Moving horizon estimation meets multi-sensor information fusion: Development, opportunities and challenges

被引：49
|
作者：
Zou, Lei [1 ]
Wang, Zidong [1 ,2 ]
Hu, Jun [3 ]
Han, Qing-Long [4 ]
机构：
[1] Brunel Univ London, Dept Comp Sci, Uxbridge UB8 3PH, Middx, England
[2] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China
[3] Harbin Univ Sci & Technol, Sch Sci, Harbin 150080, Heilongjiang, Peoples R China
[4] Swinburne Univ Technol, Sch Software & Elect Engn, Melbourne, Vic 3122, Australia
来源：
INFORMATION FUSION | 2020年 / 60卷
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Moving horizon estimation; State estimation; Filtering; Dynamical systems; Performance analysis; Multi-sensor information fusion; NETWORKED CONTROL-SYSTEMS; DISCRETE-TIME-SYSTEMS; CONSTRAINED STATE ESTIMATION; NONLINEAR-SYSTEMS; MULTIRATE SYSTEMS; LINEAR-SYSTEMS; ARRIVAL COST; ATTITUDE ESTIMATION; PREDICTIVE CONTROL; VARYING SYSTEMS;
D O I：
10.1016/j.inffus.2020.01.009
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Since the proposal of moving horizon (MH) estimation in 1960s, the MH estimation approach has drawn ever-increasing research interests due mainly to its inherent capability of handling complex nonlinear systems and constrained systems. Recent years have witnessed considerable progress on the theoretical and practical research of MH estimation. In this work, a bibliographical review is provided on the moving horizon estimation problem and its applications. The basic idea of MH estimation is first introduced in detail. Then recent advances of MH estimation according to the underlying systems are summarized. Furthermore, some applications of MH estimation are presented. Finally, some research challenges of MH estimation problem are outlined for the further research.
引用
收藏
页码：1 / 10
页数：10
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