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Distributed semi‐cooperative filter for a nonlinear multi‐agent system with heterogeneous and homologous unknown inputs
Author(s) -
Liu Changqing,
Xu Yuan,
Li Juan,
Tuo Jianyong
Publication year - 2020
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.23837
Subject(s) - filter (signal processing) , control theory (sociology) , residual , kalman filter , nonlinear system , extended kalman filter , nonlinear filter , computer science , homologous chromosome , multi agent system , generator (circuit theory) , filter design , algorithm , artificial intelligence , control (management) , power (physics) , chemistry , physics , quantum mechanics , computer vision , gene , biochemistry
In this study, the simultaneous estimation of the states and unknown inputs for a nonlinear multi‐agent system with homologous and heterogeneous unknown inputs is performed. The decentralized sub‐filter is used to estimate the states and heterogeneous unknown inputs, whereas the distributed sub‐filter is used to estimate the homologous unknown inputs. The extended Kalman filter is used to solve the estimation problem for nonlinear systems. Compared with previous studies, the distributed solution is improved to relax the existence of the homologous unknown input sub‐filter. Moreover, the updating method of the residual generator is improved to relax the heterogeneous unknown input sub‐filter. The practical problem of estimating the state of charge and temperature of the battery pack is used to verify the effectiveness of the proposed filter.