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Process Dynamics - Process Control - Lecture Slides, Slides of Process Control

This lecture is from Process Control course. Some key points for this lecture are: Process Dynamics, Steady State, Variables, Unsteady State Behavior, Curriculum Emphasizes, Mass and Energy Balance, Transient Behavior, Unit Operation, Shutdown, Start Up

Typology: Slides

2012/2013

Uploaded on 03/18/2013

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Process Dynamics
a) Refers to unsteady-state or transient behavior.
b) Steady-state vs. unsteady-state behavior
i. Steady state: variables do not change with time
ii. But on what scale? cf., noisy measurement
c) ChE curriculum emphasizes steady-state or equilibrium
situations:
i. Examples: Mass and Energy Balance, Unit Operation, Etc.
d) Continuous processes: Examples of transient behavior:
i. Start up & shutdown
ii. Grade changes
iii.Major disturbance: e.g., refinery during stormy or hurricane
conditions
iv. Equipment or instrument failure (e.g., pump failure)
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Download Process Dynamics - Process Control - Lecture Slides and more Slides Process Control in PDF only on Docsity!

Process Dynamics

a) Refers to unsteady-state or transient behavior.

b) Steady-state vs. unsteady-state behavior

i. Steady state: variables do not change with time ii. But on what scale? cf., noisy measurement

c) ChE curriculum emphasizes steady-state or equilibrium situations: i. Examples: Mass and Energy Balance, Unit Operation, Etc.

d) Continuous processes : Examples of transient behavior:

i. Start up & shutdown ii. Grade changes iii. Major disturbance: e.g., refinery during stormy or hurricane conditions iv. Equipment or instrument failure (e.g., pump failure)Docsity.com

e) Batch processes

i. Inherently unsteady-state operation ii. Example: Batch reactor

  1. Composition changes with time
  2. Other variables such as temperature could be constant.

Process Control

a) Large scale, continuous processes:

i. Oil refinery, ethylene plant, pulp mill

ii. Typically, 1000 – 5000 process variables are measured.

  1. Most of these variables are also controlled.

iii. Examples: flow rate, T , P , liquid level, composition iv. Sampling rates:

  1. Process variables: A few seconds to minutes
  2. Quality variables: once per 8 hr shift, daily, or weekly

b) Manipulated variables

i. We implement “process control” by manipulating process variables, usually flow rates.

  1. Examples: feed rate, cooling rate, product flow rate, etc. ii. Typically, several thousand manipulated variables in a large continuous plant

Process Control (cont’d.)

1.1 Illustrative Example: Blending system

Notation:

  • w 1 , w 2 and w are mass flow rates
  • x 1 , x 2 and x are mass fractions of component A Docsity.com

Assumptions:

  1. w 1 is constant
  2. x 2 = constant = 1 (stream 2 is pure A)
  3. Perfect mixing in the tank

Control Objective:

Keep x at a desired value (or “set point”) x sp , despite variations in

x 1 ( t ). Flow rate w 2 can be adjusted for this purpose.

Terminology:

  • Controlled variable (or “output variable”): x
  • Manipulated variable (or “input variable”): w 2
  • Disturbance variable (or “load variable”): x Docsity.com
  • Equation 1-3 is the design equation for the blending system.
  • If our assumptions are correct, then this value of will keep at. But what if conditions change?

x x SP

Control Question. Suppose that the inlet concentration x (^1) changes with time. How can we ensure that x remains at or near the set point?

As a specific example, if and , then x > x (^) SP.

x SP

x 1 (^) > x 1 w 2 (^) = w 2

Some Possible Control Strategies:

Method 1. Measure x and adjust w 2.

  • Intuitively, if x is too high, we should reduce w 2 ;

w 2

  • Manual control vs. automatic control
  • Proportional feedback control law,

w 2 (^) ( ) t (^) = w 2 (^) + K (^) c  xSPx t ( ) (1-4)

  1. where Kc is called the controller gain. 2. w 2 ( t ) and x ( t ) denote variables that change with time t.
  2. The change in the flow rate, is proportional to the deviation from the set point, xSPx ( t ).

w 2 (^) ( ) tw 2 ,

Method 2. Measure x 1 and adjust w 2.

  • Thus, if x 1 is greater than , we would decrease w 2 so that
  • One approach : Consider Eq. (1-3) and replace and with x 1 ( t ) and w 2 ( t ) to get a control law:

x 1 w 2 (^) < w 2 ;

x 1 w 2

( ) 1 ( ) 2 1 1 (1-5)

SP SP

x x t w t w x

1.2 Classification of Control Strategies

Method Measured Variable

Manipulated Variable

Category

1 x (^) w 2 FB a

2 x 1 w 2 FF 3 x 1 and x w 2 FF/FB 4 - - Design change

Table. 1.1 Control Strategies for the Blending System

Feedback Control:

  • Distinguishing feature: measure the controlled variable
  • It is important to make a distinction between negative feedback and positive feedback.

 Engineering Usage vs. Social Sciences

  • Advantages:

 Corrective action is taken regardless of the source of the disturbance.  Reduces sensitivity of the controlled variable to disturbances and changes in the process (shown later).

  • Disadvantages:

 No corrective action occurs until after the disturbance has upset the process, that is, until after x differs from x (^) sp.

 Very oscillatory responses, or even instability… Docsity.com

Justification of Process Control

Specific Objectives of Control

  • Increased product throughput
  • Increased yield of higher valued products
  • Decreased energy consumption
  • Decreased pollution
  • Decreased off-spec product
  • Increased Safety
  • Extended life of equipment
  • Improved Operability
  • Decreased production labor

3.2 Economic Incentives - Advanced

Control