A new book on advanced control fundamental will be published by ISA in September, 2012. This book addresses all the advanced control products that are included in the DeltaV control system or are planned for a future DeltaV release. In this session two of the authors present and discuss key areas addressed in the book and demonstrate web site that accompanies the book.

1. Advanced Control Foundation
- Tools & Techniques
Terry Blevins – Principal Technologist
Willy Wojsznis – Senior Technologist
Mark Nixon – Director, Research

2. Presenters
 Terry Blevins
 Willy Wojsznis

3. Introduction
 Over the last 10 years significant improvements made in
advanced control tool capabilities and in user interfaces,
improvements that make it easier to design and commission
advanced control solutions.
 Also since then, new advanced control applications have been
introduced for batch and continuous processes.
 The book Advanced Control Foundation – Tools, Techniques,
and Applications provides a fresh look at some of the latest
advanced control technologies that are available to the process
industry. A web site for the book allows the solutions to the
book’s workshops to be viewed using a web browser.

4. Areas to be Addressed
This session will focus on how advanced control technique may be
used to improve process operations. Areas that will be addressed
are:
 Maximizing Return on Control System Investment
 Evaluating Control System Performance
 On-demand Tuning
 Adaptive Tuning
 Fuzzy Logic Control
 Intelligent PID
 Neural Networks for Property Estimation
 Batch and Continuous Data Analytics
 Simple MPC
 MPC Integrated with Optimization
 On-line Optimization
 Process Simulation, Integrating Advanced Control Into a DCS

5. Basis for Presentation
 Material that will be presented
is based on Advanced Control
Foundation.
 This book was published in
Sept 2012 by ISA and
addresses the advanced
control products in the DeltaV
control system (or targeted for
a future DeltaV release).
 The book is available in the
ISA bookstore or may be
purchased on-line through ISA
- see

6. Basis for Presentation (Cont)
 The solution to workshop included in the book may be viewed using
your web browser- see http://www.advancedcontrolfoundation.com/

7. Maximizing Return on Control
System Investment
 By reduce process
variation, production
rate or quality
parameter targets
may be shifted. This
simple concept often
justifies control
upgrade.
 When target control
performance cannot
be achieved using
Single-loop PID
feedback and multi-
loop traditional control
techniques then
advanced control
techniques may be
required.

8. Example

9. Evaluating Control System
Performance
 The first step in
improving control
is to insure all
controls are
operating as
designed.
 Performance
monitoring tools
may be used to
quickly identify
when control is
not being utilized
i.e. control is on
manual.

10. Evaluating Control System
Performance (Cont)
 Report generation is
an important feature
of performance
monitoring tools.
 Reports can be used
to gain the
management
support that is
required to address
low control utilization
or to determine the
source of excessive
process variation
that impacts
production or
product quality.

11. Evaluating Control System
Performance (Cont)
 A plant equipped with
the latest control
systems and field
instrumentation may
still be found to have
low control utilization.
 Often the key to getting
control loops back on
automatic is for plant
management to be
aware of the low
control utilization and
its impact on product
quality and production
rate.

12. Resolving Problems that Impact
Control Utilization

13. On-demand Tuning
 Where low control
utilization is due to
PID tuning, then
On-demand tuning
may be used to
commission the
loop.
 Capturing process
dynamics in the
field (controller or
device) allows
better process
identification,
particularly for the
fastest loops.

14. On-demand Tuning (Cont)
 When using an on-
demand tuning
application,
consider that the
process gain may
change with the
operating
conditions.
 For robust control,
tuning should be
based on the
operating
conditions that
provide maximum
process gain.

15. Adaptive Tuning
 In some cases, the
tuning established
at one operating
point may not
provide the best
control for the full
operating range.
 Adaptive tuning
allows the process
gain and dynamics
to be automatically
identified and used
in control.

16. Viewing Identified Models

17. Predefined Fuzzy Logic Control
Function Block

18. Fuzzy Logic Control
 For some specific
process applications,
fuzzy logic control
enables faster setpoint
recovery with less
overshoot than PID
control for both
setpoint and load
changes
 Fuzzy logic is best
suited for controlling
processes
characterized by large
time constants and
little or no deadtime

19. Fuzzy Logic Control Workshop
Demo

20. Intelligent PID
Recovery From Process Saturation
 The PIDPlus provides
quicker recover from
process saturation.
 Also, the PIDPlus allow
the non-periodic, slow
measurement values
provided by a wireless
Control Using WirelessTransmitter device to be used in
closed loop control.

21. Compressor Surge Control

22. Compressor Surge Control (Cont)
Control Response with Preload Applied
Control Response with Variable Preload

23. Bioreactor with Wireless
Instrumentation

24. Neural Networks for Property
Estimation
 When a product quality
measurement is available
only from the lab, it is
often possible to use
upstream measurements
to calculate an estimated
value.
 To address the non-
linear response of
product quality
parameters to changes in
process inputs, the
estimator can be based
on a neural network
model.

25. Continuous Digester Example

26. Batch and Continuous Data Analytics
Through the use of on-line
data analytics, it is
possible to provide:
 Product quality
predictions which allow
quality problems to be
identified while there is
time to take corrections
action.
 Detection of abnormal
process operation
and/or equipment
problems and support
of root cause analysis

27. Continuous Example – Static Mixer

28. Batch Example

29. Simple MPC
MPC has proven
advantages over multi-loop
PID control techniques in a
variety of small applications
that are characterized by:
 Long process delay and
interaction,
 Measured disturbances
or constraints
 Production is limited by
process input(s)
 Embedded MPC
capability in the control
system.is an advantage

30. Replacing PID with MPC
One Measured Disturbance Input
MPC Constraint Control

31. MPC Integrated with Optimization
 For larger, more complex
applications that are used in
batch or continuous
processing, the plant
operation objective(s) may be
best met using MPC
integrated with optimization.
 Such applications are often
MEE Process
characterized by numerous
operating constraints and the
need to address broader
operating objectives, such as
maximizing throughput while
minimizing production costs
 Installation examples are
included in this chapter
CTMP Process

32. CTMP Refiner Process Step Response

33. On-line Optimization
 Examples are provided of
on-line LP (linear
programming) optimizer to
minimize the cost of power
generation.
 On-line operation was
achieved by using MPC with
an integrated optimizer;
however,the MPC
functionality was disabled.
 The economic benefits
achieved from on-line
optimization applications
indicate use of online
optimization will be
expanding in the coming
years.

34. Workshop for On-line Optimization

35. Process Simulation
 Dynamic process
simulation can be a
useful tool when working
with basic as well as
advanced control
techniques
 Such simulations can
easily be created using
the tools that exist in
most modern control
systems.
 The steps for developing
process simulations
starting with the P&ID
are described in detail.

36. Integrating Advanced Control Into a DCS
 When advanced control is embedded in the distributed control system
(DCS), the plant operator has a single window interface with consistent
system interaction and single log-in and span of control.
 If the DCS does not support advanced control, then the advanced control
applications must be layered onto the DCS. Several approaches may be
taken depending on the DCS support for layered applications.

37. Business Results Achieved
The economics of plant operation can be impacted by process
variation when production is limited by equipment capacity or when
maximum production and operating efficiency are achieved at a
specific operating condition.
 Through the application of advanced control techniques such as
performance monitoring, on-demand and adaptive tuning, fuzzy
logic control, intelligent PID, and MPC, it is often possible to
reduce variations in process operation and to shift and maintain
the plant to a more efficient point of operation.
 Data analytics may be used to improve batch and continuous
process operation through the on-line prediction of quality
parameter and fault detection.

38. Summary
Advanced control techniques and tools should be
considered when:
 The control objectives cannot be achieved through
the improvement of traditional control techniques.
 Traditional control strategies are more difficult to
maintain at optimal performance because of their
complexity.
Advanced control products are available as embedded
applications within modern process control systems or
as layered applications that may be added to older
control systems.

39. Where To Get More Information
 Web site for Advanced Control Foundation workshop Solutions
- see: http://www.advancedcontrolfoundation.com/
 Information on the Book
- see: http://modelingandcontrol.com/2012/08/advanced-
control-foundation-coming-soon/
 ISA Web Site on the Book
- see: http://modelingandcontrol.com/2012/09/advanced-
control-foundation-isa-web-site/