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Sampled-data stabilization of delayed Boolean control networks with state inequality constraints.

Xiangshan Kong1, Enguo Gu2, Xinyun Liu1

  • 1School of Mathematics and Statistics, Weifang University, Weifang, China.

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|May 21, 2025
PubMed
Summary

This study addresses set stabilization for delayed Boolean control networks (DBCNs) with state inequality constraints using sampled-data control. New criteria and stabilizers are developed for inequality-constrained reachability, verified in a cell apoptosis network model.

Keywords:
Algebraic state space representationDelayed Boolean control networksNonuniform sampled-data controlStabilizationState inequality constraints

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Area of Science:

  • Control Theory
  • Network Science
  • Computational Biology

Background:

  • Delayed Boolean Control Networks (DBCNs) are crucial for modeling complex biological systems.
  • State inequality constraints are essential for realistic system behavior but pose significant challenges in DBCNs.
  • Existing control methods often struggle with incorporating both time delays and state constraints effectively.

Purpose of the Study:

  • To develop novel set stabilization strategies for DBCNs with state inequality constraints.
  • To introduce time-variant nonuniform sampled-data control for enhanced network management.
  • To establish new criteria for inequality-constrained reachability in delayed networks.

Main Methods:

  • Utilized algebraic state space representation to derive equivalent algebraic forms of DBCNs.
  • Constructed an inequality constrained controllability matrix to analyze system reachability.
  • Developed time-variant nonuniform sampled-data stabilizers based on derived reachability criteria.

Main Results:

  • Proposed new criteria for nonuniform sampled-data inequality constrained reachability in DBCNs.
  • Successfully designed time-variant nonuniform sampled-data stabilizers.
  • Demonstrated the effectiveness of the proposed methods using a cell apoptosis network model.

Conclusions:

  • The developed methods provide a robust framework for set stabilization of DBCNs under state inequality constraints.
  • Time-variant nonuniform sampled-data control is effective for managing delayed networks with constraints.
  • The findings have implications for the control and analysis of complex biological networks.