Robustness improvement for cyber physical system based on an optimization model of interdependent constraints

Area of Science:

• Engineering and Technology
• Computer Science
• Systems Engineering

Background:

• Traditional infrastructure networks are evolving into complex cyber physical systems (CPSs).
• The integration of cyber and physical components introduces new failure modes, impacting system stability and safety.
• Existing models often overlook the critical interdependence between cyber and physical networks.

Purpose of the Study:

• To develop an interdependence-constrained optimization model for enhancing the robustness of cyber physical systems (CPSs).
• To address the limitations of existing models by incorporating both physical laws and cyber-physical interdependencies.
• To provide a computationally efficient method for solving complex CPS robustness optimization problems.

Main Methods:

• Formulation of a novel interdependence-constrained optimization model for CPS robustness.
• Transformation of the nonlinear model into a bi-level mixed integer linear programming (MILP) problem.
• Simulation using standard Institute of Electrical and Electronics Engineers (IEEE) test cases to validate the model's effectiveness.

Main Results:

• The proposed model significantly improves the robustness of cyber physical systems (CPSs).
• Analysis demonstrates the impact of disaster level and coupling strength on system robustness.
• Comparative performance evaluation of power supply in CPSs with varying cyber network structures.

Conclusions:

• The developed optimization model offers an effective solution for enhancing CPS robustness.
• The findings provide valuable insights for system operators to improve CPS resilience post-extreme events.
• The MILP formulation ensures efficient and practical implementation for real-world applications.