Security Control for a Fuzzy System under Dynamic Protocols and Cyber-Attacks with Engineering Applications

The objective of this study is to design a security control for ensuring the stability of systems, maintaining their state within bounded limits and securing operations. Thus, we enhance the reliability and resilience in control systems for critical infrastructure such as manufacturing, network band...

Full description

Saved in:
Bibliographic Details
Published in:Mathematics (Basel) 2024-07, Vol.12 (13), p.2112
Main Authors: Kchaou, Mourad, Castro, Cecilia, Abbassi, Rabeh, Leiva, Víctor, Jerbi, Houssem
Format: Article
Language:English
Subjects:
Algorithms
Automation
Bandwidths
Communication
Control stability
Control systems design
Controllers
Cost control
Critical infrastructure
Cybersecurity
Data transmission
Deception
dynamic event-triggering mechanism
Efficiency
Fault tolerance
Fractional calculus
Fuzzy control
Fuzzy logic
Fuzzy systems
interval type-2 fuzzy logic
Markov jump systems
MATLAB software
Network reliability
Network security
Random variables
Real time operation
Resilience
Robust control
singularly perturbed systems
Stability
System effectiveness
System reliability
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The objective of this study is to design a security control for ensuring the stability of systems, maintaining their state within bounded limits and securing operations. Thus, we enhance the reliability and resilience in control systems for critical infrastructure such as manufacturing, network bandwidth constraints, power grids, and transportation amid increasing cyber-threats. These systems operate as singularly perturbed structures with variables changing at different time scales, leading to complexities such as stiffness and parasitic parameters. To manage these complexities, we integrate type-2 fuzzy logic with Markov jumps in dynamic event-triggered protocols. These protocols handle communications, optimizing network resources and improving security by adjusting triggering thresholds in real-time based on system operational states. Incorporating fractional calculus into control algorithms enhances the modeling of memory properties in physical systems. Numerical studies validate the effectiveness of our proposal, demonstrating a 20% reduction in network load and enhanced stochastic stability under varying conditions and cyber-threats. This innovative proposal enables real-time adaptation to changing conditions and robust handling of uncertainties, setting it apart from traditional control strategies by offering a higher level of reliability and resilience. Our methodology shows potential for broader application in improving critical infrastructure systems.
ISSN:2227-7390
2227-7390
DOI:10.3390/math12132112