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2016 Fiscal Year Final Research Report

Foundation of control theory based on statistical data analysis

Research Project

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Project/Area Number 25420437
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Control engineering/System engineering
Research InstitutionKyoto University

Principal Investigator

Fujimoto Kenji  京都大学, 工学研究科, 教授 (10293903)

Project Period (FY) 2013-04-01 – 2017-03-31
KeywordsControl theory / System identification / Statistical learning / Nonlinear control
Outline of Final Research Achievements

This research program mainly achieves three major results by applying statistical learning algorithms to some problems in control engineering. One is system identification for transfer functions and state space models based on variational Bayes. Another one is active learning for system identification based on frequency weighted mutual information. The last one is to use Gaussian process inference for nonlinear controller design. In control engineering, most of the design procedures are based on a mathematical model of the plant system. However, it is not so easy to obtain precise mathematical models in practice. The scope of this research program is to derive a new design algorithms based on statistical learning theory which were not used in control engineering research area so far.

Free Research Field

Control theory

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Published: 2018-03-22  

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