Highly computationally efficient state filter based on the delta operator

Zhang, Xiao and Ding, Feng and Xu, Ling and Yang, Erfu (2019) Highly computationally efficient state filter based on the delta operator. International Journal of Adaptive Control and Signal Processing, 33 (6). pp. 875-889. ISSN 0890-6327 (https://doi.org/10.1002/acs.2995)

[thumbnail of Zhang-etal-IJACSP-2019-Highly-computationally-efficient-state-filter-based-on-the-delta-operator]
Preview
 Text. Filename: Zhang_etal_IJACSP_2019_Highly_computationally_efficient_state_filter_based_on_the_delta_operator.pdf
Accepted Author Manuscript
Download (555kB)| Preview

Abstract

The Kalman filter is not suitable for the state estimation of linear systems with multistate delays, and the extended state vector Kalman filtering algorithm results in heavy computational burden because of the large dimension of the state estimation covariance matrix. Thus, in this paper, we develop a novel state estimation algorithm for enhancing the computational efficiency based on the delta operator. The computation analysis and the simulation example show the performance of the proposed algorithm.

ORCID iDs

Zhang, Xiao, Ding, Feng, Xu, Ling and Yang, Erfu ORCID logoORCID: https://orcid.org/0000-0003-1813-5950;
CORE (COnnecting REpositories)