1. Practical Industrial Process Control: Understanding, Tuning & Autotuning Control Loops
Edi Leksono
Department of Engineering Physics
Institut Teknologi Bandung
June 2003
Practical Industrial Process Control: Understanding, Tuning & Autotuning Control Loops
Introduction to Process Control

2. Training Objectives Introduction to process control
Elements of process control loop
Dynamic modelling
Analysis of dynamic systems
Design of P, PI, PD and PID for specific process objectives or product specifications
Design of feedback, feedforward, cascade, feedforward/feedback, feedforward/feedback + cascade controls
Tuning & Autotuning
Practical Troubleshooting
GOALS
Practical Industrial Process Control: Understanding, Tuning & Autotuning Control Loops
Introduction to Process Control

3. Road Map of the Training
First, we will visit all the block elements of the control system,especially the controller
Then, analyze the whole system all together
Then, consider the variations of the elements
Controller
Process
Sensor +
Transmitter +
Actuator
Practical Industrial Process Control: Understanding, Tuning & Autotuning Control Loops
Introduction to Process Control

4. Time Table Day Time Day 1 Day 2 Day 3 Day 4 Day 5 08.00-09.30
Opening,
Introduction to Industrial Process Control
PID Control I
Tuning Methods of PID Controller + Lab. III
Cascade Control I
Feedback/ Feedforward Control + Lab
Actuators
PID Control II
Autotuning Methods of PID Controller + Lab.
Cascade Control II + Lab.
Feedback/ Feedforward + Cascade Control + Lab
Sensor/Transmitter, Filtering
Tuning Methods of PID Controller + Lab. I
Practical Troubleshooting I
Feedforward Control I
Demo
Process Dynamic
Modelling
Tuning Methods of PID Controller + Lab. II
Practical Troubleshooting II
Feedforward Control II + Lab.
Final Test,
Closing
Practical Industrial Process Control: Understanding, Tuning & Autotuning Control Loops
Introduction to Process Control

5. Introduction to Process Control
Edi Leksono
Department of Engineering Physics
Institut Teknologi Bandung
June 2003
Introduction to Process Control

6. Session Outlines & Objectives
The importance of process control
Basic concepts of process control
Objectives
Understand what process control is
Know the terms of process control system
Identify the elements of process control system
Understand the importance of process control
Know the type of process control strategies
Introduction to Process Control

7. Definition (1) Process Control Process
A series of interrelated actions which transform material
It covers all resources that are involved in the process and talks about
process “inputs” (e.g. resources, raw material) and “outputs” (e.g.
finished product)
Control
To maintain desired conditions in a physical system by adjusting selected variables in the system
Process
Raw Materials
Products
Energies Out
Introduction to Process Control

8. Definition (2) Process Control
To maintain desired conditions in a physical system by adjusting selected variables in the system in spite of disturbances affecting the system and observation noise
Corrective Action
Knowledge
Data
Process
Information
Introduction to Process Control

9. Daylife Example: Driving a Car
Control Objective (Setpoint):
Maintain car in proper lane
Controlled variable:
Location on the road
Manipulated variable:
Orientation of the front wheels
Actuator:
Steering wheel
Sensor:
Driver’s eyes
Controller:
Driver
Disturbance:
Curve in road
Noise:
Rain, fog
Brain:
Control
calculation
Eyes:
Sensor
Steering wheel:
Actuator
Introduction to Process Control

10. Industrial Example #1: Heat Exchanger
Control Objective (Setpoint):
Maintain temperature
Controlled variable:
Outlet temperature of product stream
Manipulated variable:
Steam flow
Actuator:
Control valve on steam line
Sensor:
Thermocouple on product stream
Controller:
Temperature controller
Disturbance:
Changes in the inlet feed temperature
Noise:
Measurement noise
Feed
Condensate
Product
Stream
Steam TT TC
Introduction to Process Control

11. Industrial Example #2: Liquid Level Control
Control Objective (Setpoint):
Maintain level
Controlled variable:
Fluid level in the tank
Manipulated variable:
Fluid flow
Actuator:
Control valve on fluid line
Sensor:
Level transmitter on the tank
Controller:
Level controller
Disturbance:
Changes in the inlet feed flow
Noise:
Measurement noise
Fluid LT LC
Introduction to Process Control

12. Elements of Process Control Loop
Sensor
Measure process variable
Transmitter
Convert the measured process variable into standard signal
Controller
Drive actuator by giving an appropriate controller output signal
Actuator
Adjust manipulated variable based on the value of the controller output signal
Process
Physical system to be controlled
Introduction to Process Control

13. The Terms I Control Objective (Setpoint, SP)
Controlled Variable (CV) or Process Variable (PV)
Measured Process Variable (PVm)
Controller Output (CO)
Manipulated Variable (MV)
Final Control Element (Actuator)
Sensor/Transmitter
Controller
Disturbance Variable (DV)
Measurement Noise
Introduction to Process Control

14. Goal of Process Operation
Safety & Reliability
Product Specification
Environmental Regulation
Operating Constraint
Efficiency
Maximum profit
24 hours process operation? Hmm… I think, to achieve those, we need to continuously monitor & control the process
24 hours a day,
7 days a week!!!
Introduction to Process Control

15. 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
Feed composition upsets, temporary loss of utilities (e.g., steam supply), day to night variation in the process
Introduction to Process Control

16. Product Specification
Quality
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
Old Controller
New Controller
Introduction to Process Control

17. Environmental Regulation
Various government laws may specify that the temperatures, concentrations of chemicals, and flow rates of the effluents from a process be within certain limit
Examples:
Regulations on the amounts of SO2 that a process can eject to the atmosphere, and on the quality of water returned to a river or a lake
Introduction to Process Control

18. Operational Constraint
All real process have constrained inherent to their operation which should be satisfied throughout the operation
Examples:
Tank should not overflow or go dry
Distillation column should not be flooded
Catalytic reactor temperature should not exceed an upper limit since the catalyst will be destroyed
Introduction to Process Control

19. Efficiency
The operation of a process should be as economical as possible in utilization of raw material, energy and capital
Introduction to Process Control

20. Maximizing the Profit of a Plant (1)
The operation of a process may many times involves controlling against constraints
The closer that you are able to operate to these constraints, the more profit you can make
Example:
Maximizing the product production rate usually involving controlling the process against one or more process constraints
Introduction to Process Control

21. Maximizing the Profit of a Plant (2)
Constraint control example: A reactor temperature control
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
New Controller
Improved Performance
Introduction to Process Control

22. The History of Process Control
1960s Pneumatic analog instrumentation, controllers, and computing modules
1970s Electronic analog instrumentation, controllers, and computing modules
Direct digital control with special algorithms programmed in main frame computer
1980s Electronic analog instrumentation and digital distributed control systems (DCS)
Supervisory and model predictive control configured in special purpose computers
1990s Smart analog instrumentation, valves, and digital distributed control systems
Neural networks, online diagnostics, and expert systems in special purpose computers
Real time optimization using model libraries in special purpose computers
2000s Field bus based digital smart instrumentation, valves, and control systems
Digital bus takes full advantage of smartness and accuracy of instrumentation and valves
Some fast PID controllers such as flow and pressure go to the field transmitter or valve
Model predictive control, neural networks, online diagnostics, and expert systems are integrated into the graphically configurable field bus based control systems and move to PCs
APC Infrastructure, interface, and engineering costs decrease by an order of magnitude
APC projects use consultants more for front end and commissioning than for whole job
APC software tools are easy enough for the average process and control engineer to use
Introduction to Process Control

23. Common Types of Control Strategy
Manual vs. Automatic
Servo vs. Regulator
Open-loop vs. Closed-loop
Control strategies
Feedback Control
Feedforward Control
Cascade Control
Single-Input Single-Output (SISO) vs. Multi-Input Multi-Output (MIMO, also known as multivariable)
Introduction to Process Control

24. Manual vs. Automatic Manual Automatic
Human has to adjust the MV to obtain the desired value of the PV based on observation and prior experiences
Automatic
The computer (or other device) autonomously controls the process and may report status back to a operator
Emergency cooling
Temperature indicator
Should I adjust
the valve or
should I run?
Question: Why manual override has to be included in every automatic control systems?
Introduction to Process Control

25. Regulator vs. Servo Servo control Regulatory control
Follow constant setpoint, overcoming the disturbance
Servo control
Follow the changing setpoint
75.5 C…
75.3 C…
75.4 C… o
7.00 AM: C…
8.00 AM: C…
9.00 AM: C… o
Question: How to achieve both objectives simultaneously?
Introduction to Process Control

26. Open-loop vs. Closed-loop
Process is controlled based on predetermined scenario
Ex.: When food is done in an oven, timers on outdoor lights
Closed-loop
The information from sensor is used to adjust the MV to obtain the desired value of the PV DV PV CO
Process
Decisions
Controller SP DV PV CO
Decisions
Controller
Process SP
Introduction to Process Control

27. Control Strategies (1) Feedback Control Feedback Process Controller
Corrective action based on process variable (PV)
Advantage
Requires no knowledge of the source or nature of disturbances, and minimal
detailed information about how the process itself works
Disadvantage
Controller takes some corrective actions after some changes occurs in process
variable PV DV SP PV
Feedback
Controller CO
Process
Introduction to Process Control

28. Control Strategies (2) Feedforward Control Feedforward Process
Based on the measurement of disturbance (DV)  feedforward controller can respond even before any changes occurs in PV
Advantage
Controller takes some corrective actions before the process output is different
from the setpoint  theoretically, perfect disturbance rejection is possible!
Disadvantage
Requires process model which can predict the effect of disturbance on PV
If there are some modeling error, feedforward control action will be erroneous (no corrective action)
Feedforward controller can be quite complex DV SP PV CO
Feedforward
Controller
Process
Introduction to Process Control

29. Control Strategies (3) Feedback/Feedforward Control Process
Feedforward controller will adjust CO as soon as the DV is detected
If the feedforward action is not enough due to model error, measurement error and etc., feedback controller will compensate the difference DV SP PV CO
Feedforward/
Feedback
Controller
Process
Introduction to Process Control

30. Control Strategies (4) Cascade Control
The disturbance DV1 arising within the inner loop are corrected by the inner controller before it can affects the PV of the outer one
Example: Control valve + positioner DV SP PV CO
Outer Feedback
Controller
Inner Feedback
Inner
Process
Outer
DV1
Inner loop
Outer loop
Introduction to Process Control

31. Control Strategies (5) Feedback/Feedforward + Cascade Control CODV SP PV CO
Outer Feedback
Controller
Inner Feedback
Inner
Process
Outer
DV1
Inner loop
Outer loop
Introduction to Process Control

32. SISO vs. MIMO
Based on how many PV and MV we have in a process
SISO
MIMO
DVs
PVs
COs
Decisions
Controller
Process … DV PV CO
Decisions
Controller
Process
Introduction to Process Control

33. Performances of Process Control System1
Closeness to setpoint
Short transient to one setpoint to other setpoint
Smaller overshoot and less oscillation
Smooth and minimum changes of variable manipulation
Minimum usage of raw materials and energy 2 2
1, 2
1, 2 1
Regulator
Servo 2
Introduction to Process Control

34. The Terms II Manual control Automatic control Open-loop control
Closed-loop control
Feedback control
Feedforward control
Cascade control
Servo control
Regulatory control
SISO control
MIMO control
Transient response
Overshoot
Oscillation
Introduction to Process Control

35. Development of a Control System (1)
Open Loop Analysis
What kind of system is considered?
Performance Specifications
How is the system required to behave?
The desired performance must be expressed in terms of the different performance measures that are chosen
Often, depends on the type of control problem to solve
Control Configuration
Which signals are used to calculate the control signal?
Depending on the plant the desired performance specifications and the allowed complexity of the control system
Depending on the type and the number of input signals to the controller different configurations are recognized
Introduction to Process Control

36. Development of a Control System (2)
Control Law
Which algorithm is used to calculate the control signal?
Parameter Design (Tuning)
Which are the parameters of the algorithm to calculate the control signal?
Evaluation
How will the controlled system behave in theory?  simulation!
Implementation and Verification
How will the control system be realized?
How does the controlled system behave in practice?
The controller will be implemented and one will verify whether the system is controlled as expected
Introduction to Process Control

37. The Terms III Control law (algorithm) Parameter design (tuning)
Computer simulation
Introduction to Process Control

38. Session Summary
Control has to do with adjusting manipulated variables of the process to maintain controlled variables at desired values
All control loops have a controller, an actuator, a process, and a sensor/transmitter
Various controller strategies can be realized to achieve desired process objectives & product specifications
Introduction to Process Control