Transcript Chemical Process Control

Chemical and Bio-Process Control
James B. Riggs
M. Nazmul Karim
Chapter 1
Introduction
A Career in Process Control
• Requires that engineers use all of their
chemical engineering training (i.e., provides
an excellent technical profession that can
last an entire career)
• Can become a technical “Top Gun”
• Allows engineers to work on projects that
can result in significant savings for their
companies (i.e., provides good visibility
within a company)
A Career in Process Control
• Provides professional mobility. There is a
shortage of experienced process control
engineers.
• Is a well paid technical profession for
chemical engineers.
Chemical Process Industries (CPI)
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Hydrocarbon fuels
Chemical products
Pulp and paper products
Agrochemicals
Man-made fibers
Bio-Process Industries
• Use micro-organisms to produce useful
products
• Pharmaceutical industry
• Ethanol from grain industry
Importance of Process Control for
the CPI
• PC directly affects the safety and reliability
of a process.
• PC determines the quality of the products
produced by a process.
• PC can affect how efficient a process is
operated.
• Bottom Line: PC has a major impact on the
profitability of a company in the CPI.
Safety and Reliability
• The control system must provide safe
operation
– Alarms, safety constraint control, start-up and
shutdown.
• A control system must be able to “absorb” a
variety of disturbances and keep the process
in a good operating region:
– Thunderstorms, feed composition upsets,
temporary loss of utilities (e.g., steam supply),
day to night variation in the ambient conditions
Benefits of Improved Control
Impurity
Concentration
Old Controller
Limit
Time
Benefits of Improved Control
Limit
Time
New Controller
Impurity
Concentration
Impurity
Concentration
Old Controller
Limit
Time
Better Control Means Products
with Reduced Variability
• For many cases, reduced variability
products are in high demand and have high
value added (e.g., feedstocks for polymers).
• Product certification procedures (e.g., ISO
9000) are used to guarantee product quality
and place a large emphasis on process
control.
Benefits of Improved Control
New Controller
Impurity
Concentration
Limit
Time
Limit
Time
Improved Performance
Impurity
Concentration
Impurity
Concentration
Old Controller
Limit
Time
Maximizing the Profit of a Plant
• Many times involves controlling against
constraints.
• The closer that you are able to operate to
these constraints, the more profit you can
make. For example, maximizing the
product production rate usually involving
controlling the process against one or more
process constraints.
Constraint Control Example
• Consider a reactor temperature control
example for which at excessively high
temperatures the reactor will experience a
temperature runaway and explode.
• But the higher the temperature the greater
the product yield.
• Therefore, better reactor temperature
control allows safe operation at a higher
reactor temperature and thus more profit.
Importance of Process Control for the
Bio-Process Industries
• Improved product quality.
• Faster and less expensive process validation.
• Increased production rates.
Driving a Car: An Everyday
Example of Process Control
• Control Objective (Setpoint): Maintain car in
proper lane.
• Controlled variable- Location on the road
• Manipulated variable- Orientation of the front
wheels
• Actuator- Driver’s arms/steering wheel
• Sensor- Driver’s eyes
• Controller- Driver
• Disturbance- Curve in road
Logic Flow Diagram for a
Feedback Control Loop
Disturbance
Setpoint
+-
e
Controller
c
u
Actuator
Sensor
Process
CV
Temperature Control for a Heat
Exchanger: ChE Control Example
Steam
Setpoint
TC
Product
Stream
TT
Feed
Condensate
Heat Exchanger Control
• Controlled variable- Outlet temperature of
product stream
• Manipulated variable- Steam flow
• Actuator- Control valve on steam line
• Sensor- Thermocouple on product stream
• Disturbance- Changes in the inlet feed
temperature
DO Control in a Bio-Reactor
Setpoint
AC
AT
Air
Variable Speed
Air Compressor
DO Control
• Controlled variable- the measured dissolved
O2 concentration
• Manipulated variable- air flow rate to the
bio-reactor
• Actuator- variable speed air compressor
• Sensor- ion-specific electrode in contact
with the broth in the bio-reactor
• Disturbance- Changes in the metabolism of
the microorganisms in the bio-reactor
Logic Flow Diagram for a
Feedback Control Loop
Disturbance
Setpoint
+-
e
Controller
c
u
Actuator
Sensor
Process
CV
Comparison of Driving a Car and
Control of a Heat Exchanger
• Actuator: Driver’s arm and steering wheel
vs. Control valve
• Controller: the driver vs. an electronic
controller
• Sensor: the driver’s eyes vs. thermocouple
• Controlled variable: car’s position on the
road vs. temperature of outlet stream
The key feature of all feedback control
loops is that the measured value of the
controlled variable is compared with
the setpoint and this difference is used
to determine the control action taken.
In-Class Exercise
• Consider a person skiing down a mountain.
Identify the controller, the actuator, the
process, the sensor and the controlled
variable. Also, indicate the setpoint and
potential disturbances. Remember that the
process is affected by the actuator to change
the value of the controlled variable.
Types of Feedback Controllers
• On-Off Control- e.g., room thermostat
• Manual Control- Used by operators and based on
more or less open loop responses
• PID control- Most commonly used controller.
Control action based on error from setpoint
(Chaps 6-8).
• Advanced PID- Enhancements of PID: ratio,
cascade, feedforward (Chaps 9-11).
• Model-based Control- Uses model of the process
directly for control (Chap 13).
Duties of a Control Engineer
• Tuning controllers for performance and
reliability (Chap 7)
• Selecting the proper PID mode and/or
advanced PID options (Chap 6, 10-12)
• Control loop troubleshooting (Chap 2 & 8)
• Multi-unit controller design (Chap 14)
• Documentation of process control changes
Characteristics of Effective
Process Control Engineers
• Use their knowledge of the process to guide
their process control applications. They are
“process” control engineers.
• Have a fundamentally sound picture of
process dynamics and feedback control.
• Work effectively with the operators.
Operator Acceptance
• A good relationship with the operators is a
NECESSARY condition for the success of a
control engineer.
• Build a relationship with the operators
based on mutual respect.
• Operators are a valuable source of plant
experience.
• A successful control project should make
the operators job easier, not harder.
Process Control and
Optimization
• Control and optimization are terms that are
many times erroneously interchanged.
• Control has to do with adjusting flow rates
to maintain the controlled variables of the
process at specified setpoints.
• Optimization chooses the values for key
setpoints such that the process operates at
the “best” economic conditions.
Optimization and Control of a CSTR
Optimizer
RSP
TC
RSP
Feed
FC
FV
CA0
FT
Steam
ABC
TT
Product
CA,CB, CC
Optimization Example
ABC
Mole balance on A :
Q C A0  Q C A  k1 exp[ E1 / RT ] C A Vr
Solving for C A
C A0
CA 
k1 exp[ E1 / RT ]Vr
1
Q
Likewise,C B andCC are calculatedfrom mole
balances.
Economic Objective Function
  Q CA VA  Q CB VB  Q CC VC  Q CA0 VAF
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VB > VC, VA, or VAF
At low T, little formation of B
At high T, too much of B reacts to form C
Therefore, the exits an optimum reactor
temperature, T*
Optimization Algorithm
• 1. Select initial guess for reactor
temperature
• 2. Evaluate CA, CB, and CC
• 3. Evaluate 
• 4. Choose new reactor temperature and
return to 2 until T* identified.
Graphical Solution of Optimum
Reactor Temperature, T*
Process Optimization
• Typical optimization objective function, :
 = Product values-Feed costs-Utility costs
• The steady-state solution of process models
is usually used to determine process
operating conditions which yields flow rates
of products, feed, and utilities.
• Unit costs of feed and sale price of products
are combined with flows to yield 
• Optimization variables are adjusted until 
is maximized (optimization solution).
Generalized Optimization
Procedure
Ini tial Esti mate
of O pti mi z ation
Variabl e s
O pti m iz ati on
Variabl e s
Proce ss
Mode l
Mode l
Re sul ts
Nu m e ri cal
O pti m iz ati on
Al gori thm
O pti m um
O pe ratin g
C on diti ons
Econ om ic
Fu ncti on
Val u e
Econ om ic
Fu ncti on
Eval u ati on
Econ om ic
Param e te rs
Optimization and Control of a CSTR
Optimizer
RSP
TC
RSP
Feed
FC
FV
CA0
FT
Steam
ABC
TT
Product
CA,CB, CC
In-Class Exercise
• Identify an example for which you use
optimization in your everyday life. List the
degrees of freedom (the things that you are
free to choose) and clearly define the
process and how you determine the
objective function.
Overview of Course Material
• Control loop hardware (Chap 2)
• Dynamic modeling (Chap 3)
• Transfer functions and idealized dynamic
behavior (Chap 4-6)
• PID controls (Chap 7-10)
• Advanced PID controls (Chap 12-14)
• Control of MIMO processes (Chap 15-18)
Fundamental Understanding and
Industrially Relevant Skills
• Fundamental Understanding– Laplace tranforms and transfer functions (Ch 4-5)
– Idealized dynamic behavior (Ch 6)
– Frequency response analysis (Ch 11)
• Industrially Relevant Skills–
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Control hardware and troubleshooting (Ch 2&10)
Controller Implementation and tuning (Ch 7-9)
Advanced PID techniques (Ch 12-14)
MIMO control (Ch 15-18)
Process Control Terminology
• Important to be able to communicate with
operators, peers, and boss.
• New terminology appears in bold in the text
• New terminology is summarized at the end
of each chapter.
• Review the terminology regularly in order
to keep up with it.
Overall Course Objectives
• Develop the skills necessary to function as
an industrial process control engineer.
– Skills
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Tuning loops
Control loop design
Control loop troubleshooting
Command of the terminology
– Fundamental understanding
• Process dynamics
• Feedback control
Overview
• All feedback control loops have a controller,
an actuator, a process, and a sensor where
the controller chooses control action based
upon the error from setpoint.
• Control has to do with adjusting flow rates
to maintain controlled variables at their
setpoints while for optimization the
setpoints for certain controllers are adjusted
to optimize the economic performance of
the plant.