| Project/Area Number |
16360212
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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 | Kyushu Institute of Technology |
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Principal Investigator |
NOBUYAMA Eitaku Kyushu Institute of Technology, Faculty of Computer Science and Systems Engineering, Professor, 情報工学部, 教授 (50205291)
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| Co-Investigator(Kenkyū-buntansha) |
TSUCHIYA Takashi Institute of Statistical Mathematics, Department of Mathematical Analysis and Statistical Inference, Professor, 統計数理研究所・数理推論研究系, 教授 (00188575)
SEBE Noboru Kyushu Institute of Technology, Faculty of Computer Science and Systems Engineering, Associate Professor, 情報工学部, 助教授 (90216549)
KOGA Masanobu Kyushu Institute of Technology, Faculty of Computer Science and Systems Engineering, Associate Professor, 情報工学部, 助教授 (90251644)
ITO Hiroshi Kyushu Institute of Technology, Faculty of Computer Science and Systems Engineering, Associate Professor, 情報工学部, 助教授 (70274561)
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| Project Period (FY) |
2004 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥5,600,000 (Direct Cost: ¥5,600,000)
Fiscal Year 2006: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2005: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2004: ¥3,400,000 (Direct Cost: ¥3,400,000)
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| Keywords | Control systems design / Numerical optimization / Parallel computation / 平方和最適化 / 計算制御論 / 外点法アプローチ / Sum of Squares / ロバスト制御 |
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| Research Abstract |
The objective of this research project is to exploit a new field for control theory called "Computational Control Theory" which gives numerical methods using computational power for obtaining sub-optimal solutions for control problems which are hardly solved theoretically. In this term of project the following results have been obtained.
1. Iterative methods for obtaining sub-optimal numerical solutions to multi-objective control problems : For multi-objective control problems we have proposed a numerical method using sub-level sets, an exterior point method and a bi-section method, and show the effectiveness using some numerical examples.
2. System identification methods for gray-box models : For parameter estimation problem for gray-box models we have given some numerical methods based upon SOS (sum of squares) optimization methods, and given a robustness analysis method.
3. Robust control design methods for bi-linear systems : From the optimality condition for the L2 gain optimization problem in bi-linear systems Riccati-type inequalities including state variables are derived. For such inequalities we have given a numerical method based upon SOS (sum of squares) optimization methods to obtain a feasible solution.
4. Numerical methods for input-saturated systems : For input-saturated systems we have proposed a new representation form using polynomials, and given numerical methods for obtaining feasible solutions to robust analysis/design problems for such systems.
5. Parallel computing : We have constructed a PC cluster system for parallel computing, and applied it to solve some control design problems.
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