Open AccessDistributed estimation of non‐linear functions of the state vector for multisensory continuous‐time linear systems
Author(s) -
Song II Young,
Shin Vladimir,
Lee Seokhyoung,
Choi Won
Publication year - 2015
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2013.0254
Subject(s) - state vector , state (computer science) , estimation , computer science , linear system , control theory (sociology) , mathematics , algorithm , artificial intelligence , engineering , physics , mathematical analysis , control (management) , systems engineering , classical mechanics
This study focuses on fusion algorithms for the estimation of a non‐linear function of the state vector in a multisensory continuous‐time stochastic system. The non‐linear function of the state (NFS) represents a non‐linear multivariate function of state variables, which can indicate useful information of a target system for control. To estimate a NFS using multisensory information, they propose one centralised and three distributed estimation fusion algorithms. For multivariate polynomial functions, they derive a closed‐form estimation procedure. In the general case, an unscented transformation is used for evaluation of the fusion estimate of an NFS. The subsequent application of the proposed fusion estimators to a linear stochastic system within a multisensor environment demonstrates their effectiveness.