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Set stabilization of boolean networks via sampled‐data control
Author(s) -
Sun Liangjie,
Lu Jianquan,
Lou Jungang,
Li Lulu
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.2114
Subject(s) - set (abstract data type) , state (computer science) , state space , invariant (physics) , boolean network , control (management) , control theory (sociology) , mathematics , computer science , boolean function , discrete mathematics , algorithm , artificial intelligence , statistics , mathematical physics , programming language
The paper investigates the sampled‐data state feedback control (SDSFC) for set stabilization of Boolean control networks (BCNs). Set stabilization means that a system converges to a subset of the state space under certain controllers. Assume that the given subset is M , where | M | = q and sampling period is τ . We consider two conditions q ≤ τ ; q > τ and for any given subset M , calculate the corresponding largest control invariant subset (LCIS). Moreover, a design procedure to calculate all possible SDSFCs for set stabilization of BCNs is obtained. Ultimately, we provide an example to demonstrate the efficiency of the results.