摘要：As the basis of modern control theory, state variables are widely used to describe and analyze the internal characteristics of the system, and the optimal state estimation algorithm is the key. Based on the idea that weighted average can smooth errors, this paper proposes an optimal state estimation method based on convex combination, and analyzes its effectiveness from algorithm design, theoretical analysis, and simulation experiments. Firstly, the convex combination of random variables is derived; secondly, the numerically complete equivalence between the optimal estimation based on the convex combination of random variables and likelihood estimation is analyzed; finally, the equivalence between the optimal state estimation method based on convex combination and the classical univariate Kalman filter algorithm is proved.
© 2020 IEEE.

卷、期、页：p6376-6381

发表日期：2020-11-06

收录情况：EI（工程索引）

发表期刊名称：Proceedings - 2020 Chinese Automation Congress, CAC 2020

通讯作者：葛晓露

第一作者：岳元龙,左信,姜珊

论文类型：会议论文

论文概要：岳元龙,葛晓露,左信,姜珊，Optimal State Estimation Method Based on Convex Combination，Proceedings - 2020 Chinese Automation Congress, CAC 2020，2020，p6376-6381

论文题目：Optimal State Estimation Method Based on Convex Combination