2001 Fiscal Year Final Research Report Summary
Analysis of Model Set and Time-Varying Control based on Complexity
| Project/Area Number |
11450164
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Control engineering
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| Research Institution | The University of Tokyo |
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Principal Investigator |
KIMURA Hidenori Complexity Science & Eng., The University of Tokyo, Professor, 大学院・新領域創成化学研究科, 教授 (10029514)
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| Co-Investigator(Kenkyū-buntansha) |
YAMAMOTO Shigeru Osaka Univ., Systems & Human Science, Associate Professor, 大学院・基礎工学研究科, 助教授 (70220465)
OISHI Yasuaki Mathematical Informatics, The University of Tokyo, Assistant Professor, 大学院・情報理工学系研究科, 講師 (80272392)
TSUMURA Kouji Information Physics & Computing, The University of Tokyo, Associate Prof., 大学院・情報理工学系研究科, 助教授 (80241941)
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| Project Period (FY) |
1999 – 2001
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| Keywords | Model / System identification / 4SID Method / Complexity / Learning theory / Control Systems / Adaptive control / LPV control |
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| Research Abstract |
1 Real-Time Identification of Time-Varying Systems
We are successful in obtaining sequential version of the 4-SID method which enables us to track the parameter variation of the system. We have clarified some fundamental structure of sequential 4-SID method from the viewpoint of realization theory. This is the most remarkable result we have obtained in this research program.
2 Analysis and Quantification of Model Complexity and Its Relation to Learning
We have applied learning theory to identification of model set and obtained the lower and upper bound of the samples required for guaranteering a prescribed model accuracy. We have defined complexity of model set through this sample number bounds. We have pointed out that the prevailing stochastic analysis of model set identification connected with control has some drawback.
3 Control Algorithm for Linear Parameter Varying (LPV) Systems
We have obtained some fundamental results on this issue. H-infinity control structure and topological aspects of model set have been considered from the LPV point of view. Also, we have considered the application of the so-called just-in-time (JIT) modeling. However, we are unable to establish so far the solid control architecture and algorithm for LPV systems based on the results obtained in (1) and (2).
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