カテゴリ: 論文誌(論文単位)グループ名: 【D】産業応用部門（英文）発行日: 2016/07/01タイトル(英語): Upper-Bound-Based State Estimation with Large-Time-Delay Measurement and Its Applications to Motion Control著者名: Binh-Minh Nguyen (Department of Information Physics and Computing, the University of Tokyo), Hiroshi Fujimoto (Department of Advanced Energy, the University of Tokyo), Yoichi Hori (Department of Advanced Energy, the University of Tokyo)著者名(英語): Binh-Minh Nguyen (Department of Information Physics and Computing, the University of Tokyo), Hiroshi Fujimoto (Department of Advanced Energy, the University of Tokyo), Yoichi Hori (Department of Advanced Energy, the University of Tokyo)キーワード: state estimation，time-delay，norm-bound要約(英語): In many motion control applications, it is essential to handle a delayed measurement to estimate the unknown states correctly. However, a literature review shows that difficulties still remain if the delay time is quite large in comparison with the period of the control input. For instance, some methods need to increase the size of the original system considerably. This paper describes a novel filter for a linear system with a large-time-delay measurement. By utilizing the norm-bound scheme based on a matrix inequality, the upper-bound of the estimation error covariance is obtained, and the filter gain can be computed easily. The proposed algorithm is almost similar to the standard Kalman filter without any increase in the dimension of the system. The algorithm is developed for two cases: Case 1: considering only a delayed measurement and Case 2: considering the fusion of delayed and nondelayed measurements. Two motion control applications are performed to verify the algorithm: sideslip angle estimation for vehicle motion control and target position estimation for visual servo control.本誌: IEEJ Journal of Industry Applications Vol.5 No.4 （2016）本誌掲載ページ: 303-313 p原稿種別: 論文／英語電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejjia/5/4/5_303/_article/-char/ja/
