The document discusses automatic controllers used in industrial processes, explaining their functionality in comparing actual outputs with desired values to generate control signals. It categorizes types of controllers, including on-off, proportional, and fuzzy controllers, and describes distributed control systems (DCS) that utilize multiple local controllers connected through a communication network for efficient operations. The DCS architecture enhances reliability and reduces costs in various industrial applications such as chemical plants, power plants, and manufacturing.

1. 1
EEE 2221
Instrumentation and Electrical Control
Nayeema Hasan
Lecturer
Dept. of EEE, KUET.

2. Automatic Controllers
2
 An automatic controller compares the actual value of the plant
output with the reference input (desired value), determines the
deviation, and produces a control signal that will reduce the
deviation to zero or to a small value.
 The manner in which the automatic controller produces the control
signal is called the control action.
 The controller detects the actuating error signal, which is usually at
a very low power level, and amplifies it to a sufficiently high level.
 The output of an automatic controller is fed to an actuator, such as
an electric motor, a hydraulic motor, or a - pneumatic motor or
valve. (The actuator is a power device that produces the input to the
plant according to the control signal so that the output signal will
approach the reference input signal.)

3. Automatic Controllers
3
Figure: Block diagram of an industrial control system, which consists of an
automatic controller, an actuator, a plant, and a sensor , (measuring element).

4. 4
Classification of Industrial Controllers
Industrial controllers may be classified according to their control actions as:
 1. Two-position or on-off controllers
 2. Proportional controllers
 3. Integral controllers
 4. Proportional-plus-integral controllers
 5. Proportional-plus-derivative controllers
 6. Proportional-plus-integral-plus-derivative controllers
 Most industrial controllers use electricity or pressurized fluid such as oil
or air as power sources. Controllers may also be classified according to the
kind of power employed in the operation, such as pneumatic controllers,
hydraulic controllers, or electronic controllers.
 What kind of controller to use must be decided based on the nature of the
plant and the operating conditions, including such considerations as
safety, cost, availability, reliability, accuracy, weight, and size.

5. 5
Two-position or on-off controllers
 In a two-position control system, the actuating element has only
two fixed positions, which are, in many cases, simply on and off.
 Two-position or on-off control is relatively simple and inexpensive
and, for this reason, is very widely used in both industrial and
domestic control systems.
 Let the output signal from the controller be u(t) and the actuating
error signal be e(t). In two-position control, the signal u(t) remains
at either a maximum or minimum value, depending on whether
the actuating error signal is positive or negative, so that
 u(t) = U1, for e(t) > 0
u(t) = U2, for e(t) < 0
where U1 and U2 are constants.
 The minimum value U2 is usually either zero or -Ul.

6. 6
Two-position or on-off controllers
Figure (a) Block diagram of an on-off controller
Figure (b) block diagram of an on-off controller with differential gap

7. 7
Two-position or on-off controllers
 Differential Gap: The range through which the actuating
error signal must move before the switching occurs is called
the differential gap.
 Such a differential gap causes the controller output u(t) to
maintain its present value until the actuating error signal has
moved slightly beyond the zero value.
 In some cases, the differential gap is a result of unintentional
friction and lost motion; however, quite often it is
intentionally provided in order to prevent too frequent
operation of the on-off mechanism.

8. 8
Proportional Controllers

9. 9
Integral Controllers

10. 10
Proportional-plus-integral Controllers

11. 11
Proportional-plus-derivative Controllers

12. 12
Proportional-plus-integral-plus-derivative
Controllers

13. 13
Proportional-plus-integral-plus-derivative
Controllers
Figure: Block diagram of a proportional-plus-integral-plus-derivative controller

14. 14
Fuzzy Controllers
 A fuzzy control system: is a control system based on fuzzy logic-a
mathematical system that analyzes analog input values in terms
of logical variables that take on continuous values between 0 and
1, in contrast to classical or digital logic, which operates on
discrete values of either 1 or 0 (true or false, respectively)
 The word fuzzy refers to things which are not clear or are vague.
Any event, process, or function that is changing continuously
cannot always be defined as either true or false, which means
that we need to define such activities in a Fuzzy manner.
Fuzzy Logic was introduced in 1965 by Lofti A. Zadeh in his
research paper “Fuzzy Sets”. He is considered as the father of
Fuzzy Logic.

15. 15
Fuzzy Controllers
 In the basic fuzzy system above, the values are indicated by a
number in the range from 0 to 1. Here 1.0 represents absolute
truth and 0.0 represents absolute falseness. The number which
indicates the value in fuzzy systems is called the truth value.

16. 16
Fuzzy Controllers
 Figure: The architecture of Fuzzy Logic Control (FLC).

17. 17
Fuzzy Controllers
Followings are the major components of the FLC as shown in the above
figure :
 Fuzzifier − The role of fuzzifier is to convert the crisp input values into
fuzzy values.
 Fuzzy Knowledge Base − It stores the knowledge about all the input-
output fuzzy relationships. It also has the membership function which
defines the input variables to the fuzzy rule base and the output
variables to the plant under control.
 Fuzzy Rule Base − A rule base is the set of rules for a fuzzy system. To
create a rule, you must specify the antecedents, or IF portions, and
consequents, or THEN portions, of the rule.
 Inference Engine − It acts as a core of any FLC. Basically it simulates
human decisions by performing approximate reasoning.
 Defuzzifier − The role of defuzzifier is to convert the fuzzy values into
crisp values getting from fuzzy inference engine.

18. 18
Distributed Control System (DCS)
 A distributed control system (DCS) is a digital automated
industrial control system (ICS) that uses geographically
distributed control loops throughout a factory, machine or
control area.
 Control loops are composed of all the hardware and software
control functions needed for measurements and adjustments in
an individual control system.
 A DCS has several local controllers throughout the factory. A
high-speed communication network connects the local
controllers.
 While each controller works autonomously, there is central
supervisory control run by an operator.

19. 19
Distributed Control System (DCS)
 Difference with a centralized control system:
Unlike a centralized control system that operates all machines, a
DCS enables each part of a machine to have its own dedicated
controller that runs the operation.
 Advantages:
Having the control system architecture distributed around the
factory or plant provides an effective control, efficiency and process
quality strategy.
Additionally, if a piece of the DCS architecture fails, a plant can
continue to operate. For these reasons, DSCes are commonly found
in industrial fields and processing or manufacturing plants.
The DCS concept increases reliability and reduces installation costs
by localizing control functions near the process plant, with remote
monitoring and supervision.

20. 20
Distributed Control System (DCS)
 The architectural design of a DCS includes the following:
 An engineering workstation. This is a supervisory controller for
the DCS as a whole. The station typically includes configuration
tools that let the user complete functions such as creating new
loops and input and output (I/O) points, as well as configuring
distributed devices.
 An operating station: This station is used for control, operation
and monitoring.
 A process control unit: This microprocessor-based controller is
designed for automatic and compound loop control.
 A communication system: This system brings data from station
to station and is important in distributed control systems.
Typical network protocols used include Ethernet, and Profibus.
 Smart devices: These are any smart devices or bus technologies
that are used to replace older I/O.

21. 21
Distributed Control System (DCS)
Figure: Functional Levels of a Manufacturing Control Operation

22. 22
Distributed Control System (DCS)
Level 0: contains the field devices such as flow and
temperature sensors, and control elements, such as control
valves.
Level 1: contains the industrialized Input/output (I/O)
modules, and their associated distributed electronic
processors.
Level 2: contains the supervisory computers, which collect
information from processor nodes on the system, and provide
the operator control screens.
Level 3: is the production control level, which does not
directly control the process, but is concerned with monitoring
production and monitoring targets
Level 4: is the production scheduling level.

23. 23
Distributed Control System (DCS)
 Applications of DCS:
Distributed control systems (DCS) are dedicated systems used in
manufacturing processes that are continuous or batch-oriented.
Chemical plants, Petrochemical (oil) and refineries, Pulp and paper
mills, Boiler controls and power plant systems, Nuclear power
plants, Environmental control systems, Water management systems,
Water treatment plants, Sewage treatment plants, Food and food
processing, Agrochemical and fertilizer, Metal and mines,
Automobile manufacturing, Pharmaceutical manufacturing, Sugar
refining plants, Agriculture applications.