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Transactions of the Institute of Systems, Control and Information Engineers Vol. 27 (2014), No. 1

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

Backnumber

  1. Vol. 37 (2024)

    1. No.9
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    3. No.7
    4. No.6
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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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  21. Vol. 17 (2004)

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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)

    1. No.12
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    3. No.10
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  36. Vol. 2 (1989)

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    3. No.10
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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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Transactions of the Institute of Systems, Control and Information Engineers Vol. 27 (2014), No. 1

Design of Servo Systems to Attain the Given Setting Time

Yuzo Ohta, Takeshi Takiyama, Izumi Masubuchi

pp. 1-7

DOI:

10.5687/iscie.27.1

Abstract

In this paper, we treat 2 dimensional systems or systems which can be approximated as 2 dimensional systems. We will propose a PI control scheme of a servo system design that gives the shortest M% settling time and satisfies a percent overshoot requirement for an assigned M. The usefulness of the proposing method is demonstrated through examples.

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Design of Servo Systems to Attain the Given Setting Time

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Ris

On the Bifurcation Analysis of the Stochastic Predator-prey System based on the D-bifurcation

Masaaki Ishikawa

pp. 8-13

DOI:

10.5687/iscie.27.8

Abstract

This research is concerned with a bifurcation analysis of a stochastic predator-prey system. The P-bifurcation (Phenomenological bifurcation) and the D-bifurcation (Dynamical bifurcation) are major analytical methods for the stochastic bifurcation. The P-bifurcation studies a stationary measure corresponding to the one-point motion, while the D-bifurcation approach is based on the stability of invariant measures. Since the P-bifurcation is based on the one point-motion, there is a possibility to miss certain branches in bifurcation. So, we study the bifurcation of the stochastic predator-prey system with help of the D-bifurcation, and analyze the influence of the random noise on the bifurcation phenomena in the proposed stochastic model.

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On the Bifurcation Analysis of the Stochastic Predator-prey System based on the D-bifurcation

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Distributed Circle Fitting by an Averaging Consensus Algorithm

Yu Muranishi, Naoki Hayashi, Shigemasa Takai

pp. 14-19

DOI:

10.5687/iscie.27.14

Abstract

This paper considers circle fitting problems by an averaging consensus algorithm of multi-agent systems. We propose a distributed approach where each agent arranged in a plane estimates a circle that minimizes the algebraic or geometric distance to all agents. The simulation result shows that the proposed circle fitting can find the optimal circle by the distributed consensus algorithm.

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Distributed Circle Fitting by an Averaging Consensus Algorithm

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Synthesis of Fixed-Structure Dynamic Quantizers by using Evolutionary Algorithm

Yuki Minami, Takao Muromaki

pp. 20-27

DOI:

10.5687/iscie.27.20

Abstract

This paper addresses the design problem of fixed-structure dynamic quantizers for discrete-valued input control. The problem is to find a dynamic quantizer when the dimension and the decentralized structure of quantizer are given as design specifications. In this paper, we first formulate a quantizer design problem under constraint conditions such as stability and input saturation. Then, for getting a solution to the problem, we provide a simple and useful design method with a particle swarm optimization which is one of evolutionary algorithms. Finally, we verify that the proposed method gives satisfactory fixed-structure dynamic quantizers, by several numerical examples.

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Synthesis of Fixed-Structure Dynamic Quantizers by using Evolutionary Algorithm

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