PSE and PROCESS CONTROL
Sigurd Skogestad
Department of Chemical Engineering
Norwegian University of Science and Tecnology (NTNU)
Trondheim, Norway
PSE Education Session
AMIDIQ 2012, Mexico, May 2012
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PROCESS CONTROL
Theory
Left side of brain = logical
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PROCESS CONTROL
Control structures + Practise
Right side of brain = creative
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PROCESS CONTROL
Theory & practise
Combine both sides!
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Process control course.
Four main elements:
1. PROCESS
–
–
Process dynamics: Step responses, simulation
Process control structures: Flowsheet (P&ID*). PID tuning
2. CONTROL
–
theory: Feedback idea, block diagrams, stability, transfer functions
(Laplace), feedforward/cascade/frequency response, identification,
multivariable control (MPC)
3. PRACTISE
–
–
Laboratory
Simulation (Aspen, Hysys/Unisim..)
4. SYSTEMS
–
Modelling principles, Solution. State space models, linearization
(ABCD), optimization
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*P&ID: Process and Instrumentation Diagrams
Difficult course
•
Many new concepts
– Inputs and outputs, causality
– Feedback
– Stability
•
New mathematics
– Laplace
– Frequency analysis
– System theory (ABCD)
•
•
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And all of this combined with practise: operation of real plants
Too much for one course?
I teach the course in two parts
1. ”Process control” crash course (3 weeks)
–
Focus on process control structures (P&ID)
2. Standard process control course (11 weeks)
–
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Focus on theory
Crash course process control
Sigurd Skogestad
Institutt for kjemisk prosessteknologi
Rom K4-211
skoge@ntnu.no
More information (literature, old exams, etc.):
• www.nt.ntnu.no/users/skoge/prosessregulering_lynkurs
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Why control?
•
•
Until now: Design of process. Assume steady-state
Now: Operation
Actual value(dynamic)
Steady-state (average)
time
“Disturbances” (d’s)
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Example: Control of shower temperature
MVs, CVs and control
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CLASSIFICATION OF VARIABLES
flow in
Hs
H
LC
flow out
OUTFLOW: INPUT FOR CONTROL
INFLOW: DISTURBANCE
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BLOCK DIAGRAMS
d
FEEDBACK (measure output):
ys
Desired value
Setpoint
ys-ym Controller u
error
input (MV)
(brain)
ym
measured output
measured disturbance
d
Measurement
device
Controller
(brain)
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output (CV)
Measurement
device
FEEDFORWARD (measure disturbance):
dm
y
Process
(shower)
u
input (MV)
Process
(shower)
•All lines: Signals (information)
•Blocks: controllers and process
•Do not confuse block diagram (lines are signals) with flowsheet (lines are flows); see below
y
output (CV)
Most important control structures
1.
2.
3.
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Feedback control
Ratio control (special case of feedforward)
Cascade control
Process and instrumentation diagram (P&ID)
(flowsheet)
T
(measured CV)
Ts
(setpoint CV)
TC
MV (could be valve)
2nd letter:
C: controller
I: indicator (measurement)
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1st letter: Controlled variable (CV). What we are trying to control (keep constant)
T: temperature
F: flow
L: level
P: pressure
DP: differential pressure (Δp)
C: composition
X: quality
H: enthalpy/energy
Typical distillation control:
Two-point composition control
LV-configuration with inner T-loop
LV
CC
Ts
TC
CC
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xB
xD
Process dynamics (response)
• “Things take time”
•
Step response (step in u):
– k = Δy(∞)/ Δu – process gain
–  - process time constant (63%)
–  - process time delay
•
•
Time constant : Often equal to residence time = V[m3]/q[m3/s] (but not always!)
Can find  (and k) from balance equations:
–
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Rearrange to match standard form of 1st order linear differential equation:
Pairing of variables
Main rule: “Pair close”
The response (from input to output) should be fast, large and in one direction.
Avoid dead time and inverse responses!
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Model-based tuning (SIMC rule)
• From step response
– k = Δy(∞)/ Δu – process gain
–  - process time constant (63%)
–  - process time delay
• Proposed SIMC controller tunings
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k = Δy(∞)/ Δu
Process Control crash course (3 weeks):
1. Process operation: Why do we need process control?
2. Classification of variables (inputs, outputs, disturbances, measurements)
3. Feedback versus feedforward control
4. Block diagram representation (information diagrams, causality)
5. Flowsheet representation (process & instrumentation diagrams)
6. Single-loop control: Pairing of input and outputs
7. More advanced control: Ratio control, Cascade control,
8. The control hiearchy (optimization, advanced control, basic control)
9. Process dynamics (basics): first- and second order systems, time delay,
identification
10. Process modelling: balance principle
11. PID control and tuning
12. Simulation
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Control theory (11 weeks)
“standard course”
13. Laplace transforms, transfer functions
14. Closed-loop response, derivation of PID tuning rules
15. Pros and cons of high gain feedback. Stability. Change dynamics.
Biological systems
16. Dynamic systems (theory). poles, zeros, state space, observability,
controllability
17. Control systems (theory), frequency analysis, stability conditions,
robustness
18. Controller implementation: discrete control, windup, bumpless transfer
19. Identification (theory)
20. Multivariable control: interactions, MPC
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+ 3. Practise
• LAB ?!!
– At least have demonstration
• SIMULATIONS ?!!
– Time consuming
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+ 4. Systems engineering
• General modelling principles, DAE-system
• Solution of dynamic models (integration)
• Linearization, State space models (deviation variables)
• Optimization
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Conclusion: Process systems engineering
(PSE) and process control
• Process control is a key course
– Engineers must know some control!
• Usually too little time to focus on systems issues
– Need advanced course to cover process systems
aspects of process control
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