation for exact linearizaion. We apply this technique to obstacle avoidance of a manipulator in the master-slave control. We show how to use the freedom for such an object and give the way to construct the linearizing coordinates transformation and feedback. And we evaluate the effectiveness of our technique by experiments.

mendeley

ブックマーク

詳細

PDFダウンロード

SNSによる共有

論文タイトル

厳密な線形化の自由度を用いたマニピュレータの障害物回避制御

twitter
facebook
mendeley

Bibtex

Ris

ロボット制御則の並列化問題に対する遺伝アルゴリズムの適用

田川 聖治, 福居 毅至, 羽根田 博正

pp. 321-330

DOI:

10.5687/iscie.10.321

抄録

This paper presents a genetic algorithm (GA) for scheduling problem of a robot control computation. That is very difficult problem which belongs to the class of NP-hard problems. The authors have already proposed several algorithms, which are based on heuristic and branch-and-bound approaches, for the scheduling problem. The conventional algorithms, however, have the limits of their ability in quality of solutions and computational time. The scheduling problem is a typical partitioning problem : partitioning objects into a fixed number of groups to optimize an objective function. Consequently, this paper proposes a new crossover method named weighted-edge crossover which preserves both the structure and the characteristic of the feasible solution of partitioning problem. Furthermore, in order to improve the performance of GA, this paper defines a distance between feasible solutions and uses it in the adaptive control of crossover rate. To demonstrate the effectiveness of the proposed GA, comparative study of the GA with the conventional algorithms is carried out on several computational experiments.

mendeley

ブックマーク

詳細

PDFダウンロード

SNSによる共有

論文タイトル

ロボット制御則の並列化問題に対する遺伝アルゴリズムの適用

twitter
facebook
mendeley

Bibtex

Ris

マイナフィードバックを併用したH∞制御とその圧力制御系への応用

木村 哲也, 原 辰次, 冨坂 寿弘

pp. 331-337

DOI:

10.5687/iscie.10.331

抄録

The uncertainty model used in the H∞ control is norm bounded, while the actual modeling error is not so in general, and hence such uncertainty model can be conservative in certain applications. Therefore, the resulting system performance might be conservative if we simply apply the H∞ control scheme. An H∞ control scheme with minor feedback is examined to reduce the conservativeness. Since the minor feedback loop changes both the nominal plant and the uncertainty models, we cannot conclude immediately that it improves system performances even if the magnitude of uncertainty model is reduced. A disturbance attenuation problem is discussed to investigate the effect of the minor feedback, and a sufficient condition is derived on which the minor feedback improves system performance. Experimental results for a pneumatic pressure control system confirm the effectiveness of the proposed method.

mendeley

ブックマーク

詳細

PDFダウンロード

SNSによる共有

論文タイトル

マイナフィードバックを併用したH∞制御とその圧力制御系への応用

twitter
facebook
mendeley

Bibtex

Ris

決定論的変異を有するランダム探索法によるニューラルネットワークの一設計法

吉野 敏樹, 福見 稔, 赤松 則男

pp. 338-340

DOI:

10.5687/iscie.10.338
mendeley

ブックマーク

詳細

PDFダウンロード

SNSによる共有

論文タイトル

決定論的変異を有するランダム探索法によるニューラルネットワークの一設計法

twitter
facebook
mendeley

Bibtex

Ris

論文アクセスランキング

23 Nov. (Last 30 Days)

この機能はログイン後に利用できます。
下のボタンをクリックしてください。

詳細検索

論文タイトル

著者

抄録

ジャーナル名

年

出版日を西暦で入力してください（4桁の数字）。

検索したいキーワードを入力して下さい