| Project/Area Number |
12650452
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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 PREFECTURE UNIVERSITY |
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Principal Investigator |
WADA Teruyo Osaka Prefecture University, Department of Mechanical Systems Engineering, Graduate School of Engineering, Assistant Professor, 大学院・工学研究科, 講師 (70201259)
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| Co-Investigator(Kenkyū-buntansha) |
IMAI Jun Okayama University, Department of Electrical and Electronic Engineering, Faculty of Engineering, Lecturer, 工学部, 講師 (50243986)
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| Project Period (FY) |
2000 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥3,300,000 (Direct Cost: ¥3,300,000)
Fiscal Year 2001: ¥1,300,000 (Direct Cost: ¥1,300,000)
Fiscal Year 2000: ¥2,000,000 (Direct Cost: ¥2,000,000)
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| Keywords | Nonlinear systems / Linear-model-sets identification method / modeling / System identification / Linear-model-sets |
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| Research Abstract |
The final purpose of this research is to construct a unified approach from modeling and identification to control-system design of nonlinear systems with theoretical background, and the followings are the obtained results.
1. Modeling of nonlinear systems : The feasibility of the modeling method was investigated, by which a nonlinear system is modeled as a set of linearized systems at plural operating points.
2. Identification method: As an identification method based on the above modeling method, the linear-model-sets identification (LM-sets ID) method was proposed, which was the identification method for nonlinear plants under shifts of operating points. Applying this method to a nonlinear plant, we can identify the plant from input-output data as a collection of a finite number of linear-model-sets (LM-sets), each of which includes the exact linearized model of the plant at each operating point.
3. Control-system design and analysis : Design method of gain scheduled control systems was derived for nonlinear plants based on the above LM-sets ID method. A theoretical analysis was achieved which ensures the convergence of the state of the scheduled control system.
4. A numerical simulation was given to prove the effectiveness of the above methods.
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