| Project/Area Number |
17560392
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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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 | Osaka University |
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Principal Investigator |
YAMAMOTO Shigeru Osaka University, Graduate School of Engineering Science, Associate Professor, 大学院基礎工学研究科, 助教授 (70220465)
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| Co-Investigator(Kenkyū-buntansha) |
FUJII Takao Fukui University of Technology, Faculty of Engineering, Professor, 工学部, 教授 (70029510)
KANEKO Osamu Osaka University, Graduate School of Engineering Science, Research Associate, 大学院基礎工学研究科, 助手 (00314394)
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| Project Period (FY) |
2005 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2006: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2005: ¥2,600,000 (Direct Cost: ¥2,600,000)
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| Keywords | control systems design / controller tuning / system identification / data driven controller design / model reference control |
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| Research Abstract |
We consider several important issues concerned with designing a closed loop system for an unknown plant based on input/output measurements. The main results are as follows.
1. We have proposed a direct method to obtain parameters of the desired controller via controller identification from the input/output measurements and the desired response instead of model identification of the plant. The proposed method is an extension of the existing method, i.e., VRFT and FRIT. A salient feature of the proposed method is to be able to detect unexpected closed loop instability by using identification error.
2. We addressed the issues on the optimality of the parameter obtained FRIT, and have provided the theoretical result that applying a prefilter enables us to obtain the actual optimal parameter for the achievement of the optimal tracking performance. Based on this theoretical result, we have also expanded FRIT into more practical method in the sense that the optimization can be performed in the linear computation, which implies that the result obtained here can be examined by more simple computation.
3. We have proposed a new concept "identification of a plant via controller identification" of system identification based on controller tuning. That is, by tuning a controller including the structure of a plant, we have an optimal parameter of the plant reflecting the information of the data and the given specification.
4. We have addressed the connection between an existing canonical controller and proposed FRIT. We have reformulated canonical controllers in our framework. As a result, we have refined FRIT in the sense that the tuning method done in FRIT yields the parameter fitting the data and the given specification from the theoretical points of view.
5. We have extended the proposed method to obtain a single controller which uniformly achieves control performance under plant dynamics variation.
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