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2001 Fiscal Year Final Research Report Summary

Construction of a unified approach from modeling to control-system design of nonlinear systems

Research Project

Project/Area Number 12650452
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Control engineering
Research InstitutionOSAKA 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)

Co-Investigator(Kenkyū-buntansha) IMAI Jun  Okayama University, Department of Electrical and Electronic Engineering, Faculty of Engineering, Lecturer, 工学部, 講師 (50243986)
Project Period (FY) 2000 – 2001
KeywordsNonlinear 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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Published: 2003-09-17  

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