The Process Control System and Its Elements: Distributed Control Systems

2007 ◽  
pp. 217-261
1997 ◽  
Vol 30 (12) ◽  
pp. 293-298
Author(s):  
Lim Peng Hun ◽  
Philip Chin Sim Moo ◽  
Yang Zhizong ◽  
Pee Suat Hoon ◽  
Lim Jin Choon

Vestnik MEI ◽  
2021 ◽  
Vol 3 (3) ◽  
pp. 78-87
Author(s):  
Edik K. Arakelyan ◽  
◽  
Ivan A. Shcherbatov ◽  

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.


1991 ◽  
Vol 01 (03) ◽  
pp. 303-326
Author(s):  
PETER P.K. CHIU ◽  
Y.S. CHEUNG

A new methodology for the specification of process control systems involving time interval information and verification of their design is proposed. The specification is based on interval logic and a time-interval operator is defined. By means of this operator, time interval information is incorporated in the specification. Thus properties that involve time intervals can be verified. Moreover, combinational and sequential processes can be specified. An application example for a process control system is demonstrated.


2019 ◽  
Vol 287 ◽  
pp. 08002
Author(s):  
Nina G. Nikolova

In the present work, the application of repetitive filters in the robust process control systems is examined. The functionality of the proposed system and the improved performance, robust performance and filtering properties has been proven.


Author(s):  
Mikhail Yurievich Gudkov ◽  
Alexey Sergeyevich Dobrynin ◽  
Alexander Sergeyevich Koynov

The article considers the problem of the modern automated control systems which operate in the difficult conditions of constantly changing multi-factorial effects of the environment. Such systems should be considered as multi-mode, non-stationary human-technical systems, since they realize the integrated management of a complex technological object. As a rule, these systems are influenced by both environmental factors and complex man-machine mechanisms and technical means (such as communication devices with an object, programmable controllers - PLC), which constitute the control infrastructure, which ultimately leads to additional complexity and errors, additional management problems and reduced overall management quality. The approach to building an automated process control system is claimed to be based on using reference libraries and control algorithms (precedents), which are selected depending on the changing environmental conditions and the assets used, as well as on the logistics support. Despite the use of modern software and hardware in many systems, such as PLC, very often the quality of control leaves much to be desired. This is due to the fact that the control object changes over time for various reasons, and the control algorithm remains unchanged, which leads to a decrease in the efficiency of functioning of such systems. The generalized structure of the precedent process control system is described, which highlights the approach to the control of a technological object within the framework of the well-known concept of support-disturbed movement, which is suitable for building robust control systems for technological objects with substantial nonstationarity.


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