Adaptive Hierarchical Network Model Reduction of Large-Scale Systems Strictly Preserving Finite Frequency Properties
| Project/Area Number |
25820177
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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 |
Control engineering/System engineering
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| Research Institution | The University of Tokyo |
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Principal Investigator |
KOJIMA CHIAKI 東京大学, 情報理工学(系)研究科, 助教 (00456162)
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| Project Period (FY) |
2013-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 制御理論 / 階層化ネットワークシステム / モデル低次元化 / 固有直交分解 / 有限周波数特性 / 安定性診断 / 分散カルマンフィルタ / 電力ネットワーク / 分散型固有直交分解 / 多次元システム |
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| Outline of Final Research Achievements |
In this research project, we first derived a model reduction method preserving dissipativity which is stronger property than finite frequency properties. Next, we proposed a distributed approach to the proper orthogonal decomposition which is one of efficient model reduction method of large-scale systems, and theoretically guaranteed an upper bound of an approximation error. Based on this approach, we also derived a method for transient stability diagnosis of power networks. In addition to these results, we characterized finite frequency properties of multi-dimensional systems in terms of dissipation inequality, which can be regarded as an original result. Moreover, we clarified an estimation performance of a distributed Kalman filter with diffusion strategies. This can be an efficient result for a design of the filter.
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Report
(4 results)
Research Products
(11 results)
