| Project/Area Number |
19760297
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Control engineering
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| Research Institution | Ariake National College of Technology |
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Principal Investigator |
IKENOUE Masato Ariake National College of Technology, 電気工学科, 准教授 (10353343)
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| Project Period (FY) |
2007 – 2009
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| Project Status |
Completed (Fiscal Year 2009)
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| Budget Amount *help |
¥3,830,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥630,000)
Fiscal Year 2009: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2008: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2007: ¥1,100,000 (Direct Cost: ¥1,100,000)
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| Keywords | 制御理論 / システム同定 / 変数誤差モデル / 最小2乗法 / バイアス補償法 / 最小相関法 / 補助変数法 / 逐次計算アルゴリズム / パラメータ推定 / バイアス補償最小2乗法 |
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| Research Abstract |
In this study, some consistent estimation methods for errors-in-variables (EIV) models identification have been proposed under various noisy environments. Firstly, the bias-compensated least-squares (BCLS) method, which can be applied to the case where the input-output measurements are corrupted by white noises and colored noises, has been proposed, and it has been extended to continuous-time models identification problem. The bias-compensated instrumental variable type (BCIV-type) method has been proposed to deal with the case where the input-output measurements are corrupted by white noises, colored noises, quantization errors and the multiple noises. Moreover, the least-correlation (LC) based method has been proposed by introducing the prefilter and the extended vectors. Some recursive algorithms have been proposed and it is shown that the proposed algorithms provide good estimates via some numerical examples. Finally, the real-world applications using "Matlab/Simulink xPC Target"are considered, and we construct the environments the identification experiments.
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