| Project/Area Number |
23560543
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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
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| Research Institution | Fukui University of Technology |
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Principal Investigator |
UOSAKI Katsuji 福井工業大学, 工学部, 客員教授(特任) (20029151)
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| Co-Investigator(Kenkyū-buntansha) |
HATANAKA Toshiharu 大阪大学, 情報科学研究科, 助教 (10252884)
KANAE Shunshoku 福井工業大学, 工学部, 教授 (90274555)
OSOGAMI Masahiro 福井工業大学, 工学部, 准教授 (70298389)
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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 |
¥5,070,000 (Direct Cost: ¥3,900,000、Indirect Cost: ¥1,170,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2011: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | 非線形フィルタ / バイオミメティックス / 進化計算 / パーティクルスォーム最 適化 / 確率近似法 / パーティクルスォーム最適化 / 粒子フィルタ / パーティクルスウォーム最適化 / パーティクルフィルタ(粒子フィルタ) / パーティクルスウォーム最適化(PSO) / 確率近似 |
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| Research Abstract |
Integrating the biomimetic approaches such as evolutionary computation techniques (genetic algorithm (GA), evolutionary strategies (EC), etc.) and swarm intelligence (particle swarm optimization (PSO), ant colony optimization (ACO), bacteria foraging optimization (BFO) algorithms, etc.) with the computer-intensive nonlinear filtering methods such as Monte Carlo filters and particle filters, new particle filters including the ES based unscented particle filter (ESUP) and stochastic approximation type nonlinear filter with an adaptive gain were developed.
An efficient guide selection method in the multi-objective PSO was proposed to obtain the Pareto optimal front, and it may be applicable to nonlinear filter design under the multi-criteria. Moreover, nonlinear identification methodology was developed for the static P-V curve estimation using Fuzzy logic and ACO.
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