Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time Systems

We propose two new multisensory fusion predictors for an arbitrary nonlinear function of the state vector in a discrete-time linear dynamic system. Nonlinear function of the state (NFS) represents a nonlinear multivariate functional of state variables, which can indicate useful information of the ta...

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Main Authors: Ha Ryong Song, Il Young Song, Vladimir Shin
Format: Article
Language:English
Published: Wiley 2015-11-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2015/249857
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author Ha Ryong Song
Il Young Song
Vladimir Shin
author_facet Ha Ryong Song
Il Young Song
Vladimir Shin
author_sort Ha Ryong Song
collection DOAJ
description We propose two new multisensory fusion predictors for an arbitrary nonlinear function of the state vector in a discrete-time linear dynamic system. Nonlinear function of the state (NFS) represents a nonlinear multivariate functional of state variables, which can indicate useful information of the target system for automatic control. To estimate the NFS using multisensory information, we propose centralized and decentralized predictors. For multivariate polynomial NFS, we propose an effective closed-form computation procedure for the predictor design. For general NFS, the most popular procedure for the predictor design is based on the unscented transformation. We demonstrate the effectiveness and estimation accuracy of the fusion predictors on theoretical and numerical examples in multisensory environment.
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series International Journal of Distributed Sensor Networks
spelling doaj-art-fe33a565641d450a9646ce3d2927ee3a2025-08-20T03:25:47ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-11-011110.1155/2015/249857249857Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time SystemsHa Ryong Song0Il Young Song1Vladimir Shin2 Flight Safety Technology Division, Korea Aerospace Research Institute, 169-84 Gwahangno, Yuseong-gu, Daejeon 305-806, Republic of Korea Department of Sensor Systems, Hanwha Corporation R&D Center, 52-1 Oesam-dong, Yuseong-gu, Daejeon 305-106, Republic of Korea Department of Information and Statistics, Research Institute of Natural Science, Gyeongsang National University, 501 Jinjudaero, Jinju, Gyeongsangnam-do 660-701, Republic of KoreaWe propose two new multisensory fusion predictors for an arbitrary nonlinear function of the state vector in a discrete-time linear dynamic system. Nonlinear function of the state (NFS) represents a nonlinear multivariate functional of state variables, which can indicate useful information of the target system for automatic control. To estimate the NFS using multisensory information, we propose centralized and decentralized predictors. For multivariate polynomial NFS, we propose an effective closed-form computation procedure for the predictor design. For general NFS, the most popular procedure for the predictor design is based on the unscented transformation. We demonstrate the effectiveness and estimation accuracy of the fusion predictors on theoretical and numerical examples in multisensory environment.https://doi.org/10.1155/2015/249857
spellingShingle Ha Ryong Song
Il Young Song
Vladimir Shin
Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time Systems
International Journal of Distributed Sensor Networks
title Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time Systems
title_full Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time Systems
title_fullStr Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time Systems
title_full_unstemmed Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time Systems
title_short Multisensory Prediction Fusion of Nonlinear Functions of the State Vector in Discrete-Time Systems
title_sort multisensory prediction fusion of nonlinear functions of the state vector in discrete time systems
url https://doi.org/10.1155/2015/249857
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AT vladimirshin multisensorypredictionfusionofnonlinearfunctionsofthestatevectorindiscretetimesystems