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Transactions of the Institute of Systems, Control and Information Engineers Vol. 2 (1989), No. 8

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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  2. Vol. 36 (2023)

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  6. Vol. 32 (2019)

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  7. Vol. 31 (2018)

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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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  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)

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Transactions of the Institute of Systems, Control and Information Engineers Vol. 2 (1989), No. 8

A Method of Recognition of Separation from Group

Yutaka TAKAHASHI, Masaru NISHIDE, Eiichi BAMBA

pp. 253-260

DOI:

10.5687/iscie.2.253

Abstract

This paper presents a method that one holonic subsystem in the overall system can recognize separation from a, group. To remain in the group is a complemental event to the separation. After each subsystem has listened to the others' chats, it always broadcasts what could be caught. One subsystem can contact with the others if they make a directed closed-loop in the graphic network of the system. And then, those subsystems make up a group. One can look for the directed closed-loop by the reachability matrix which is built from the listeners' status. The experiment using microcomputers shows that this method is useful for the recognition of separation from group.

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A Method of Recognition of Separation from Group

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Ris

Feedforward and Repetitive Control for Machine Tool Feed Drives

Yasushi MIURA, Masayoshi TOMIZUKA

pp. 261-267

DOI:

10.5687/iscie.2.261

Abstract

A feed drive control method to improve the accuracy of periodic trajectory is described and evaluated. The method is based on the combination of feedforward control (zero phase error tracking control) and repetitive control. Adding the repetitive control compensates for the model mismatching which generally degrades feedforward control performance. Investigations on robust stability and disturbance effects reveal some tips on controller design. A repetitive controller is proposed to assure robust stability for unmodelled dynamics and dead-time while maintaining tracking performance in low frequencies. The regulation error, however, is increased in certain frequencies by adding the repetitive controller under the existence of load disturbances and measurement noise. Simulation results indicate that the proposed approach greatly decreases the tracking error.

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Feedforward and Repetitive Control for Machine Tool Feed Drives

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Slip Frequency Control Type Vector Control of an Induction Motor Using Numerical Data Processor

Kaneo TAKAKU

pp. 268-273

DOI:

10.5687/iscie.2.268

Abstract

As a method of variable-speed induction motor drives, there is newly developed vector control method. The vector control method is made by controlling flux current component and torque current component of stator current vector, respectively. Since the flux component is parallel with rotor flux vector and the torque component is perpendicular with the flux vector, the control method is characterized by decoupling between the components of flux and torque.
In the vector control method, there are field-orientation method (rotor flux vector detection type-vector control method) and slip frequency control type vector control. A flux detector is required in the field-orientation method, and therefore, the slip frequency control type vector control has been made by a 16-bit personal computer using numerical data processor. Then, the vector controlled induction motor shows good dynamic performance. This paper describes the theory and experimental results.

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Slip Frequency Control Type Vector Control of an Induction Motor Using Numerical Data Processor

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Two Formulations of Discriminant Problem for Interval Data

Hisao ISHIBUCHI, Hideo TANAKA

pp. 274-282

DOI:

10.5687/iscie.2.274

Abstract

In the conventional discriminant analysis, the attribute values of each sample are represented by a point in the multi-dimensional feature space. But they should be represented by an interval vector in the feature space when the observed values are not constant but fluctuating with time. Thus we intend to propose a discriminant method for multi-dimensional interval data. The discriminant method for the interval data is based on the interval linear discriminant function which maps an interval vector in the multi-dimensional feature space to an interval in the one-dimensional decision space. Therefore our discriminant problem is to determine the interval linear discriminant function and group intervals which represent the given groups in the one-dimensional decision space. In this paper, two mathematical programming problems are formulated for such a discriminant problem and computational algorithms using the linear programming are shown.

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Two Formulations of Discriminant Problem for Interval Data

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