RE-ENGINEERED CONTROL SYSTEM IMPLEMENTATION PHILOSOPHY (RCSIP): A TESTED APPROACH TO INDUSTRIAL CONTROL SYSTEM DESIGN FOR OPTIMAL SECURITY IN CLOUD-BASED APPLICATIONS

This article explicitly explains how to design industrial control systems for optimal security in cloud-based applications. It is a step by step article to understanding and building control systems.
Re engineered Control System Implementation Philosophy

Article Contents
•    The elementary meaning of control system.
•    The problems inherent in the existing industrial control system automation architecture (ICSAA).
•    The Solution Philosophy.
•    Solution integration with ICSAA
•    Solution integration with cloud based applications(CBAs)
•    Conclusion
•    Q & A



Click the link to download the PDF copy of  this article for free: RE-ENGINEERED CONTROL SYSTEM IMPLEMENTATION PHILOSOPHY (RCSIP)

RE-ENGINEERED CONTROL SYSTEM IMPLEMENTATION PHILOSOPHY (RCSIP)

Meaning of Control System

Water filling System

A Control System is a combination of different Components for the purpose of manipulating or regulating a process. 
sample of a Control System Equation

Control System Equation

The Components/Sequences of a Control System

•    The Set or Reference Point
•    The Controller
•    The Actuator
•    The Process
•    Process Variable
•    Sensor

Simulink Simulation of the Water Filling System

 The figure below shows the block diagram of a simulink simulation water filling system.
Simulink simulation of the water filling system

Characterizing the Water Filling System

The diagram below shows the function block parameters of a PID controller.
The function block parameters of a PID controller.

Ideal Step Response of the Water Filling System

 Below is the graph of an ideal step response of the water system.
Figure 5: Ideal Step Response of the water filling system graph

The Step Response of the Water Filling System at Varying Control Parameters

The graph below is the graph of the step response of the water filling system at varying control parameters.


Figure 6: The step response of the water filling system at varying control parameters

Existing Industrial Control System Automation Architecture (ICSAA) and Inherent Challenges

 The Industrial Control System Automation Architecture of a water filling system and the Network Segmentation and Security Logic for ICSAA are shown in the two diagrams below.
Industrial Control System Automation Architecture of a water filling system
ICSAA
Network Segmentation and Security Logic for ICSAA
Network Segmentation and Security Logic for ICSAA

The Solution Philosophy: Control System Hardening 

The figure below illustrates the embedded security solution for Process Control.


Embedded security solution for Process Control


Control System Hardening: A Case for Operating (Set) Point in Acid Gas Removal from Natural gas



The diagram below shows the Acid Gas Removal Process with the chemical equations involved, substances involved and their boiling points and densities.
Acid Gas Removal Process (AGRP)

Figure 10: Acid Gas Removal Process (AGRP)


Automation architecture for temperature control of AGRP
Figure 11: Automation architecture for temperature control of AGRP

AGRP:  The Mathematical and Simulink Models for the Operating Point Hardening



The Mathematical and Simulink Models for the Operating Point Hardening

AGRP:  Validating the Mathematical and Simulink Models for the Operating Point Hardening

Validating the Mathematical and Simulink Models for the Operating Point Hardening
Validating the Mathematical and Simulink Models for the Operating Point Hardening
Graph for Validating the Mathematical and Simulink Models for the Operating Point Hardening
Graph for Validating the Mathematical and Simulink Models for the Operating Point Hardening
The table in the diagram shows the response characteristics of the hardened control system.
The response characteristics of the hardened control system
Table 2: The response characteristics of the hardened control system
The table in the diagram below shows the distribution of the steady state errors of hardened and unhardened control system.


Distribution of the steady state errors of hardened and unhardened control system
The standard deviation of the results without the hardener was found to be 0.007698 while that of the control system with hardener is 0.001429. The ratio of 0.007698 to 0.001429 is 5.39 representing 81.44 percentage improvements in accuracy.

Conclusion

Control system and ICT solutions used to work as separate entities in parallel line.  Now, things have changed. Control systems are being increasingly interfaced with ICT solutions for Optimal System Management and Production (OSMP). With internet of things emerging, more Integration will happen.

This integration requires human resources with dual knowledge of ICT and Control Engineering so as to avoid integration errors which can have huge consequences as far as Industrial Control System is concerned.
The human resources with this requisite knowledge are PRESENTLY LACKING in the industries.

Academia need to review university curriculum to bridge this gap.
Institutions, private organizations, individuals that will develop in this direction will definitely have course to smile in the immediate future.

Click the link to download the PDF copy of  this article for free: RE-ENGINEERED CONTROL SYSTEM IMPLEMENTATION PHILOSOPHY (RCSIP)

Reference

Modeling a Process - Filling a Tank. (n.d.). Retrieved August 12, 2016, from http://eleceng.dit.ie/gavin/Control/Modeling/Filling%20a%20Tank.htm


By Engr. Ekene Samuel Mbonu     


(MNSE, MIEEE, MISA, B.Eng., M.Eng)

See Also: How to Integrate Photo Voltaic Solar Systems As an Alternative Energy Source

See Also: How to Use Solar Energy to Power Base Stations

Hope you learnt a lot from this article? Comment below if you have any confusion. Don’t forget to share this article with your friends. Also subscribe to get our latest posts.

Share this

Related Posts

Previous
Next Post »

WHAT'S ON YOUR MIND?
WE LOVE TO HEAR FROM YOU!

Like Our Page Today