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Transactions of the Institute of Systems, Control and Information Engineers Vol. 12 (1999), No. 5

ISIJ International
belloff
ONLINE ISSN: 2185-811X
PRINT ISSN: 1342-5668
Publisher: THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)

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  1. Vol. 37 (2024)

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  2. Vol. 36 (2023)

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  3. Vol. 35 (2022)

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  4. Vol. 34 (2021)

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  5. Vol. 33 (2020)

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  6. Vol. 32 (2019)

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  7. Vol. 31 (2018)

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  8. Vol. 30 (2017)

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  9. Vol. 29 (2016)

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  10. Vol. 28 (2015)

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  11. Vol. 27 (2014)

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  12. Vol. 26 (2013)

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  13. Vol. 25 (2012)

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  14. Vol. 24 (2011)

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  15. Vol. 23 (2010)

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  16. Vol. 22 (2009)

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  17. Vol. 21 (2008)

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  18. Vol. 20 (2007)

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  19. Vol. 19 (2006)

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  20. Vol. 18 (2005)

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  22. Vol. 16 (2003)

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  23. Vol. 15 (2002)

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  24. Vol. 14 (2001)

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  25. Vol. 13 (2000)

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  26. Vol. 12 (1999)

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  27. Vol. 11 (1998)

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  28. Vol. 10 (1997)

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  29. Vol. 9 (1996)

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  30. Vol. 8 (1995)

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  31. Vol. 7 (1994)

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  32. Vol. 6 (1993)

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  33. Vol. 5 (1992)

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  34. Vol. 4 (1991)

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  35. Vol. 3 (1990)

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  36. Vol. 2 (1989)

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  37. Vol. 1 (1988)

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

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Transactions of the Institute of Systems, Control and Information Engineers Vol. 12 (1999), No. 5

Evolutionary Segmentation of Texture Image Using Genetic Algorithms and Two-Dimensional Wavelet Transform

Motohide YOSHIMURA, Shunichiro OE

pp. 263-276

DOI:

10.5687/iscie.12.263

Abstract

In this paper we consider the segmentation problem of a texture image composed of different kinds of texture fields not as a pattern classification problem but a combinatorial optimization problem. We apply a probabilistic and effective successive search procedure of genetic algorithms to the clustering of small regions in a feature space. Moreover, we propose a new feature extraction scheme using two-dimensional wavelet transform, which can extract the hierarchical characteristics of the texture feature, and perform the accurate feature extraction upon the unstationary texture fields.

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Evolutionary Segmentation of Texture Image Using Genetic Algorithms and Two-Dimensional Wavelet Transform

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Active Vibration Control of a Building Structure against Earthquakes

Toshiharu SUGIE, Hideyuki TANAKA, Ken'ichi KIRIHARA, Masafumi OKADA, Yoshiyuki SUZUKI

pp. 277-282

DOI:

10.5687/iscie.12.277

Abstract

This paper is concerned with controller design and its experimental evaluation for active vibration control of a building structure in case of earthquake. Taking account of the mode-decomposition for the building structure model, we design an H∞ controller for active vibration control, where we adopt the linear matrix inequality approach because the standard assumption of H∞control is not satisfied in this case. Then we evaluate its effectiveness for a five-story building structure via experiments.

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Active Vibration Control of a Building Structure against Earthquakes

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Ris

An Iterative Learning Control Algorithm within Prescribed Input-Output Subspace

Kenichi HAMAMOTO, Toshiharu SUGIE

pp. 283-289

DOI:

10.5687/iscie.12.283

Abstract

In this paper, we consider an iterative learning control method (for short, ILC method). With the iteration of experiments, the ILC method yields the desired input for tracking the target trajectory. Most of former ILC methods use the time derivative of the error signal or the passivity of systems. Contrary to these former methods, this paper proposes an alternative ILC algorithm which does not use such things. This algorithm has the following property; the input space is restricted in the prescribed subspace, and the iterative learning law uses the modified error signal, which is projected on this input subspace. The effectiveness of the proposal method is demonstrated by a numerical example and an experiment.

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An Iterative Learning Control Algorithm within Prescribed Input-Output Subspace

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A Design of a Strongly Stable Self-Tuning Controller Using Coprime Factorization Approach

Akira INOUE, Akira YANOU, Yoichi HIRASHIMA

pp. 290-296

DOI:

10.5687/iscie.12.290

Abstract

This paper proposes a new self-tuning controller having a new design parameter. In selecting the design parameter, the controller gives a strongly stable self-tuning controller, that is, not only the closed-loop system is stable, but also the controller itself is stable.The controller consists of a generalized minimum variance controller and a parameter identification law. The proposed controller has an extended minimum variance controller with a newly introduced design parameter. The parameter is introduced by applying the coprime factorization approach and Youla parametrization of stabilizing compensators to the design of minimum variance controller.

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A Design of a Strongly Stable Self-Tuning Controller Using Coprime Factorization Approach

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A Genetic Algorithm Approach to Optimization Problems with Uncertainties

Hisashi TAMAKI, Toshihiko ARAI, Shigeo ABE

pp. 297-303

DOI:

10.5687/iscie.12.297

Abstract

In this paper, we propose a method of optimum seeking in an uncertain environment by extending the conventional genetic algorithms (GA). The key point of our approach is to evaluate an individual not directly by an objective value of a corresponding solution currently observed, but by accumulating values which have been observed at preceding generations. Finally, we confirm the effectiveness of our extended GA through some computaitional experiments using simple function optimization problems.

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A Genetic Algorithm Approach to Optimization Problems with Uncertainties

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A Discrete-Time SAC System with No Output Tracking Error

Deyu LI, Hiroshi SHIBATA, Toru FUJINAKA

pp. 304-312

DOI:

10.5687/iscie.12.304

Abstract

A feasible discrete-time SAC (Simple Adaptive Control) algorithm extended from continuous-time system was proposed for a single-input single-output (SISO) system and removed an offset between a plant output and a reference model output, by inserting parallel feedforward compensators to both of the plant and the reference model. Here, we contrive the design parameters instead of adding the parallel feedforward compensator to the model to remove the above-mentioned offset, and propose a discrete-time SAC algorithm which is feasible and applicable to a multi-input multi-output (MIMO) system. We prove the stability of the system by using asymptotic output tracker theory instead of CGT (Command Generator Tracker) theory, which removes the conventional restriction between the plant and the model.

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Implementation of the Alternating Direction Method of Multipliers for Quadratic Transportation Problems on a Vector Parallel Computer

Eiki YAMAKAWA, Masao FUKUSHIMA

pp. 313-315

DOI:

10.5687/iscie.12.313
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Implementation of the Alternating Direction Method of Multipliers for Quadratic Transportation Problems on a Vector Parallel Computer

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