Process control involves maintaining the output of a process within a desired range through mechanisms and algorithms. For example, controlling the temperature of a chemical reactor to maintain consistent product output. There are different types of process control including regulatory control to maintain performance at a certain level, feedforward control which anticipates disturbances to compensate before they affect the process, and adaptive control where the controller modifies its own parameters based on dynamic process conditions. Discrete control systems make event-driven or time-driven changes to processes.

1. Process control
is an engineering discipline that deals with architectures,
mechanisms and algorithms for maintaining the output of a specific
process within a desired range. For instance, the temperature of a
chemical reactor may be controlled to maintain a consistent
product output.
Types of processes using process control
Continuous Process Control
ƒ Regulatory control
In regulatory control, the objective is to maintain process performance
at a certain level or within a given tolerance band of that level. This is
appropriate,for example, when the performance attribute is some measure
of product quality, and it is important to keep the quality at the specified
level Of within a specified range.

2. Applications
The Shell Surge Volume Control (SSVC)
is designed to take full advantage of the Surge Capacity available
in the plant to achieve a more stable operation. The SSVC module
manages the surge vessel’s level within specified limits while
minimizing flow fluctuation entering or leaving the surge vessel.
The algorithm is designed to work not only for one surge volume
but also for cascading surge volume such as cascading Distillation
Columns.

3. ƒ Feedforward control
The strategy in feedforward control is to anticipate the effeet of
disturbances that will upset the process by sensing them and
compensating for them before they can affect the process.
Usually combined with regulatory control.
Regulatory control and feedforward control are more closely associated
with process industries.
Examples
In order to illustrate the effect of feedforward control, let us consider the
heat exchange process shown in Fig.1. The cold water comes from a tank
and flows to the heat exchanger. The flow rate of cold water can be
considered as a disturbance. The change in input flow line may occur due
to the change in water level in the tank. Suppose, the feedforward line is
not connected, and the controller acts as a feedback control only. If the

4. water inlet flow rate increases, the temperature of the outlet hot water flow
will decrease. This will be sensed by the temperature sensor that will
compare with the set point temperature and the temperature controller will
send signal to open the control valve to allow more steam at the steam
inlet. The whole operation is a time consuming and as a result the response
of the controller due to the disturbance (inlet water flow rate) is normally
slow. But if we measure the change in inlet flow rate by a flowmeter and
feed this information to the controller, the controller can immediately take
the correcting action anticipating the change in outlet temperature. This
will improve the speed of response. Thus feedforward action, in addition
to the feedback control improves the performance of the system, but
provided, the disturbance is measurable.

6. ƒ Steady-State optimization
This term refers to a class of optimization techniques in which the process
exhibits the following charecteristics : (1) there is a well-defined index of
performance, such as product cost, production rate, or process yield; (2)
the relationship between the process variables and the index of
performance is known; and (3) the values of the system parameters that
optimize the index of performance can be determined mathematically.
When these characteristics apply, the control algorithm is designed to
make adjustments in the process parameters to drive the process toward
the optimal state. The control system is open-loop, as seen in Figure 4.4,
Several mathematical techniques are available for solving steady-state
optimal control problems, including differential calculus, calculus of
variations, and a variety of mathematical programming methods

7. ƒ Adaptive control
An automatic control scheme in which the controller is programmed to
evaluate its own effectiveness and modify its own control parameters to
respond to dynamic conditions occurring in or to the process which affect
the controlled variables.
Examples
(1)Adaptive Control of Batch Reactors
Batch Reactor: Chemical batch reactors are critical operating units and
automatic control of the reaction temperature is desirable. Due to its
complex nature, a large percentage of batch reactors running today
cannot keep the temp in auto-matic control throughout its entire
operating period. This results in lower efficiency, wasted manpower and
materials, and poor product quality.

8. Objectives: The control system must react quickly to cut-off the cooling
water and send in a proper amount of steam to drive the temperature
back to normal. PID cannot control the temp during this transition if it is
tuned to control the process for Stages 1 and 2. Typically, reactors are
switched to manual control and rely on well-trained operators during
critical transitions.
(2)Adaptive Control of CNC, DNC
sources of variability in machining
1. Variable depth/width of cut 2. Variable workpiece hardness and
variable machinability. 3. Variable workpiece rigidity
4. Toolwear 5. Air gaps during cutting
Adaptive Control Optimization (ACO)
 Index of performance is a measure of overall process performance
such as production rate or cost per volume of metal removed.
 Objective is to optimize the index of performance by manipulating
speed or feed in the operation
 IP = MRR/TWRMRR – Material removal rate TWR – Tool wear rate
 Sensors for measuring IP not available

9. Adaptive control Constraint (ACC)
 Nearly all AC systems is of this type
 Less sophisticated and less expensive than research ACO systems
 Objective is to manipulate speed or feed so that measured process
variables are maintained at or below their constraint limit values.
Operation of ACC system
 Profile or contour milling on NC machine tool
 Feed is controlled variable
 Cutter force and horsepower are used as measured variables
 Hardware components
1. Sensors mounted on the spindle to measure cutter force
2. Sensors to measure spindle motor current
3. Control unit and display panel to operate the system
4. Interface hardware to connect the AC system to existing NC/CNC
system.

10. 3- Indirect and Multimodel Adaptive Control of a Flexible
Transmission:
The flexible transmission built consists of three horizontal pulleys
connected by two elastic belts.The first pulley is driven by a D.C. motor
whose position is controlled by local feedback. The third pulley may be
loaded with disks of different weight.
The objective is to control the position of the third pulley measured by a
position sensor. The system input is the reference for the axis position of
the first pulley. A PC is used to control the system. The sampling
frequency is 20 Hz.

11. ƒ On-line search strategies
Special class of adaptive control in which the decision function cannot
be sufficiently defined.
Relationship between input parameters and IP is not known, or not
known well enough to implement the previous form of adaptive control.
Instead, experiments are performed on the process.
Small systematic changes are made in input parameters to observe
effects.
Based on observed effects, larger changes are made to drive the system
toward optimal performance.
Discrete Control Systems
Changes are executed either due to a change of the state of
the system or because of elapsed time .
Event-driven changes:
Responds to some event that has changes the state of the system
,such as presence of a part,low-level of plastic molding
compound, counting parts on a conveyer belt.
Time-driven change :
Executed either at a specific time,or after a certain time lapes
,such as “Shop Clock” to start and end work , length of heat
treatment , A washing machine has both event-driven and time-
driven changes that control it.

12. Types of discrete control :
1- Combinational logic control : controls the event –driven
changes.
2-Sequential control : manages time-driv

13. NAME : Amr Mohamed Seif eldin
CLASS : ( 2 )
DEPARTMENT: production and design dep.
Delivered TO: Prof.Dr : Soliman El-Naggar