Journal of Process Control

A journal of IFAC, the International Federation of Automatic Control

Journal of Process Control - ISSN 0959-1524
Source Normalized Impact per Paper (SNIP): 2.241 Source Normalized Impact per Paper (SNIP):
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 1.21 SCImago Journal Rank (SJR):
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Impact Factor: 2.7 (2016) Impact Factor:
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
5 Year Impact Factor: 3.116 (2016) Five-Year Impact Factor:
To calculate the five year Impact Factor, citations are counted in 2016 to the previous five years and divided by the source items published in the previous five years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
Volumes: Volumes 61-72
Issues: 12 issues
ISSN: 09591524

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Description

This international journal covers the application of control theory, operations research, computer science and engineering principles to the solution of process control problems. In addition to the traditional chemical processing and manufacturing applications, the scope of process control problems involves a wide range of applications that includes energy processes, nano-technology, systems biology, bio-medical engineering, pharmaceutical processing technology, energy storage and conversion, smart grid, and data analytics among others.



Papers on the theory in these areas will also be accepted provided the theoretical contribution is aimed at the application and the development of process control techniques.



Topics covered include:



• Control applications

• Process monitoring

• Plant-wide control

• Process control systems

• Control techniques and algorithms

• Process modelling and simulation

• Design methods



Advanced design methods exclude well established and widely studied traditional design techniques such as PID tuning and its many variants. Applications in fields such as control of automotive engines, machinery and robotics are not deemed suitable unless a clear motivation for the relevance to process control is provided.



For more details on the International Federation of Automatic Control (IFAC), access their home page.