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Transactions of the Institute of Systems, Control and Information Engineers Vol. 13 (2000), No. 7

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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Transactions of the Institute of Systems, Control and Information Engineers Vol. 13 (2000), No. 7

Control of Jump Phenomena in a Flexible Rotor System

Kaoru INOUE, Shigeru YAMAMOTO, Toshimitsu USHIO, Takashi HIKIHARA

pp. 300-307

DOI:

10.5687/iscie.13.7_300

Abstract

A flexible rotor system has a coupled structure with a flexible rotor and a drive/effector. We have examined bifurcation phenomena of the system by an experiment and a simulation. As a result, it has been clarified that the jump phenomena occur in the rotating speed under mechanical resonance. This paper shows a sufficient condition for stabilization of an M-D-K-system which has continuously bounded time-varying coefficients, and proposes a control method which eliminates the jump phenomena in the rotating speed by using torque. The numerical discussion is also given.

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Control of Jump Phenomena in a Flexible Rotor System

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Ris

Self-Organization and Association for Fine Spatio-Temporal Spike Sequences

Kenichi AMEMORI, Shin ISHII

pp. 308-317

DOI:

10.5687/iscie.13.7_308

Abstract

In this paper, we discuss unsupervised learning for a temporally precise sequence. A network of leaky integrate-and-fire neurons is able to learn a fine spatio-temporal pattern, when the neurons are provided many excitatory random inputs. This unsupervised learning is achieved by selecting appropriate connections in the network. After learning, the trained network works as an associative memory with high temporal precision. Namely, it distinguishes the training sequence through filtering the disarranged sequence according to its correlation value with the training sequence.

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Self-Organization and Association for Fine Spatio-Temporal Spike Sequences

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Track Design of Linear-Motor Driven Transport System by Genetical CBR Method

Shinichiro ENDO, Masami KONISHI, Toshimichi MORIWAKI, Masayoshi YOSHIDA, Naoki TAKE

pp. 318-328

DOI:

10.5687/iscie.13.7_318

Abstract

A new design method for a traversal track formation in the linear-motor (LIM) driven transportation system has beeen developed. The object of the design is to minimize the LIM number assuring smoothness of vehicle speed control along the whole track. Conventionally, the design was made by human experts based on their experiments. Therefore, the quality of the design depends on their expert skill. To automate and standardize the design procedure, Cased Based Reasoning (CBR) technology was applied. In addition, Genetic Algorithms were used to update the CBR.

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Track Design of Linear-Motor Driven Transport System by Genetical CBR Method

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Ris

A Language to Generate GUI for Industrial Analyzers

Masaru KOBAYASHI, katsuo IKEDA

pp. 329-337

DOI:

10.5687/iscie.13.7_329

Abstract

A programing language to generate GUI for industrial analyzers is proposed. We use a keyword “State” which corresponds to the State of an analyzer. This “State” represents the status of a program, and enables us to compose a program in the same structure as the specification or the manual of the analyzer.

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A Language to Generate GUI for Industrial Analyzers

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Subspace-based Identification for Continuous-Time Stochastic Systems via Distribution-Theoretic Approach

Akira OHSUMI, Kentaro KAMEYAMA, Ken-Ichi YAMAGUCHI

pp. 338-345

DOI:

10.5687/iscie.13.7_338

Abstract

This paper presents a novel approach for system identification of continuous-time stochastic state space models from random input-output continuous data. The approach is based on the introduction of the random distribution theory in describing the (higher) time derivatives of stochastic processes, and the input-output algebraic relationship is derived which is treated in the time-domain. The efficacy of the approach proposed is examined by comparing with other approaches employing the filters.

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Subspace-based Identification for Continuous-Time Stochastic Systems via Distribution-Theoretic Approach

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