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
REENGINEERED CONTROL SYSTEM IMPLEMENTATION PHILOSOPHY (RCSIP)
Meaning of Control System
A Control System is a combination of different Components for the purpose of manipulating or regulating a process.

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.
Characterizing the Water Filling System
The diagram below shows 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.
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.
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.

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.
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.

Figure 10: Acid Gas Removal Process (AGRP)


Figure 11: Automation architecture for temperature control
of AGRP

AGRP: 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 

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.

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.
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.
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