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CONTROL SYSTEM
Group Members:
๏‚—Muhammad Saleem Nagri

(10-ee-38)
๏‚—Mazhar Ali balti
(10-ee-49)
๏‚—Ehtisham-ul- Haq Chilasi
(10-ee-48)
๏‚—Asad Ali Jafri
(10-ee-164)
๏‚—Nisar Ahmad
(10-ee-39)
Mirpur University of Science and Technology
AJ&K,Pakistan.
The Excitement of Control
Engineering
Motivation for Control Engineering
Feedback control has a long history which began with
the early desire of humans to harness the materials and
forces of nature to their advantage. Early examples of
control devices include clock regulating systems .
Modern industrial plants have sophisticated control
systems which are crucial to their successful operation.
A modern industrial plant: A section of the
Oil Refinery Plant
Impact on Industry
Control Engineering has had a major impact on society.
For example, Wattโ€™s Fly Ball Governor had a major
impact on the industrial revolution. Indeed, most
modern systems (aircraft, high speed trains, CD players,
electrical appliance โ€ฆ ) could not operate without the
aid of sophisticated control systems.
Figure: Wattโ€™s fly ball governor
This photograph shows a flyball
governor used on a steam engine
in a cotton factory . Of course,
Cotton industry was at the centre of the
industrial revolution. Actually, this
cotton factory is still running today.
This flyball governor is in the
same cotton factory mentoned above.
However, this particular governor
was used to regulate the speed of
a water wheel driven by the flow of
the river. The governor is quite
large as can be gauged by the outline
of the door frame behind the
governor.
Improved control system benefits:
๏‚— enhanced product quality
๏‚— waste minimization
๏‚— environmental protection
๏‚— greater throughput for a given installed capacity
๏‚— greater yield
๏‚— deferring costly plant upgrades, and
๏‚— higher safety margins
Figure: Process schematic of a Kellogg ammonia plant
System Integration
Success in control engineering depends on taking a
holistic viewpoint. Some of the issues are:
๏‚— plant, i.e. the process to be controlled
๏‚— objectives
๏‚— sensors
๏‚— actuators
๏‚— communications
๏‚— computing
๏‚— architectures and interfacing
๏‚— algorithms
Plant
The physical layout of a plant is an intrinsic part of
control problems. Thus a control engineer needs to be
familiar with the "physics" of the process under study.
This includes a rudimentary knowledge of the basic
energy balance, mass balance and material flows in the
system.
Objectives
Before designing sensors, actuators or control
architectures, it is important to know the goal, that is,
to formulate the control objectives. This includes
๏‚— what does one want to achieve (energy reduction, yield
increase,...)
๏‚— what variables need to be controlled to achieve
these objectives
๏‚— what level of performance is necessary (accuracy,
speed,...)
Sensors
Sensors are the eyes of control enabling one to see what
is going on. Indeed, one statement that is sometimes
made about control is:
If you can measure it, you can control it.
Actuators
Once sensors are in place to report on the state of a
process, then the next issue is the ability to affect, or
actuate, the system in order to move the process from
the current state to a desired state
Figure: Typical flatness control set-up for rolling mill

A typical industrial control problem will usually
involve many different actuators - see below:
Communications
Interconnecting sensors to actuators, involves the use
of communication systems. A typical plant can have
many thousands of separate signals to be sent over long
distances. Thus the design of communication systems
and their associated protocols is an increasingly
important aspect of modern control engineering.
Computing
In modern control systems, the connection between
sensors and actuators is invariably made via a
computer of some sort. Thus, computer issues are
necessarily part of the overall design. Current
control systems use a variety of computational devices
including DCS's (Distributed Control
Systems),
PLC's (Programmable Logic Controllers), PC's (Personal
Computers), etc.
Algorithms
Finally, we come to the real heart of control engineering
i.e. the algorithms that connect the sensors to the
actuators. It is all to easy to underestimate this final aspect
of the problem.
As a simple example from our everyday experience,
consider the problem of playing tennis at top international
level. One can readily accept that one needs good eye sight
(sensors) and strong muscles (actuators) to play tennis at
this level, but these attributes are not sufficient. Indeed
eye-hand coordination (i.e. control) is also crucial to
success.
In summary:
Sensors provide the eyes and actuators the muscle but
control science provides the finesse.
๏ถ Better Sensors
Provide better Vision
๏ถ Better Actuators
Provide more Muscle

๏ถ Better Control
Provides more finesse by combining sensors and
actuators in more intelligent ways

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Lcs presentation

  • 1. CONTROL SYSTEM Group Members: ๏‚—Muhammad Saleem Nagri (10-ee-38) ๏‚—Mazhar Ali balti (10-ee-49) ๏‚—Ehtisham-ul- Haq Chilasi (10-ee-48) ๏‚—Asad Ali Jafri (10-ee-164) ๏‚—Nisar Ahmad (10-ee-39) Mirpur University of Science and Technology AJ&K,Pakistan.
  • 2. The Excitement of Control Engineering
  • 3. Motivation for Control Engineering Feedback control has a long history which began with the early desire of humans to harness the materials and forces of nature to their advantage. Early examples of control devices include clock regulating systems . Modern industrial plants have sophisticated control systems which are crucial to their successful operation.
  • 4. A modern industrial plant: A section of the Oil Refinery Plant
  • 5. Impact on Industry Control Engineering has had a major impact on society. For example, Wattโ€™s Fly Ball Governor had a major impact on the industrial revolution. Indeed, most modern systems (aircraft, high speed trains, CD players, electrical appliance โ€ฆ ) could not operate without the aid of sophisticated control systems.
  • 6. Figure: Wattโ€™s fly ball governor
  • 7. This photograph shows a flyball governor used on a steam engine in a cotton factory . Of course, Cotton industry was at the centre of the industrial revolution. Actually, this cotton factory is still running today.
  • 8. This flyball governor is in the same cotton factory mentoned above. However, this particular governor was used to regulate the speed of a water wheel driven by the flow of the river. The governor is quite large as can be gauged by the outline of the door frame behind the governor.
  • 9. Improved control system benefits: ๏‚— enhanced product quality ๏‚— waste minimization ๏‚— environmental protection ๏‚— greater throughput for a given installed capacity ๏‚— greater yield ๏‚— deferring costly plant upgrades, and ๏‚— higher safety margins
  • 10. Figure: Process schematic of a Kellogg ammonia plant
  • 11. System Integration Success in control engineering depends on taking a holistic viewpoint. Some of the issues are: ๏‚— plant, i.e. the process to be controlled ๏‚— objectives ๏‚— sensors ๏‚— actuators ๏‚— communications ๏‚— computing ๏‚— architectures and interfacing ๏‚— algorithms
  • 12. Plant The physical layout of a plant is an intrinsic part of control problems. Thus a control engineer needs to be familiar with the "physics" of the process under study. This includes a rudimentary knowledge of the basic energy balance, mass balance and material flows in the system.
  • 13. Objectives Before designing sensors, actuators or control architectures, it is important to know the goal, that is, to formulate the control objectives. This includes ๏‚— what does one want to achieve (energy reduction, yield increase,...) ๏‚— what variables need to be controlled to achieve these objectives ๏‚— what level of performance is necessary (accuracy, speed,...)
  • 14. Sensors Sensors are the eyes of control enabling one to see what is going on. Indeed, one statement that is sometimes made about control is: If you can measure it, you can control it.
  • 15. Actuators Once sensors are in place to report on the state of a process, then the next issue is the ability to affect, or actuate, the system in order to move the process from the current state to a desired state
  • 16. Figure: Typical flatness control set-up for rolling mill A typical industrial control problem will usually involve many different actuators - see below:
  • 17.
  • 18. Communications Interconnecting sensors to actuators, involves the use of communication systems. A typical plant can have many thousands of separate signals to be sent over long distances. Thus the design of communication systems and their associated protocols is an increasingly important aspect of modern control engineering.
  • 19. Computing In modern control systems, the connection between sensors and actuators is invariably made via a computer of some sort. Thus, computer issues are necessarily part of the overall design. Current control systems use a variety of computational devices including DCS's (Distributed Control Systems), PLC's (Programmable Logic Controllers), PC's (Personal Computers), etc.
  • 20.
  • 21. Algorithms Finally, we come to the real heart of control engineering i.e. the algorithms that connect the sensors to the actuators. It is all to easy to underestimate this final aspect of the problem. As a simple example from our everyday experience, consider the problem of playing tennis at top international level. One can readily accept that one needs good eye sight (sensors) and strong muscles (actuators) to play tennis at this level, but these attributes are not sufficient. Indeed eye-hand coordination (i.e. control) is also crucial to success.
  • 22. In summary: Sensors provide the eyes and actuators the muscle but control science provides the finesse.
  • 23. ๏ถ Better Sensors Provide better Vision ๏ถ Better Actuators Provide more Muscle ๏ถ Better Control Provides more finesse by combining sensors and actuators in more intelligent ways

Editor's Notes

  1. <<<1.1>>> ###Control System Design### {{{Control, Design}}}
  2. <<<1.2>>>
  3. <<<1.3>>>
  4. {{{Flyball Governor}}}
  5. {{{cotton mill}}}
  6. {{{ammonia plant}}}
  7. <<<1.5>>> ###System Integration###
  8. <<<1.5.1>>>
  9. <<<1.5.2>>>
  10. <<<1.5.3>>>
  11. <<<1.5.4>>>
  12. <<<1.5.5>>>
  13. <<<1.5.6>>>
  14. <<<1.5.8>>>