Industrial control system

Summary

An industrial control system (ICS) is an electronic control system and associated instrumentation used for industrial process control. Control systems can range in size from a few modular panel-mounted controllers to large interconnected and interactive distributed control systems (DCSs) with many thousands of field connections. Control systems receive data from remote sensors measuring process variables (PVs), compare the collected data with desired setpoints (SPs), and derive command functions that are used to control a process through the final control elements (FCEs), such as control valves. Larger systems are usually implemented by supervisory control and data acquisition (SCADA) systems, or DCSs, and programmable logic controllers (PLCs), though SCADA and PLC systems are scalable down to small systems with few control loops. Such systems are extensively used in industries such as chemical processing, pulp and paper manufacture, power generation, oil and gas processing, and tel

Official source

https://en.wikipedia.org/wiki/Industrial_control_system

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (46)

Related publications

Related people (5)

Related people

Related units (3)

Related units

Related concepts (11)

Related concepts

Related courses (5)

Related courses

Related lectures (13)

Related lectures

Modelling and monitoring industrial automation systems

Rodrigo Garcia Garcia

The modelling of a manufacturing enterprise is not an easy task. A manufacturing enterprise is a complex system where technical knowledge is as important as management abilities. For taking more accurate management decisions and for these decisions to have a quick impact on manufacturing activities, the communication between the higher and lower levels of an enterprise must be fluent. The fluent communication of the different levels of an enterprise is called integration. When this integration is achieved thanks to the use of computers, it is called Computer Integrated Manufacturing (CIM). In the first part of this work, we study the methodologies that have been developed for enterprise modelling and integration and we propose a new functional analysis technique based on the combination of certain elements of the studied methodologies. The second part of this work deals with low level communication aspects of distributed control systems and shows how to use SFCs for determining the state of graphical components and for composite event detection.

EPFL2006

Online Stream Mining for Condition Monitoring in Large Infrastructure Systems

Nils Robin Bouchardon

Supervisory Control and Data Acquisition (SCADA) systems are nowadays widely used in modern industry. Their utility has been proven over the past decades to supervise any automated processes. The scope of applications of such a system has been extended from industrial to infrastructure and facility processes. Classic SCADA systems offer tools to help monitoring and analyzing data from this type of systems, but the existing approaches are often limited to Data Warehousing and Reporting. The main problem of these solutions is that they are not designed to work on online mode and can be seen as batch processing on archived data. In this thesis we study how to link machine learning solutions to SCADA systems on large infrastructures. The solution we propose in this work is a complete framework with its architecture providing a ’toolkit’ with different modules to build online solutions on top of a SCADA system.

2015

, ,

Programmable Logic Controllers (PLCs) are embedded computers widely used in industrial control systems. Ensuring that a PLC software complies with its specification is a challenging task. Formal verification has become a recommended practice to ensure the correctness of safety-critical software but is still underused in industry due to the complexity of building and managing formal models of real applications. In this paper, we propose a general methodology to perform automated model checking of complex properties expressed in temporal logics (e.g., CTL, LTL) on PLC programs. This methodology is based on an Intermediate Model (IM), meant to transform PLC programs written in various standard languages (ST, SFC, etc.) to different modeling languages of verification tools. We present the syntax and semantics of the IM and the transformation rules of the ST and SFC languages to the nuXmv model checker passing through the intermediate model. Finally, two real cases studies of CERN PLC programs, written mainly in the ST language, are presented to illustrate and validate the proposed approach.

Institute of Electrical and Electronics Engineers2015