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.

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

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

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.

Safety and Security in SCADA Systems Must be Improved through Resilience Based Risk Management

2013 ◽  
pp. 1422-1436
Author(s):  
Stig O. Johnsen
Keyword(s):  
Risk Management ◽  
Best Practices ◽  
Process Control ◽  
Control Systems ◽  
Knowledge Generation ◽  
Continuity Of Operations ◽  
Process Control Systems ◽  
Industrial Setting ◽  
Scada Systems ◽  
Distributed Process

This chapter describes vulnerabilities related to safety and security in distributed process control systems integrated with information and communication technology (ICT). The author describe key vulnerabilities and how to mitigate these vulnerabilities by current best practices, which have worked in an industrial setting in Norway. Distributed process control systems are denoted as SCADA systems, i.e. supervisory control and data acquisition systems. Increased networking and increased use of ICT impacts the complexity and vulnerability of the SCADA systems. To improve safety and security, there must be a focus on systematic knowledge generation between ICT and process experts and a focus on exploring resilience as a strategy to manage risks and support continuity of operations (resilience seen as the ability to bounce back and sustain operations). Best practices in risk management in this area are to establish policies, improve risk awareness, perform risk assessment in collaboration between ICT and SCADA professionals, focus on segregation of networks, focus on active protection against malicious software, improve reporting and sharing of incidents, and establish and explore disaster/recovery plans. In addition, there should be focus on certification and testing of components in ICT and SCADA systems and improvement of resilience to mitigate uncertainty and complexity.

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