2001 Fiscal Year Final Research Report Summary
Construction of a unified approach from modeling to control-system design of nonlinear systems
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 |
Section | 一般 |
Research Field |
Control engineering
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Research Institution | OSAKA PREFECTURE UNIVERSITY |
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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Keywords | Nonlinear systems / Linear-model-sets identification method / modeling / System identification / Linear-model-sets |
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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