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An improved multiple‐state observer of Boolean control networks
Author(s) -
Yang Junqi,
Gao Zihan,
Li Zhiqiang,
Qian Wei
Publication year - 2019
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2256
Subject(s) - observer (physics) , state (computer science) , state observer , control theory (sociology) , computer science , control (management) , boolean network , logical matrix , alpha beta filter , boolean function , matrix (chemical analysis) , mathematics , algorithm , artificial intelligence , moving horizon estimation , kalman filter , group (periodic table) , nonlinear system , chemistry , physics , organic chemistry , quantum mechanics , extended kalman filter , materials science , composite material
This paper explores the issue of state estimation for Boolean control networks (BCNs), and a kind of improved multiple‐state observer is proposed. The improved multiple‐state observer can be described by means of a specific BCN that overcomes the difficulty of the existing multiple state observers where it is difficult to find a general expression for the observer gain matrix. Next, based on the states that can possibly generate the output and those that are observed by the designed observer in current time step, an adaptive algorithm that completes the design of the multiple‐state observer is provided to update the observer states, and which makes the state estimation of Boolean control networks feasible. Finally, an example is presented to illustrate the effectiveness of the obtained results.