chap01
TRANSCRIPT
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Chemical and Bio-Process Control
James B. Riggs
M. Nazmul Karim
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Chapter 1
Introduction
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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)
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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.
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Chemical Process Industries (CPI)
• Hydrocarbon fuels
• Chemical products
• Pulp and paper products
• Agrochemicals
• Man-made fibers
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Bio-Process Industries
• Use micro-organisms to produce useful products
• Pharmaceutical industry
• Ethanol from grain industry
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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.
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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
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Benefits of Improved Control
Time
Impu
rity
C
once
ntra
tion Limit
Old Controller
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Benefits of Improved Control
Time
Impu
rity
C
once
ntra
tion Limit
Time
Impu
rity
C
once
ntra
tion Limit
Old Controller New Controller
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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.
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Benefits of Improved Control
Time
Impu
rity
C
once
ntra
tion Limit
Time
Impu
rity
C
once
ntra
tion Limit
Time
Impu
rity
C
once
ntra
tion Limit
Old Controller New Controller
Improved Performance
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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.
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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.
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Importance of Process Control for the Bio-Process Industries
• Improved product quality.
• Faster and less expensive process validation.
• Increased production rates.
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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
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Logic Flow Diagram for a Feedback Control Loop
Controller Actuator Process
Sensor
CVSetpoint
Disturbance
+-uce
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Temperature Control for a Heat Exchanger: ChE Control Example
TT
Condensate
Steam
Feed
TCProductStream
Setpoint
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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
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DO Control in a Bio-Reactor
Air
AC
Variable SpeedAir Compressor
AT
Setpoint
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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
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Logic Flow Diagram for a Feedback Control Loop
Controller Actuator Process
Sensor
CVSetpoint
Disturbance
+-uce
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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
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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.
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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.
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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).
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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
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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.
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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.
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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.
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Optimization and Control of a CSTR
TC
Feed
Product
TTSteam
FC
RSP
OptimizerRSP
FT
FVCA0
CA,CB, CC
ABC
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Optimization Example
balances.
molefromcalculatedareandLikewise,
]/exp[1
forSolving
]/exp[
:AonbalanceMole
11
0
110
CB
r
AA
A
rAAA
CC
QVRTEk
CC
C
VCRTEkCQCQ
CBA
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Economic Objective Function
AFACCBBAA VCQVCQVCQVCQ 0
• 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*
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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.
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Graphical Solution of Optimum Reactor Temperature, T*
-0.5
0
0.5
1
1.5
2
250 275 300 325 350
Reactor Temperature (K)
Eco
nom
ic O
bjec
tive
F
unct
ion,
T *
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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).
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Generalized Optimization Procedure
NumericalOptimization
Algorithm
ProcessModel
EconomicParameters
EconomicFunction
Evaluation
OptimizationVariables
EconomicFunction
Value
ModelResults
Initial Estimateof Optimization
Variables
OptimumOperatingConditions
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Optimization and Control of a CSTR
TC
Feed
Product
TTSteam
FC
RSP
OptimizerRSP
FT
FVCA0
CA,CB, CC
ABC
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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.
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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)
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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-– 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)
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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.
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Overall Course Objectives
• Develop the skills necessary to function as an industrial process control engineer.– Skills
• Tuning loops
• Control loop design
• Control loop troubleshooting
• Command of the terminology
– Fundamental understanding• Process dynamics
• Feedback control
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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.