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Transactions of the Institute of Systems, Control and Information Engineers Vol. 8 (1995), No. 6

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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  14. Vol. 24 (2011)

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  16. Vol. 22 (2009)

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  17. Vol. 21 (2008)

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  20. Vol. 18 (2005)

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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
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    3. No.5
    4. No.4
    5. No.3
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Transactions of the Institute of Systems, Control and Information Engineers Vol. 8 (1995), No. 6

An Approach to Parameter Identification of Continuous-Time System Based on λ Transform

Yang Wu, Tohru KATAYAMA

pp. 237-241

DOI:

10.5687/iscie.8.237

Abstract

This paper deals with the identification of parameters of continuous-time system based on λ-transform (λ=1/ (τs+1)) due to Johansson. Using the pre-filtering technique based on the λ transform followed by a sampling of the pre-filtered signals, we derive a linear regression model to which the_least-squares (LS) method is applied. Noting that the residuals associated with the LS estimate are dependent on the parameter of the pre-filter, we present a simple search method of choosing the optimal parameter so that the sum of squared residuals is minimized. To show the applicability, we present simulation results for the identification of vibrating systems excited by an impulse input where the output acceleration is measured.

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An Approach to Parameter Identification of Continuous-Time System Based on λ Transform

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Ris

A Polynomial Matrix Approach to the ILQ Servo Controller Design

Kenji SUGIMOTO, Akira INOUE

pp. 242-248

DOI:

10.5687/iscie.8.242

Abstract

This paper proposes a new design scheme for multivariable servo control systems. By making full use of fractional representation by polynomial matrices, this scheme provides a frequency-domain version of the well-known ILQ design method, and connects the designed controller with the circle criterion in a transparent form. LQ optimality for some weightings is guaranteed by letting a parameter tend to infinity, and the lower bound for optimality in this sense can be computed by means of a generalized eigenvalue problem, together with a bisection algorithm.

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A Polynomial Matrix Approach to the ILQ Servo Controller Design

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Ris

Modeling and Control of Flexible Solar Array Paddles with Revolute Joints

Fumitoshi MATSUNO, Maki OKA

pp. 249-257

DOI:

10.5687/iscie.8.249

Abstract

In this paper, modeling and vibration control of flexible solar array paddles with revolute joints, which are mounted on satellites and free flying robots, are discussed. We consider flexible solar array paddles which are in zero gravity field and are rotated about two axes of the flexible plates by motors. We assume the solar array paddles can be regarded as connected two fully clamped rectangular plates. We first derive partial differential equations and two sets of boundary conditions which represent vibration of the paddles and ordinary differential equations which represent the dynamics of angles of rotation of motors. On the basis of a finite-dimensional modal model for the distributed parameter system, an optimal controller with low-pass property and a robust H∞ controller are constructed. Simulation results confirm that the controllers perform remarkably well.

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Modeling and Control of Flexible Solar Array Paddles with Revolute Joints

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A Design Method for Multivariable Model Reference Adaptive Control Systems Including Fixed Compensator with Two-Degree-of-Freedom Structure

Shiro MASUDA, Akira INOUE

pp. 258-268

DOI:

10.5687/iscie.8.258

Abstract

A multivariable model reference adaptive control system (MRACS) including a fixed compensator is proposed. First, an exact model matching (EMM) system with two-degree-of-freedom structure is derived. Using this structure, a multivariable MRACS including fixed compensator is constructed. Since the proposed method is based on the EMM system with two-degree-of-freedom structure, the fixed compensator is chosen independently of specifications for responses to reference commands. The boundedness of all signals in the closed-loop system and the convergence of the output error are proved. A design method of the fixed compensator for MRACS with low sensitivity is also given. Finally, numerical examples are illustrated in order to show the effectiveness of the proposed method.

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A Design Method for Multivariable Model Reference Adaptive Control Systems Including Fixed Compensator with Two-Degree-of-Freedom Structure

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A Genetic Algorithm for Nonstationary Function Optimization Problems

Kazuhiro OHKURA, Kanji UEDA

pp. 269-276

DOI:

10.5687/iscie.8.269

Abstract

An extended genetic algorithm for solving nonstationary function optimization problems is presented. When using a standard genetic algorithm, it is difficut to deal with those problems due to brittleness caused by the fact that the population tends to stay where it believes to be optimal. In order to overcome this unwanted phenomenon, a new string representation associated with inactive regions for being capable of adopting various types of neutral mutations is presented. Genetic operations except for point mutations are prepared to be effective for all the genes in as a subset of genes that which is also an object of other genetic opetations. Further, using this extension, two 0/1 knapsack problems are examined to discuss the dynamics of the extended genetic algorithm. In the experiments, the population shows the behavior asserted in the neutral theory of molecular evolution and the directed evolution emerged as the result of acquiring two adaptive strategies.

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A Genetic Algorithm for Nonstationary Function Optimization Problems

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