Controlled self-organizing networks with model prediction control
| Project/Area Number |
26730048
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Information network
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| Research Institution | Osaka University |
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Principal Investigator |
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2016: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2015: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | センサーネットワーク / 自己組織型制御 / 最適制御 / 自己組織化制御 / 管理型自己組織化制御 / H∞制御 / モデル予測制御 / ロバスト制御 |
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| Outline of Final Research Achievements |
In this research, we introduced the model predictive control into network systems to improve their convergence performance against environmental changes. In this research, we focused on sensor network systems for collecting environmental information with potential-based routing that is one of self-organizing routing methods. In this routing method, it is known that each node calculates its own potential value based on local information and it takes much time to converge the calculation. By giving an optimal control input from an external controller to a part of nodes, the calculation time for potential of all nodes can be greatly reduced without losing the advantages of self-organizing method.
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Report
(4 results)
Research Products
(6 results)
