MODELLING OF CYBER-PHYSICAL CONTROL SYSTEMS UNDER NEGATIVE EXTERNAL FACTORS

Abstract

The effective modeling of cyber-physical control systems (CPCS) under negative external factors is critical for ensuring their reliability and stability. This paper provides a comprehensive analysis of the modeling approaches used to assess the impact of various external influences, such as environmental conditions, technical failures, and human factors, on the performance of these systems. The study emphasizes the importance of understanding how these factors can lead to significant disruptions in the operation of CPCS, potentially resulting in severe consequences for critical infrastructures.

The research investigates different modeling methodologies, including mathematical models and simulation techniques, to evaluate the dynamics of CPCS in the presence of adverse conditions. Specifically, the paper discusses the application of Markov models to describe the system's states and transition probabilities, allowing for a detailed assessment of the likelihood of component failures. Additionally, the use of Monte Carlo simulations is explored as a means to generate various scenarios that account for external influences on system behavior.

Moreover, the paper highlights the role of monitoring and control technologies, such as IoT and real-time data analytics, in enhancing the resilience of CPCS. These technologies facilitate continuous monitoring of system components, enabling proactive measures to mitigate the effects of negative external factors. The findings indicate that organizations implementing robust monitoring systems can significantly improve their responsiveness and adaptability to changing conditions.

Furthermore, the study provides practical recommendations for designing resilient CPCS that can withstand external impacts. These include integrating advanced information technologies, optimizing data processing methods, and ensuring data security to protect against cyber threats. By adopting these strategies, organizations can enhance the operational efficiency of their systems while minimizing risks associated with external disruptions.

The results of this research contribute to the understanding of how to effectively model and manage cyber-physical control systems in challenging environments. This work serves as a foundation for future studies aimed at improving the robustness and reliability of CPCS, ultimately leading to more secure and efficient operations in various industries.