Event-Triggered Control for the Disturbance Decoupling Problem of Boolean Control Networks.

Area of Science:

• Control Theory
• Discrete Systems Analysis
• Networked Systems

Background:

• Boolean control networks (BCNs) are discrete dynamical systems widely used in modeling biological and engineered systems.
• The disturbance decoupling problem (DDP) is crucial for ensuring system robustness against external perturbations.
• Event-triggered control offers potential advantages in reducing communication and computation load compared to time-triggered control.

Purpose of the Study:

• To investigate the disturbance decoupling problem (DDP) in Boolean control networks (BCNs) using event-triggered control strategies.
• To develop a systematic method for designing event-triggered controllers that can solve the DDP for BCNs.
• To extend the proposed event-triggered control approach to address the DDP in Boolean partial control networks.

Main Methods:

• Utilizing the semi-tensor product of matrices to transform Boolean control networks into an algebraic framework.
• Designing event-triggered controllers based on the algebraic representation of BCNs to achieve disturbance decoupling.
• Applying the developed methodology to Boolean partial control networks.

Main Results:

• The paper successfully formulates the DDP for BCNs within an algebraic framework.
• Event-triggered controllers are designed to effectively solve the DDP for both standard and partial BCNs.
• The proposed methods are validated through two illustrative examples, demonstrating their practical effectiveness.

Conclusions:

• Event-triggered control provides an effective approach for solving the disturbance decoupling problem in Boolean control networks.
• The semi-tensor product method facilitates the algebraic analysis and controller design for BCNs.
• The study contributes to the advancement of robust control strategies for discrete-time systems.