Multiple-model adaptive estimation with a new weighting algorithm
type: Item
instance of: scholarly article
title: Multiple-model adaptive estimation with a new weighting algorithm
zbMATH Open document ID: 1398.93327
DOI: 10.1155/2018/4789142
author: Weicun Zhang
author: Yuzhen Zhang
author: Sufang Wang
published in: Complexity
publication date: 2018-09-28T00:00:00Z
review text: Summary: The state estimation of a complex dynamic stochastic system is described by a discrete-time state-space model with large parameter (including the covariance matrices of system noises and measurement noises) uncertainties. A new scheme of weighted multiple-model adaptive estimation is presented, in which the classical weighting algorithm is replaced by a new weighting algorithm to reduce the calculation burden and to relax the convergence conditions. Finally, simulation results verified the effectiveness of the proposed MMAE scheme for each possibility of parameter uncertainties.
Mathematics Subject Classification ID: 93E10
Mathematics Subject Classification ID: 93E03
Mathematics Subject Classification ID: 93C55
Mathematics Subject Classification ID: 93C41
Mathematics Subject Classification ID: 93E25
zbMATH DE Number: 6945219
zbMATH Keywords: state estimation
zbMATH Keywords: complex dynamic stochastic system
zbMATH Keywords: discrete-time state-space model
zbMATH Keywords: uncertainties
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2018/4789142
OpenAlex ID: W2807960766
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description: scientific article; zbMATH DE number 6945219