Title
Set Stabilization of Probabilistic Boolean Control Networks: A Sampled-Data Control Approach.
Abstract
This article investigates the set stabilization of probabilistic Boolean control networks (PBCNs) under sampled-data (SD) state-feedback control within finite and infinite time, respectively. First, the algorithms are, respectively, proposed to find the sampled point set and the largest sampled point control invariant set (SPCIS) of PBCNs by SD state-feedback control. Based on this, a necessary and sufficient criterion is proposed for the global set stabilization of PBCNs by SD state-feedback control within finite time. Moreover, the time-optimal SD state-feedback controller is designed. It is interesting that if the sampled period (SP) is changed, the time of global set stabilization of PBCNs may also change or even the PBCNs cannot achieve set stabilization. Second, a criterion for the global set stabilization of PBCNs by SD state-feedback control within infinite time is obtained. Furthermore, all possible SD state-feedback controllers are obtained by using all the complete families of reachable sets. Finally, three examples are presented to illustrate the effectiveness of the obtained results.
Year
DOI
Venue
2020
10.1109/TCYB.2019.2940654
IEEE Transactions on Cybernetics
Keywords
DocType
Volume
Probabilistic logic,Switches,Feedback control,Stability criteria,Adaptive control
Journal
50
Issue
ISSN
Citations 
8
2168-2267
2
PageRank 
References 
Authors
0.36
28
5
Name
Order
Citations
PageRank
Mengxia Xu120.36
Yang Liu255132.55
jungang lou318417.24
Zhengguang Wu43550137.72
Jie Zhong517114.53