Dynamics & Design Conference
Online ISSN : 2424-2993
セッションID: 108
会議情報
108 サポートベクター回帰モデルによる倒立振子の学習制御
小林 正幸小西 康夫石垣 博行
著者情報
会議録・要旨集 フリー

詳細
抄録
Support Vector Machines (SVM) are new machine learning methods, and are studied about many applications. However, a regression method of SVM shows little availability. In this paper, we propose a learning control scheme using Support Vector Regression (SVR). This control system consists a pre-learned SVR, and is applied to a control problem of inverted pendulum. SVR system learned input-output data of state feedback control given an initial condition. The computer simulation results show the availability of the proposed control system.
著者関連情報
© 2003 一般社団法人 日本機械学会
前の記事 次の記事
feedback
Top