JaLCDOI 10.18926/46948
FullText URL mfe_38_1-2_015_027.pdf
Author Torigoe, Takashi| Konishi, Masami| Imai, Jun| Nishi, Tatsushi|
Abstract In these days, mechanical systems are becoming more complex and highly automated. So, there exist wide variety of demands for reliable diagnostic technology. A reliable data analysis and quantitative diagnosis method of mechanical system is necessary for the purpose. In this paper a quantitative diagnosis method for looper height control system has been developed based on neural network technologies. The wavelet transformation is used for pre-processing to analyze characteristics of looper height control system. And, self organizing map neural network is used for the purpose of classification based on the pre-processed data. After that, the classified results are used for quantitative diagnosis in hierarchical neural network.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2004-03
Volume volume38
Issue issue1-2
Start Page 15
End Page 27
ISSN 0475-0071
language 英語
File Version publisher
NAID 80016785934
JaLCDOI 10.18926/46947
FullText URL mfe_38_1-2_005_014.pdf
Author Ishimaru, Kazuhito| Konishi, Masami| Imai, Jun| Nishi, Tatsushi|
Abstract Temperature distribution in the reactor furnace is mainly operated by gas blowing from multiple tuyeres and material charge distribution. The objective of our research is obtain the optimal profile of gas flow to control temperature distribution in the reactor furnace in the shortest possible time. We formulated the optimization problem to reduce deviation of temperature distribution from its desired one in the reactor furnace. Based on the formulation, gas blow conditions are optimized by a sequential quadratic programming method to realize the desired temperature distribution. The validity of the method was checked through numerical experiments.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2004-03
Volume volume38
Issue issue1-2
Start Page 5
End Page 14
ISSN 0475-0071
language 英語
File Version publisher
NAID 80016785933
FullText URL IFAC_49_8_7.pdf
Author Imai, Jun| Noso, Katsuyuki| Takahashi, Akiko| Funabiki, Shigeyuki|
Keywords Distributed parameter systems Method of weighted residuals Boundary conditions Reduced-order models
Note This is an Accepted Manuscript of an article published by Elsevier|
Published Date 2016-08-09
Publication Title IFAC-Papers OnLine
Volume volume49
Issue issue8
Publisher Elsevier
Start Page 7
End Page 12
ISSN 2405-8963
Content Type Journal Article
language 日本語
OAI-PMH Set 岡山大学
Copyright Holders https://creativecommons.org/licenses/by-nc-nd/4.0/deed.ja
File Version author
DOI 10.1016/j.ifacol.2016.07.410
Web of Science KeyUT 000381505200003
Related Url https://doi.org/10.1016/j.ifacol.2016.07.410
Author Konishi, Masami| Nakano, Koichi| Imai, Jun|
Published Date 2011-06-01
Publication Title 鉄と鋼
Volume volume97
Issue issue6
Content Type Journal Article
Author Imai, Jun|
Published Date 2002-8
Publication Title SICE 2002. Proceedings of the 41st SICE Annual Conference
Volume volume3
Content Type Journal Article
FullText URL fulltext.pdf
Author Imai, Jun| Wada, Kiyoshi|
Keywords error analysis flexible structures frequency-domain analysis linear programming modelling parameter estimation uncertain systems
Note Print ISBN: 0-7803-6638-7|
Published Date 2000-12
Publication Title Proceedings of the 39th IEEE Conference on Decision and Control
Volume volume4
Publisher IEEE
Start Page 3780
End Page 3784
ISSN 0191-2216
NCID BA51644536
Content Type Journal Article
language 英語
OAI-PMH Set 岡山大学
Copyright Holders © 2000 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
File Version publisher
DOI 10.1109/CDC.2000.912298
Web of Science KeyUT 000172029000684
Author Imai, Jun| Ando, Yasuaki| Konishi, Masami|
Published Date 2003-12
Publication Title Decision and Control
Content Type Journal Article
Author Imai, Jun|
Published Date 2002-12
Publication Title Decision and Control
Content Type Journal Article
Author Takenaga, Hiroki| Konishi, Masami| Imai, Jun|
Published Date 2009-11-11
Publication Title Proceedings : Fifth International Workshop on Computational Intelligence & Applications
Volume volume2009
Issue issue1
Content Type Conference Paper
JaLCDOI 10.18926/47023
FullText URL mfe_36_2_015_042.pdf
Author Ohtani, Ryuji| Konishi, Masami| Imai, Jun| Nishi, Tatsushi|
Abstract In this paper, we studied a planning and scheduling of production system considering demand changes. In the proposed system, planning part determines lot-size and amount of jobs in production. On the other hand, scheduling part determines the production sequence of jobs. In order to treat with the demand changes, both planning and scheduling should work well simultaneously. In the proposed system, preset and real time production control system is newly constructed from the view point of adaptive control. In the system, production planning is modified when the difference between production amount and demand becomes large. Moreover, production schedule is regenerated when the determined schedule is deviated from the prospected one. The scheduling system is characterized as the autonomous decentralized optimization system where each job works as agent and agent searches its appropriate starting time of processing. The effectiveness of the proposed system is confirmed by numerical examples.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2002-03
Volume volume36
Issue issue2
Start Page 15
End Page 42
ISSN 0475-0071
language 英語
File Version publisher
NAID 80015471209
JaLCDOI 10.18926/46998
FullText URL mfe_36_1_029_039.pdf
Author Imai, Jun| Wada, Kiyoshi|
Abstract A procedure for control-oriented modeling is proposed for large flexible structures with unknown modal parameters. Techniques on quantification of errors in modal truncated nominal models are developed for the case where a finite number of upper and lower bounds of the unknown modal parameters are given. A feasible set of systems matching the conditions is introduced, and then error bounds covering the feasible set are established in the frequency domain. The bounds are easily checked using linear programming for any user-specified frequency. The feasibility of the proposed scheme is illustrated by numerical study on an ideal flexible beam example.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2001-12
Volume volume36
Issue issue1
Start Page 29
End Page 39
ISSN 0475-0071
language 英語
File Version publisher
NAID 80012887118
JaLCDOI 10.18926/46978
FullText URL mfe_37_2_029_044.pdf
Author Imajo, Shuya| Konishi, Masami| Imai, Jun| Nishi, Tatsushi|
Abstract In hot strip rolling mills, the looper control system is automated. However, the looper's behavior tends to be unstable in threading. Therefore, human expert always intervenes and stabilizes the looper's behavior by tuning PID gains and interposing manipulation variable of looper control system. In this paper, we propose a method based on the recurrent neural network to express PID gains tuning action by human. Furthermore, we propose two methods to update the model by learning. To check the effectiveness of the proposed learning methods, numerical simulation applied to the looper height control is carried out.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2003-03
Volume volume37
Issue issue2
Start Page 29
End Page 44
ISSN 0475-0071
language 英語
File Version publisher
NAID 80016037880
JaLCDOI 10.18926/46977
FullText URL mfe_37_2_013_027.pdf
Author Shibuta, Taizo| Konishi, Masami| Imai, Jun| Nishi, Tatsushi|
Abstract Nowadays, various kind of reactor furnaces are widely used for the production in industry. The raw materials charged into the furnace generate reaction heat produced by blowing gas. Generally speaking, the reaction heat generated in the furnace is remarkably high. Therefore the occurrence of an inappropriate temperature distribution in the furnace may make damege or serious accident of the furnace. This is the motivation of furnace control. The author is considering the application of studied results to the furnace control of Blast Furnace in steel industry. To the propose, the approximated and simplified Macro Model of the Blast Furnace is constructed which has the function of representation of qualitative characteristics of the furnace in dynamical sense. The furnace temperature, distribution greatly effects both on the producting and the product quality of the furnace. Needless to say, stable furnace operation is indispensable for the economical prosperity of the industry. In this paper, macro simulation of the furnace is developed to support the analysis and design of the furnace control. Using the simulator, the stability and the control characteristics for inner furnace temperature distribtion are analised quantitatively.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2003-03
Volume volume37
Issue issue2
Start Page 13
End Page 27
ISSN 0475-0071
language 英語
File Version publisher
NAID 80015999991
JaLCDOI 10.18926/46967
FullText URL mfe_37_1_001_010.pdf
Author Sotobayashi, Ken| Konishi, Masami| Nishi, Tatsushi| Imai, Jun|
Abstract Auto Guided Vehicles (AGVs) are widely used in a semi-conductor fabricating factory and contribute to the stable production of a high quality semi-conductor products. In the near future, further expansion of the transportation system is expected accompanied with the rapid growth of semi-conductor industries. In such situation, the necessity of performing quick planning of transportation route and transportation control will be elevated. In this paper, practicable planning of the transportation route and transportation control are studied based on the decentralized agent method. Especially, the geometrical sizes of AGVs are considered in the determination of transportation routes and control strategy avoiding the occurrence of mutual collisions or deadlock of AGVs.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2002-11
Volume volume37
Issue issue1
Start Page 1
End Page 10
ISSN 0475-0071
language 英語
File Version publisher
NAID 120003457322
JaLCDOI 10.18926/44495
FullText URL mfe_045_001_014.pdf
Author Akiyoshi, Tatsuro| Imai, Jun| Konishi, Masami|
Abstract This paper presents a method of the controller design for the handling machine by using dsPIC(Digital Signal Processor + Peripheral Interface Controller). Recently, many manufacturing robots are operated in manufacturing facilities, with the aim of labor, cost saving, and improvement of the productivity. Such robots need to have positioning performance of high precision and simultaneously to save cost. In this paper, a digital optimal servo controller is designed, and it is implemented into our barebones controller which involves dsPIC. We have designed and manufactured the controller which is added suitable peripherals to improve the consistency between the mechanical machine operating in continuous time and controller in discrete time. The significance of this research is that digital implementation of the embedded system which has performance-limitation has ensured a comparable result, against the one with PC which has broad utility. When it is used as a controller, it is possible to restrain product prices greatly equivalent PC precision. We demonstrate potential that good control can be achieved even with low cost. Our research has lead to the viability of lower cost and higher performance system for the production process at factories.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2011-01
Volume volume45
Start Page 1
End Page 14
ISSN 1349-6115
language 英語
Copyright Holders Copyright © by the authors
File Version publisher
NAID 120002905951
JaLCDOI 10.18926/17844
FullText URL Mem_Fac_Eng_OU_43_75.pdf
Author Ohe, Keita| Konishi, Masami| Imai, Jun|
Abstract As is well known, an advanced knowledge and know-how are needed in the design and the diagnosis work. Further, human experts can cope with the recent trend of customers needs. Therefore, the design and the diagnosis work have been privately performed in the past, and its information cannot be shared. In addition, the number of experts is decreasing. It is a very important problem to maintain and to extend experts technologies having been built up. For the purpose, methods and systems for technical inheritance of the advanced techniques of the skilled engineers are needed to train the unskilled operators and also can assist skilled operators. In this research, attention is focused on the design of analog filter circuit. To attain the target, the circuit structural classifier system to support design work is developed. Furthermore, simulation technology for hot strip rolling mills based on distributed agents is presented aimed to develop tools for the diagnosis of hot strip rolling mills operation.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2009-01
Volume volume43
Start Page 75
End Page 92
ISSN 1349-6115
language 英語
File Version publisher
NAID 120002308900
JaLCDOI 10.18926/17841
FullText URL Mem_Fac_Eng_OU_43_55.pdf
Author Inoue, Shinichiro| Konishi, Masami| Imai, Jun|
Abstract In this research, an image processing method and a system for inspection support of a rod figured cutting tool are developed. As is well known, the visual inspection of a cutting tool by image processing is not easy, because cutting blade have a helical blade structure. To cope with the problem, an experimental facility with rotation and longitudinal tool shift functions to enable acquisition of blade surface pictures along a cutting rod is developed. The type of the defect treated in this paper is the spot of coating on blade surface. To judge the quality of the processed image of blade surface, neural network with autonomous learning is used. The processed image of cutting tool is divided into 64 × 64 blocks used for the input to the neural networks. Before input, each block data is preprocessed applying a edge detection filter and a transformation by the discrete fourier transform (DFT). Using these technologies, the experimental inspection system is built and tested to check the capabilities of the inspection algorithms. The diagnostic performance of the surface defect of a cutting tool was confirmed. There remained a problem to mis judge the normal tools as the defect.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2009-01
Volume volume43
Start Page 55
End Page 60
ISSN 1349-6115
language 英語
File Version publisher
NAID 120002308973
JaLCDOI 10.18926/17839
FullText URL Mem_Fac_Eng_OU_43_49.pdf
Author Akamatsu, Shinya| Konishi, Masami| Imai, Jun|
Abstract In this paper, the controlled target is the SCARA robot with two links, and the object is fine control of the arm head position of the robot. To attain the object, Internal Model Control (IMC) is introduced. A nonlinear equations are for robot dynamics formulated by solving Lagrange equation, and is linearized to design control system by IMC. The controller of IMC is designed or synthesisted as the inverse system of the linearized model, and IMC filter model is selected. Also, reference filter is introduced to make the improvement of performance. The result of control performance by IMC is compared with that of PID numerically, accuracy and incoherency are confirmed.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2009-01
Volume volume43
Start Page 49
End Page 54
ISSN 1349-6115
language 英語
File Version publisher
NAID 120002308854
JaLCDOI 10.18926/17837
FullText URL Mem_Fac_Eng_OU_43_39.pdf
Author Kuwashima, Takayuki| Imai, Jun| Konishi, Masami|
Abstract This paper presents method of the controller design for one link arm with parametric uncertainty. Recently, many manufacturing robots are operated in manufacturing facilities, with the aim of labor and cost saving or improvement of the productivity. Such robots need to have positioning performance of high precision. In condition that there is an uncertainty in plant dynamics, desired control performance may not be attained because the controller is designed according to the mathematical model of a plant. So it is important that the designed control system have a robust control performance. In this paper, the robust controller is designed using Quantitative Feedback Theory (QFT) for one link arm with parametric uncertainty. Simulation experiments are run for control system designed by using QFT and conventional method. The results are compared with each other and it is found that the control system designed by QFT shows a robust performance and can suppress the unevenness of output against parametric uncertainty.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2009-01
Volume volume43
Start Page 39
End Page 48
ISSN 1349-6115
language 英語
File Version publisher
NAID 120002308875
JaLCDOI 10.18926/17835
FullText URL Mem_Fac_Eng_OU_43_32.pdf
Author Mabuchi, Shuji| Konishi, Masami| Imai, Jun|
Abstract A tractor-trailer vehicle in the factory might move on the route determined beforehand. However, automation of a tractor-trailer vehicle is difficult so that it is necessary to consider the nonlinearity of a vehicle and a trailer. In this research, the effective tracking control method of a tractor-trailer vehicle is proposed. The control method using time-state control form for a preview control is presented, and be applied a tractor-trailer vehicle with nonholonomic characteristics. Results of numerical experiments are presented to check effectiveness of the proposed control method.
Publication Title Memoirs of the Faculty of Engineering, Okayama University
Published Date 2009-01
Volume volume43
Start Page 32
End Page 38
ISSN 1349-6115
language 英語
File Version publisher
NAID 120002308736