On the input‐output decoupling of Boolean control networks by state feedback

Abstract We propose a new state feedback‐based input‐output‐decoupling approach for Boolean control networks. A constructive necessary and sufficient condition, based on some appropriately constructed input‐output‐decoupling matrices, is established for the design of the input‐output‐decoupling state feedback gain. The proposed approach does not rely on the restrictive assumption of the existence of the input‐output decomposed form which is instrumental in the very few existing state‐feedback‐based input‐output‐decoupling approaches in the literature. Finally, a numerical example is provided to illustrate the effectiveness of the proposed approach.

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Publication Details

Journal
Asian Journal of Control
Published
2024-11-19
DOI
https://doi.org/10.1002/asjc.3543
Citations
2
Primary Topic
Gene Regulatory Network Analysis
Type
article
Field-Weighted Citation Impact
0.47

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article

On the input‐output decoupling of Boolean control networks by state feedback

Hongli Lyu, Abdelhamid Tayebi, Jun‐e Feng, Yiliang Li
2 citations
Asian Journal of Control
Gene Regulatory Network Analysis
0.47
article

On the input‐output decoupling of Boolean control networks by state feedback

Hongli Lyu, Abdelhamid Tayebi, Jun‐e Feng, Yiliang Li
article en
2 citations

Abstract

Abstract We propose a new state feedback‐based input‐output‐decoupling approach for Boolean control networks. A constructive necessary and sufficient condition, based on some appropriately constructed input‐output‐decoupling matrices, is established for the design of the input‐output‐decoupling state feedback gain. The proposed approach does not rely on the restrictive assumption of the existence of the input‐output decomposed form which is instrumental in the very few existing state‐feedback‐based input‐output‐decoupling approaches in the literature. Finally, a numerical example is provided to illustrate the effectiveness of the proposed approach.

Asian Journal of ControlVol. 27(4)
Shandong University (CN), Lakehead University (CA)
National Natural Science Foundation of China
Openalex Percentile: Top 34%
Gene Regulatory Network Analysis
0.47
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