Synthesis of Control Systems based on Incomplete Observed Information
| Project/Area Number |
23656270
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Multi-year Fund |
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| Research Field |
Control engineering
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| Research Institution | Kyoto University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
AZUMA Shun-ichi 京都大学, 大学院・情報学研究科, 准教授 (40420400)
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| Project Period (FY) |
2011 – 2013
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2013: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2011: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 量子化出力 / 粒子フィルタ / システム同定 / 確率的制御器 / 量子化 / 線形近似モデル / 走化性システム |
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| Research Abstract |
This project studies how to design high performance control systems under incom-plete observed data by exploiting stochastic optimizations and stochastic controllers. First,particle fil-ters are shown to be effective to construct system models. Then a model-based method to reconstruct the high resolution signals from the low resolution ones is given and its effectiveness is evaluated. Further-more, it is confirmed that the stochastic behaviors in control are effective to compensate the incomplete observed data through various cases including multi-agent systems and biological ones.
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Report
(4 results)
Research Products
(9 results)
