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A modified particle filter for parameter identification with unknown inputs
Author(s) -
Wan Zhimin,
Wang Ting,
Li Shande,
Zhang Zhifu
Publication year - 2018
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.2268
Subject(s) - particle filter , nonlinear system , identification (biology) , excitation , filter (signal processing) , particle (ecology) , algorithm , control theory (sociology) , computer science , mathematics , engineering , physics , artificial intelligence , oceanography , botany , control (management) , geology , computer vision , biology , quantum mechanics , electrical engineering
Summary Particle filter (PF) is usually used for identifying structural parameters in nonlinear systems. However, the traditional PF method requires that all the external excitations are available or can be measured, which may not be the case for many structures. In this paper, a modified PF method with unknown inputs, referred to as PF‐UI, is proposed to identify the augmented states, including structural states and parameters, as well as the unknown excitation inputs. The augmented states are identified by the traditional PF algorithm, and the unknown excitations are simultaneous identified with the least‐square algorithm. Such an analytical solution for PF‐UI is not available in the previous literature. Numerical studies of two typical nonlinear systems are conducted to demonstrate that the proposed approach is capable of identifying the states and parameters with unknown excitation inputs.