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Advanced Control Foundation
    - Tools & Techniques

  Terry Blevins – Principal Technologist
  Willy Wojsznis – Senior Technologist
    Mark Nixon – Director, Research
Presenters


    Terry Blevins



    Willy Wojsznis
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.
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
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
Basis for Presentation (Cont)
   The solution to workshop included in the book may be viewed using
    your web browser- see http://www.advancedcontrolfoundation.com/
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.
Example
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.
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.
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.
Resolving Problems that Impact
Control Utilization
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.
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.
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.
Viewing Identified Models
Predefined Fuzzy Logic Control
Function Block
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
Fuzzy Logic Control Workshop




Demo
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.
Compressor Surge Control
Compressor Surge Control (Cont)




   Control Response with Preload Applied




  Control Response with Variable Preload
Bioreactor with Wireless
Instrumentation
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.
Continuous Digester Example
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
Continuous Example – Static Mixer
Batch Example
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
Replacing PID with MPC




       One Measured Disturbance Input




              MPC Constraint Control
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
CTMP Refiner Process Step Response
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.
Workshop for On-line Optimization
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.
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.
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.
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.
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/

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Advanced control foundation tools and techniques

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