Systemization of completely distributed optimization theory for large-scale systems and its application to social systems
| Project/Area Number |
15K06143
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Control engineering/System engineering
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| Research Institution | Tottori University |
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Principal Investigator |
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| Co-Investigator(Renkei-kenkyūsha) |
NISHIDA Shin-ichiro 鳥取大学, 大学院工学研究科, 教授 (50358529)
MIURA Masashi 鳥取大学, 大学院工学研究科, 助教 (80623537)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2015: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 分散制御 / 分散最適化 / マルチエージェントシステム / センサネットワーク / リアルタイムプライシング / スマートグリッド / ネットワーク / デマンドレスポンス |
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| Outline of Final Research Achievements |
In this study, we proposed a concept of a completely distributed optimization and designed an algorithm to realize this optimization. The core of the proposed algorithm is to enhance the accuracy of the estimation of global information by each user via communication between users. This enables us to control large-scale systems without centralized management systems. Moreover, we derived a necessary and sufficient condition of the topologies of communication networks to obtain solutions of optimization problems. Finally, we showed the practicability of the proposed algorithm by applying it to a power system and a sensor network.
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Report
(4 results)
Research Products
(34 results)
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[Journal Article] Neurocomputing2017
Author(s)
Kazunori Sakurama
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Journal Title
Leader selection via LASSO for formation control of time-delayed multi-agent systems
Volume: 270
Pages: 18-26
DOI
Related Report
Peer Reviewed
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