Output feedback control for set stabilization of Boolean control networks

Rongjian Liu; Jianquan Lu; Wei Xing Zheng; Jurgen Kurths

doi:10.1109/TNNLS.2019.2928028

Output feedback control for set stabilization of Boolean control networks

Rongjian Liu, Jianquan Lu, Wei Xing Zheng, Jurgen Kurths

Western Sydney University

Research output: Contribution to journal › Article › peer-review

32 Citations (Scopus)

Abstract

In this paper, the output feedback set stabilization problem for Boolean control networks (BCNs) is investigated with the help of the semi-tensor product (STP) tool. The concept of output feedback control invariant (OFCI) subset is introduced, and novel methods are developed to obtain the OFCI subsets. Based on the OFCI subsets, a technique, named spanning tree method, is further introduced to calculate all possible output feedback set stabilizers. An example concerning lac operon for the bacterium Escherichia coli is given to illustrate the effectiveness of the proposed method. This technique can also be used to solve the state feedback (set) stabilization problem for BCNs. Compared with the existing results, our method can dramatically reduce the computational cost when designing all possible state feedback stabilizers for BCNs.

Original language	English
Pages (from-to)	2129-2139
Number of pages	11
Journal	IEEE Transactions on Neural Networks and Learning Systems
Volume	31
Issue number	6
DOIs	https://doi.org/10.1109/TNNLS.2019.2928028
Publication status	Published - 2020

Keywords

Boolean matrices
computer networks
input-output analysis
spanning trees (graph theory)

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10.1109/TNNLS.2019.2928028

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T1 - Output feedback control for set stabilization of Boolean control networks

AU - Liu, Rongjian

AU - Lu, Jianquan

AU - Zheng, Wei Xing

AU - Kurths, Jurgen

PY - 2020

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N2 - In this paper, the output feedback set stabilization problem for Boolean control networks (BCNs) is investigated with the help of the semi-tensor product (STP) tool. The concept of output feedback control invariant (OFCI) subset is introduced, and novel methods are developed to obtain the OFCI subsets. Based on the OFCI subsets, a technique, named spanning tree method, is further introduced to calculate all possible output feedback set stabilizers. An example concerning lac operon for the bacterium Escherichia coli is given to illustrate the effectiveness of the proposed method. This technique can also be used to solve the state feedback (set) stabilization problem for BCNs. Compared with the existing results, our method can dramatically reduce the computational cost when designing all possible state feedback stabilizers for BCNs.

AB - In this paper, the output feedback set stabilization problem for Boolean control networks (BCNs) is investigated with the help of the semi-tensor product (STP) tool. The concept of output feedback control invariant (OFCI) subset is introduced, and novel methods are developed to obtain the OFCI subsets. Based on the OFCI subsets, a technique, named spanning tree method, is further introduced to calculate all possible output feedback set stabilizers. An example concerning lac operon for the bacterium Escherichia coli is given to illustrate the effectiveness of the proposed method. This technique can also be used to solve the state feedback (set) stabilization problem for BCNs. Compared with the existing results, our method can dramatically reduce the computational cost when designing all possible state feedback stabilizers for BCNs.

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KW - computer networks

KW - input-output analysis

KW - spanning trees (graph theory)

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DO - 10.1109/TNNLS.2019.2928028

M3 - Article

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EP - 2139

JO - IEEE Transactions on Neural Networks and Learning Systems

JF - IEEE Transactions on Neural Networks and Learning Systems

IS - 6

ER -

Output feedback control for set stabilization of Boolean control networks

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