| Project/Area Number |
14350225
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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 The University of Tokyo, Graduate School of Frontier Sciences, Professor, 大学院・新領域創成科学研究科, 教授 (10029514)
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| Co-Investigator(Kenkyū-buntansha) |
USHIDA Shun The University of Tokyo, Graduate School of Frontier Sciences, Research Associate, 大学院・新領域創成科学研究科, 助手 (30343114)
OIHSI Yasuaki The University of Tokyo, Graduate School of Information Science and Technology, Lecturer, 大学院・情報理工学系研究科, 講師 (80272392)
TSUMURA Koji The University of Tokyo, Graduate School of Information Science and Technology, Associate Professor, 大学院・情報理工学系研究科, 助教授 (80241941)
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| Project Period (FY) |
2002 – 2003
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| Project Status |
Completed (Fiscal Year 2003)
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| Budget Amount *help |
¥7,200,000 (Direct Cost: ¥7,200,000)
Fiscal Year 2003: ¥3,200,000 (Direct Cost: ¥3,200,000)
Fiscal Year 2002: ¥4,000,000 (Direct Cost: ¥4,000,000)
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| Keywords | Model-Driven control / Adaptive control / Complicated system / 2-degrees of freedom control system / control biology / quantum control system / モデル駆動型制御 / むだ時間 |
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| Research Abstract |
The purpose of the research is to formulate a new method of adaptive control called "Model-driven control" from a control theoretical point of view and to establish a theory for. analysis and synthesis as powerful control design framework. We have revealed significances and its properties of model-driven control architecture from theoretical and experimental aspects. A fundamental concept of model-driven control comes from a motor control of human. In this research, in order to provide new developments of method for dealing with "Complicated System" for both fields of adaptive control and motor control we tried the following three themes mainly (1) The formulation of model-driven adaptive control and the relation to motor control, (2) The establishment of identification method for complicated systems and the relation to learning control and (3) Control theoretical approaches to various nonlinear complicated systems
In (1), we formulated a well-known "Feedback Error Learning method" as two-degrees of freedom control systems and investigated its closed-loop structure. A stability of the closed-loop system including adaptation and a convergence of its adaptation parameters were shown theoretically. Furthermore, these results were extended to a case where a time delay exists in the feedback loop. Each, result in (2) includes interest approaches to the essential difficulties for dealing with complicated systems. In (3), we obtained various outcomes which related to various complicated system, e.g., nonlinear robot arm, a hear exchanger in a fuel cell, control biology, biomechanics of human motor control, quantum control systems, a large scale network system and so on. In particular, results on control biology and quantum control system moved forward the frontier of new field in control theory.
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