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システム/制御/情報 Vol. 23 (2010), No. 4

ISIJ International
belloff
オンライン版ISSN: 2185-811X
冊子版ISSN: 1342-5668
発行機関: THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)

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システム/制御/情報 Vol. 23 (2010), No. 4

安全性を考慮して故障直後の過渡応答の乱れを抑制する制御系設計

陶山 貢市, 瀬部 昇

pp. 65-73

抄録

This paper presents control system synthesis to prevent undesirable transient responses after a device failure for safety against deviation from control range. It is based on multiobjective design for possible contexts and switchings by a failure to optimize the normal-case performance.

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安全性を考慮して故障直後の過渡応答の乱れを抑制する制御系設計

データベースとグリーディ探索を用いた渦電流探傷法における欠陥同定

Nguyen Thanh-Duong, 小島 史男

pp. 74-82

抄録

This paper is concerned with an optimization method to recover crack profiles from measurement signals obtained by eddy current testing. This inversion technique uses Greedy search algorithm to find the optimum of least-square error between measurement signals and simulation data. In creating simulation data, a database called ECT database is used. This database is constructed as a set of parameters-to-output mapping data, by using hybrid FEM-BEM simulator derived from Maxwell’s equations. Numerical experimental results show the effectiveness and feasibility of this method.

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データベースとグリーディ探索を用いた渦電流探傷法における欠陥同定

最悪ケースを考慮した最適スーパバイザの強化学習

梶原 弘治, 山﨑 達志

pp. 83-89

抄録

The supervisory control initiated by Ramadge and Wonham is a framework for logical control of discrete event systems. In the original supervisory control, the costs for occurrence and disabling of events have not been considered. Then, the optimal supervisory control based on quatitative measures has also been studied. This paper proposes a synthesis method of the optimal supervisor based on the worst-case behavior of discrete event systems. We introduce the new value functions for the assigned control patterns. The new value functions are not based on the expected total rewards, but based on the most undesirable event occurrence in the assigned control pattern. In the proposed method, the supervisor learns how to assign the control pattern based on reinforcement learning so as to maximize the value functions. We show the efficiency of the proposed method by computer simulation.

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最悪ケースを考慮した最適スーパバイザの強化学習

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