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.

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.

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

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.

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

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.

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

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.

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.

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.

Types of discrete control :

1- Combinational logic control : controls the event –driven

changes.

2-Sequential control : manages time-driv

NAME : Amr Mohamed Seif eldin

CLASS : ( 2 )

DEPARTMENT: production and design dep.

Delivered TO: Prof.Dr : Soliman El-Naggar