Analysis of Cybersecurity Requirements of Automated Process Control Systems As Critical Information Infrastructure

2021 ◽  
Vol 43 (4) ◽  
pp. 103-112
Author(s):  
O. Bakalynskyi ◽  
◽  
D. Pakholchenko ◽  
Keyword(s):  
Process Control ◽  
Control Systems ◽  
Cyber Security ◽  
Information Infrastructure ◽  
Automated Control ◽  
Critical Information ◽  
Technological Processes ◽  
Process Control Systems ◽  
Automated Process

The analysis of the current legislation and the best world practices on cyber protection of automated control systems of technological processes in which requirements for realization of cyber protection of objects of critical information infrastructure are offered is carried out. Problematic issues related to cyber security of critical information infrastructure objects are given.

scholarly journals Directions for Improving Apcs in the Oil and Gas Production Industry

2021 ◽  
Vol 19 (3) ◽  
pp. 25-34
Author(s):  
S. G. Mukhametdinova ◽  
◽  
A. I. Korshunov ◽  
N. O. Vakhrusheva ◽  
◽  
...  
Keyword(s):  
Big Data ◽  
Process Control ◽  
Control Systems ◽  
Oil And Gas ◽  
Gas Production ◽  
Digital Transformation ◽  
Automated Control ◽  
Oil And Gas Production ◽  
Process Control Systems ◽  
Automated Process

The paper discusses automated control systems for technological processes (APCS) of oil and gas producing enterprises of the Russian Federation. The history of the development of automated process control systems in oil and gas production is described. At the moment, the efficient operation of technological facilities is not possible without the use of automated control systems. Special attention should be paid to the fact that almost all oil production facilities are currently characterized by a high level of depletion and are mainly at the late (third or fourth) stages of operation. Under these conditions, the average production rate falls, the costs of technological procedures for oil and gas production increase significantly. In this regard, in the current conditions, the effective development of process control systems for oil and gas enterprises is an extremely urgent task. The paper provides a typical block diagram and classification of automated systems that provide control of technological processes in oil and gas production. The necessity of using an automated dispatch control system (ADCS) is substantiated and its main tasks are considered. The need for an automated process control system in oil and gas production to reach the next level of functional development, which can be provided by modern automation and communication means, is clearly demonstrated, thereby giving a new impetus to the digital transformation process. The concept of "smart" well is considered, comparative characteristics of different levels of oil fields are presented: standard, digital and intelligent. The concepts of big data (Big Data), cloud technologies (Cloud Storage), augmented reality are considered in relation to the specifics of the industry. A qualitative assessment of the readiness and development prospects of the APCS in the context of the transition to digital technologies in oil and gas production is carried out. The digital transformation of the industry must be economically substantiated and justified.

DETERMINATION OF THE JUICE EVAPORATION MATHEMATICAL MODELS EFFICIENCY FOR AUTOMATED PROCESS CONTROL SYSTEMS

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
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◽  
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...  
Keyword(s):  
Process Control ◽  
Mathematical Models ◽  
Control Systems ◽  
Process Control Systems ◽  
Automated Process

APPLICATION OF INTERNET ARCHITECTURE IN CENTRALIZED AUTOMATED PROCESS CONTROL SYSTEMS

2021 ◽  
pp. 3-6
Author(s):  
D. Vasilchenko ◽  
A. Budilovskaya
Keyword(s):  
Process Control ◽  
Control Systems ◽  
Centralized Control ◽  
Distributed Objects ◽  
Internet Architecture ◽  
Process Control Systems ◽  
Scada Systems ◽  
Geographically Distributed ◽  
Automated Process ◽  
Use Of Internet

This article discusses the use of Internet architecture in centralized automated process control systems for the purpose of monitoring and managing geographically distributed objects. The hardware components of the proposed architecture are described and the required functions are formulated. The methods of implementing these functions of centralized control systems based on this architecture are proposed: using internal algorithms of SCADA systems, or using microprocessor subsystems. The difficulties that are likely to be encountered when implementing all the required functions in the system being developed are described.

Reducing the Impact of Source Information Uncertainty in Intelligent Automated Thermal Process Control Systems in Ensuring Reliable Operation of Power Equipment

Vestnik MEI ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 78-87
Author(s):  
Edik K. Arakelyan ◽  
◽  
Ivan A. Shcherbatov ◽  
Keyword(s):  
Control System ◽  
Process Control ◽  
Control Systems ◽  
Process Control System ◽  
Power Equipment ◽  
Source Information ◽  
Equipment Operation ◽  
Process Control Systems ◽  
Automated Process ◽  
The Impact

The uncertainty of the source information is used to solve key tasks in an intelligent automated thermal process control system affects the calculation of control actions, the implementation of equipment optimal operating modes and, as a result, leads to degraded reliability. As a rule, this type of information can be qualitative (the use of expert knowledge) or quantitative in nature. In this regard, it is extremely important to reduce the impact of uncertainty. The aim of the study is to identify the types and origins of uncertainty in the source information used by an intelligent automated process control system and to develop approaches to reduce its impact on the reliability of power equipment operation. The approaches used to ensure the specified indicators of reliability, efficiency and environmental friendliness in modern intelligent automated process control systems are based on predictive strategies, according to which the technical condition of equipment and specific degradation processes are predicted. This means that various types of uncertainty can have a significant negative impact. To reduce the influence of uncertainty of the initial information that affects the reliability of power equipment operation, the use of artificial neural networks is proposed. Their application opens the possibility to predict the occurrence of equipment defects and failures based on retrospective data for specified forecast time intervals. A method for reducing the impact of anomalies contained in the source information used in an intelligent process control system for energy facilities is demonstrated. Data omissions and outliers are investigated, the elimination of which reduces the impact of uncertainty and improves the quality of solving key problems in intelligent automated process control systems. Experimental studies were carried out that made it possible to identify the mathematical methods for removing omissions and anomalies in the source information in the best way. Methodological aspects of eliminating various types of uncertainty that exist in managing of power facilities by means of intelligent automated process control systems at the key stages of the power equipment life cycle are described.

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