proces dynamics & controls.pdf
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Introduction to PD&C
In the chemical industry, the design of a controlsystem is essential to achieve:
1. Safety
2. Environmental protection3. Equipment protection
4. Smooth operation
5. Product quality
6. Profit
7. Monitoring and diagnosis
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Why?
Most chemical and biological engineers are notprocess control experts, but they need to
understand the basics!
Production engineering: responsible for day-to-dayoperations. Need to understand process controls to
deal with daily issues.
Process engineer: longer term view towardcontinuous process improvementtheseimprovements often involve new or modified processcontrols.
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Specialists
Some chemical and biological engineers becomeprocess control engineers focus on improving
process control systems and implementingstandard systems
Even fewer become process control specialists
implement solutions for specialized, nonstandard,control situations.
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Basic Control System
Oil heater that uses steam
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A balloon by itself indicates a discrete stand-alone instrument, such as a:
Transmitter
Sensor
Alarm
P & ID General Instrument Symbols:
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Basic Control System
#1 we need a sensor (and we cannot measureeverything, like entropy or fugacity)
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Basic Control System
#2 we need a controller (e.g., PID controller)
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Basic Control System
#3 we need something to control (and we cannotcontrol everything like steam T and P)
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Introduction
Process Dynamics:
Study of the transient behavior of processes
Process Control
the use of process dynamics for the improvement ofprocess operation and performance
or
the use of process dynamics to alleviate the effect of
undesirable (unstable) process behaviors
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Ref. book
Focus is on information needed by process andproduction engineers (i.e., not specialists)
Reference book:1. Chemical Process Control: An Introduction to Theory and Practice, George Stephanopoulos2. Process dynamics and control, Modeling for control and prediction, Brain Roffel and BenBetlem
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Introduction
What do we mean by process?
A process, P, is an operation that takes an INPUT or a DISTURBANCEand givesan OUTPUT
INPUT: (u) Something that you can manipulate
DISTURBANCE: (d) Something that comes as a result of some outsidephenomenon
OUTPUT: (y) An observable quantity that we want to regulate
u
d
yP
Information Flow
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Examples
Stirred tank heater
M
Tin, w
Q
T, w
TinwQ
TProcess
Inputs Output
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Control
What is control?
To regulate of a process output despite the effect of disturbancese.g.
Driving a car
Controlling the temperature of a chemical reactor Reducing vibrations in a flexible structure
To stabilize unstable processes e.g.
Riding a bike
Flight of an airplane
Operation of a nuclear plant
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Benefits of Control
Economic Benefits
Quality (waste reduction)
Variance reduction (consistency)
Savings in energy, materials, manpower
Operability, safety (stability)
Performance
Efficiency
Accuracy robotics
Reliability Stabilizability
bicycle
aircraft
nuclear reactor
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Control
A controller is a system designed to regulate a given process Process typically obeys physical and chemical conservation laws
Controller obeys laws of mathematics and logic (sometimesintelligent)
e.g. - Riding a bike (human controller)
- Driving a car
- Automatic control (computer programmed to control)
Process
Controller
What is a controller?
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Block representations
Block diagrams are models of the physical systems
Process
System PhysicalBoundary Transfer offundamental
quantities
Mass, Energy and Momentum
Input variables Output variables
Physical
OperationAbstract
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Control
A controlled processis a system which is comprised of two interactingsystems:
e.g. Most controlled systems are feedback controlled systems
The controller is designed to provide regulation of process outputs in thepresence of disturbances
Process
Controller
OutputsDisturbances
Action Observation
monitorintervene
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What is required?
What is required to control a process?
1. Process Understanding Required measurements
Required actuators
Understand design limitations
2. Process Instrumentation Appropriate sensor and actuator selection
Integration in control system
Communication and computer architecture3. Process Control
Appropriate control strategy
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Types of Process Controls
1. Manual control (open loop)
2. On/Off control (closed feedback loop)
3. PID control (closed feedback loop)
4. Dynamic model-based control (closed feedforward
loop)1. Empirical models (e.g., cold shower)
2. Phenomenological models
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Classical Control 20/9
Control is meant to provide regulation of process outputs about areference/set point, r, despite inherent disturbances
The deviation of the plant output, e=(r-y), from its intended
reference/setpoint is used to make appropriate adjustments in the plantinput, u
ProcessController
Classical Feedback Control System
d
yur e+
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Control Nomenclature
Identification of all process variables
Inputs (affect process) Outputs (result of process)
Inputs
Disturbance variables Variables affecting process that are due to external forces
Manipulated variables Things that we can directly affect
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Control
Process is a combination of sensors and actuators
Controller is a computer (or operator) that performs the required
manipulations
e.g. Classical feedback control loop
yr e
AC P
M
d
Computer Actuator
Process
Sensor
-
+
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Positive & negative control
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Examples
Stirred-Tank Heater
Q T, w
Heater
TCThermocouple
Tin, w
Tin, w
ye
AC P
M
Controller
Tank
-
+
Heater
Thermocouple
TR
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Examples
Measure Ti, adjust Q
A PC
MTi
Qi
Q
Q
+
+
Feedforward Control
Control System Development
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Control System Development
Define Objectives
Develop a processmodel
Design controllerbased on model
Test bySimulation
Implement and Tune
MonitorPerformance
Control development is usually carried out following theseimportant steps
Often an iterative process, based on performance we maydecide to retune, redesign or remodel a given control system
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Control System Development
Objectives
What are we trying to control?
Process modeling
What do we need? Mechanistic and/or empirical
Controller design
How do we use the knowledge of process behavior to
reach our process control objectives? What variables should we measure?
What variables should we control?
What are the best manipulated variables?
What is the best controller structure?
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Control System Development
Implement and tune the controlled process
Test by simulation
incorporate control strategy to the process hardware tune and re-tune
Monitor performance periodic retuning and redesign is often necessary based
on sensitivity of process or market demands
statistical methods can be used to monitor performance
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Process Modeling
Motivation:
Develop understanding of process
a mathematical hypothesis of process mechanisms Match observed process behavior
useful in design, optimization and control of process
Control:
Interested in description of process dynamics Dynamic model is used to predict how process responds to given
input
Tells us how to react
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Process Modeling
What kind of model do we need?
Dynamic vs. Steady-state
Steady-state Variables not a function of time
useful for design calculation
Dynamic
Variables are a function of time Control requires dynamic model
Process Modeling
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Process Modeling
What kind of model do we need?
Experimental vs Theoretical
Experimental Derived from tests performed on actual process
Simpler model forms Easier to manipulate
Theoretical Application of fundamental laws of physics and chemistry
more complex but provides understanding
Required in design stages
Process Modeling
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g
Dynamic vs. Steady-state
Step change in input to observe
Starting at steady-state, we made a step change
The system oscillates and finds a new steady-state
Dynamics describe the transitory behavior
0 50 100 150 200 250 30040
45
50
55
60
65
Output
Time
Steady-State 1
Steady-State 2
Process Modeling
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Process Modeling
Empirical vs. Mechanistic models Empirical Models
only local representation of the process
(no extrapolation) model only as good as the data
Mechanistic Models Rely on our understanding of a process
Derived from first principles Observing laws of conservation of
Mass
Energy
Momentum Useful for simulation and exploration of new operating conditions
May contain unknown constants that must be estimated
Process Modeling
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Process Modeling
Empirical vs Mechanistic models
Empirical models
do not rely on underlying mechanisms Fit specific function to match process
Mathematical French curve
0 5 0 1 0 0 1 5 0 2 0 0 2 5 0 3 0 00 . 4
0 . 5
0 . 6
0 . 7
0 . 8
0 . 9
1
1 . 1
1 . 2
1 . 3
Output
T i m e
Process Modeling
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Linear vs Nonlinear Linear
basis for most industrial control
simpler model form, easy to identify
easy to design controller
poor prediction, adequate control
Nonlinear
reality more complex and difficult to identify
need state-of-the-art controller design techniques to do the job
better prediction and control
Process Modeling
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g
In existing processes, we really on Dynamic models obtained from experiments
Usually of an empirical nature
LinearIn new applications (or difficult problems)
Focus on mechanistic modeling
Dynamic models derived from theory Nonlinear
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Process Modeling
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Modeling procedure
Check model consistency do we have more unknowns than equations
Determine unknown constants e.g. friction coefficients, fluid density and viscosity
Solve model equations typically nonlinear ordinary (or partial) differential equations
initial value problems
Check the validity of the model compare to process behavior
Process Control and Modeling
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In designing a controller, we must Define control objectives
Develop a process model
Design controller based on model Test through simulation
Implement to real process
Tune and monitor
y
d
Process
Model
Controllerur e
Design
Implementation
E l
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Example
T
L
T
wi, Ti
wc, Tci
wc, Tco
wo, To
h
Variables wi, wo: Tank inlet and outlet mass flows Ti, To: Tank inlet and outlet temperatures wc: Cooling jacket mass flow
Pc: Position of cooling jacket inlet valve Po: Position of tank outlet valve Tci, Tco: Cooling jacket inlet and outlet
temperatures h: Tank liquid level
Po
Pc
Example
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Example
Variables Inputs OutputsDisturbances Manipulated Measured Unmeasured Control
wiTiTciwch
woToPc
Po
Task: Classify the variables
Control System Development
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y p
Define Objectives
Develop a processmodel
Design controllerbased on model
Test bySimulation
Implement and Tune
MonitorPerformance
Control development is usually carried out following theseimportant steps
Often an iterative process, based on performance we maydecide to retune, redesign or remodel a given control system
The task of a process control system
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The task of a process control system
Monitoring certain variables that indicate process
conditions at any time (measurements)
Making rational decisionsregarding what corrective
action is needed (current state vs. desired state)
Inducing changes in the appropriate process
variables to improve process conditions (valves tomanipulate)
once more...
According to what rationale does a
feedback control system work?
On off control: the simplest one
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On-off control: the simplest one
The control variable is manipulated according to:
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