Model-Free Adaptive Resilient Control for Nonlinear CPSs With Aperiodic Jamming Attacks.

Area of Science:

• Control Theory
• Cyber-Physical Systems Security
• Adaptive Control

Background:

• Nonlinear cyber-physical systems (CPSs) are vulnerable to aperiodic jamming attacks.
• Existing model-free adaptive resilient control (MFARC) methods face challenges with unavailable parameters and attack mitigation.

Purpose of the Study:

• To develop an MFARC framework for nonlinear CPSs under aperiodic jamming attacks.
• To enhance system resilience and tracking performance despite external disturbances.

Main Methods:

• Established an MFARC framework incorporating an intermediate variable method to handle unavailable parameters.
• Devised a tracking control scheme by transforming the problem into a feasibility problem solvable via linear matrix inequality (LMI).
• Developed a novel attack compensation mechanism to counteract jamming impacts.

Main Results:

• Successfully established an MFARC framework for nonlinear CPSs under aperiodic jamming attacks.
• The proposed scheme effectively transforms tracking control into a solvable feasibility problem using LMIs.
• A novel attack compensation mechanism was developed and validated.

Conclusions:

• The devised MFARC scheme effectively addresses nonlinear CPSs subjected to aperiodic jamming attacks.
• The intermediate variable method and LMI-based approach ensure controller parameter acquisition and tracking performance.
• The novel attack compensation mechanism significantly mitigates the impact of jamming attacks, demonstrating the scheme's effectiveness.