adaptive control beta site feedback. [file name or event] emerson confidential 27-jun-01, slide 2...
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Adaptive Control Beta Site Adaptive Control Beta Site FeedbackFeedback
[File Name or Event]Emerson Confidential27-Jun-01, Slide 2
PresentersPresenters
• Peter Wojsznis
• Terry Blevins
• Bruce Johnson
• Clair Meger
Terry Chmelyk
[File Name or Event]Emerson Confidential27-Jun-01, Slide 3
IntroductionIntroduction
• DeltaV Adaptive Control Overview• Pre-beta and Internal Testing
– Solutia– UT Pickle Research – Fisher Controls
• Customer Beta Test– Husky Energy– Canfor– Eastman Chemical– Lubrizol– Results Achieved
• Summary • References
[File Name or Event]Emerson Confidential27-Jun-01, Slide 4
DeltaV Adaptive ControlDeltaV Adaptive ControlDeltaV Adaptive ControlDeltaV Adaptive Control
• Fully Adaptive Controller Tuning– PID Feedback and Feedforward
• Adapts to Changing Process– Identifies Process Dynamics While
In Automatic Control– Calculates optimal tuning
parameters– No Bump Tests Required
• Remembers Tuning for Different Operating Conditions
• Easy to Use – Out of the Box– Can be applied to all controllers
“Always in Control”
[File Name or Event]Emerson Confidential27-Jun-01, Slide 5
Beta Implementation - Adaptive ControlBeta Implementation - Adaptive ControlBeta Implementation - Adaptive ControlBeta Implementation - Adaptive Control
• New control block in the advanced control palette.
• Parameters are automatically assigned to the historian.
• No more difficult to use than PID.
• Initial values for model, limits, and time to steady state are automatically defaulted based on block tuning.
[File Name or Event]Emerson Confidential27-Jun-01, Slide 6
Adaptive Control - Internal StructureAdaptive Control - Internal StructureAdaptive Control - Internal StructureAdaptive Control - Internal Structure
Control
Process
Controller Redesign
Supervisor Model Evaluation
Model Par. Interpolation
Set of Models
PID Controller w/Dyn Comp Feedforward
Excitation Generator
Manipulate
Measured Disturbance
Adaptive Control Block
SP
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DeltaV Adaptive ControlDeltaV Adaptive ControlOperational FeaturesOperational Features
DeltaV Adaptive ControlDeltaV Adaptive ControlOperational FeaturesOperational Features
• Process models are automatically established for the feedback or feedforward paths.
• Model adaptation utilizes a data set captured after a setpoint change or injected pulse (Automatic Mode), or a significant change in the disturbance input change in controller output (manual Mode).
• Multiple models are evaluated and a new model is determined
[File Name or Event]Emerson Confidential27-Jun-01, Slide 8
Adapt Operating RegionsAdapt Operating RegionsAdapt Operating RegionsAdapt Operating Regions
• Adaptive control allows operating regions to be defined as a function of an input “state” parameter
• Define up to 5 regions• When the state parameter
changes from one region to another, the model values (and associated tuning) immediately change to the last model determined for the new region
• Limits on model parameter adjustment are defined independently for each region.
Model Parameters
State Parameter Value
Model Parameters
State Parameter Value
Region 1
Region 2
Region 3
Region 4
Region 5
Region 1
Region 2
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Triggering of IdentificationTriggering of IdentificationTriggering of IdentificationTriggering of Identification
• Operator SP change in control system will trigger the Adapt block to collect to create model
[File Name or Event]Emerson Confidential27-Jun-01, Slide 10
Viewing Latest Feedback ModelViewing Latest Feedback ModelViewing Latest Feedback ModelViewing Latest Feedback Model
[File Name or Event]Emerson Confidential27-Jun-01, Slide 11
Feedforward View – Dynamic CompFeedforward View – Dynamic CompFeedforward View – Dynamic CompFeedforward View – Dynamic Comp
Deadtime, Lead and Lag are also shown if Dynamic Compensation is selected in ADAPT_OPTS
[File Name or Event]Emerson Confidential27-Jun-01, Slide 12
Accessing Feedback Models by RegionAccessing Feedback Models by RegionAccessing Feedback Models by RegionAccessing Feedback Models by Region
• To access the last good model identified in each region of operation, then select Region and the Feedback tab.
• Value of state parameter
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Control Setup WindowControl Setup WindowControl Setup WindowControl Setup Window
• Trigger to adapt
• Controller Output pulse injection (used in phase 2 of beta)
• How fast to adapt
• Process type: Integrating – Non Integrating; Minimum time to steady state
• Adaptive mode of operation
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Common Causes of Uncertain or Bad ModelCommon Causes of Uncertain or Bad ModelCommon Causes of Uncertain or Bad ModelCommon Causes of Uncertain or Bad Model
• Actuator is sticking (coarse resolution) or has deadband.
• The measurement has uncertain or bad status.
• Initial Tuning for the existing loops or (manual entered) Time to Steady state is significantly off from the required value(s).
• Loop feedback and feedforward action (direct or reverse) is set incorrectly
• The identified model is outside the limits on process gain, time constant, and/or deadtime defined in the region view.
• State parameter is constantly switching between regions.
[File Name or Event]Emerson Confidential27-Jun-01, Slide 15
Actuator Deadband and ResolutionActuator Deadband and ResolutionActuator Deadband and ResolutionActuator Deadband and Resolution
• May be evident from trend plot. Also, reference the Health view to quantify deadband and/or resolution.
Deadband
Deadband and ResolutionDeadband and Resolution
[File Name or Event]Emerson Confidential27-Jun-01, Slide 16
Health ViewHealth ViewHealth ViewHealth View• Quantifies
deadband or resolution and Loop Oscillation
• May be configured to create a module alarm
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Adaptive Control Test ProgramAdaptive Control Test ProgramAdaptive Control Test ProgramAdaptive Control Test ProgramPre-Beta Sites• Solutia – Pensacola, FL, May, 2004 5 loops• J.J.Pickle Center, UT, Austin, TX Dec, 2004 3 loops
Internal Beta Sites• Fisher Control, Marshalltown, IA Sept, 2004• Rosemount, Eden Prairie and Chanhassen, MN March, 2005• Ovation, Pittsburgh, PENN April, 2005
Customer Beta Sites• Canfor – Prince George, CAN Feb, 2005 47 loops• Husky Energy – Prince George, CAN Feb, 2005 45 loops• Eastman Chemical – Longview, TX, Mar, 2005 147 loops• Lubrizol – Houston, TX 350 loops, April, 2005 350 loops
[File Name or Event]Emerson Confidential27-Jun-01, Slide 18
Pre-Beta – Solutia, Pensacola, FLPre-Beta – Solutia, Pensacola, FLPre-Beta – Solutia, Pensacola, FLPre-Beta – Solutia, Pensacola, FL
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Pre-Beta at Solutia, Pensacola, FLPre-Beta at Solutia, Pensacola, FLPre-Beta at Solutia, Pensacola, FLPre-Beta at Solutia, Pensacola, FL
LTTT TT
Cooling Tower Water
Cooling Tower Water
TC
TC
TT
TT
FT
FC
LC
AT
AC
HMD(Base)
65AC681(pH)
65TC68865TC684
65TC685
65LC682
Strike Kettle Process and Instrumentation
[File Name or Event]Emerson Confidential27-Jun-01, Slide 20
Pre-beta – Solutia, Pensacola, FLPre-beta – Solutia, Pensacola, FLPre-beta – Solutia, Pensacola, FLPre-beta – Solutia, Pensacola, FL
Kettle control – regular PID control
[File Name or Event]Emerson Confidential27-Jun-01, Slide 21
Pre-beta – Solutia, Pensacola, FLPre-beta – Solutia, Pensacola, FLPre-beta – Solutia, Pensacola, FLPre-beta – Solutia, Pensacola, FL
Kettle control – Adapt control
[File Name or Event]Emerson Confidential27-Jun-01, Slide 22
Pre-Beta at J.J Pickle Research CampusPre-Beta at J.J Pickle Research CampusPre-Beta at J.J Pickle Research CampusPre-Beta at J.J Pickle Research Campus
• DeltaV is installed at UT’s J.J. Pickle Research Campus, Austin, Texas on a 18”distillation column and 6” reactive distillation columns
• Emerson Process Management is:– Funding a PhD graduate student
under the guidance of Professor Tom Edgar to demonstrate and test DeltaV advanced control on the reactive column.
– Participating in a DOE project to explore a technique for early detection of column flooding – Professor Bruce Eldridge.
[File Name or Event]Emerson Confidential27-Jun-01, Slide 23
Pre-beta - J.J.Pickle Research CampusPre-beta - J.J.Pickle Research CampusPre-beta - J.J.Pickle Research CampusPre-beta - J.J.Pickle Research Campus
Flow loop
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Pre-beta - J.J.Pickle Research CampusPre-beta - J.J.Pickle Research CampusPre-beta - J.J.Pickle Research CampusPre-beta - J.J.Pickle Research Campus
Flow loop
[File Name or Event]Emerson Confidential27-Jun-01, Slide 25
Internal Beta – Fisher Controls, Internal Beta – Fisher Controls, Marshalltown, IAMarshalltown, IA
Internal Beta – Fisher Controls, Internal Beta – Fisher Controls, Marshalltown, IAMarshalltown, IA
[File Name or Event]Emerson Confidential27-Jun-01, Slide 26
Internal Beta – Fisher ControlsInternal Beta – Fisher ControlsInternal Beta – Fisher ControlsInternal Beta – Fisher Controls
[File Name or Event]Emerson Confidential27-Jun-01, Slide 27
Valve Installed Characteristics – Gain Valve Installed Characteristics – Gain Change of 7X Over Test RangeChange of 7X Over Test Range
Valve Installed Characteristics – Gain Valve Installed Characteristics – Gain Change of 7X Over Test RangeChange of 7X Over Test Range
[File Name or Event]Emerson Confidential27-Jun-01, Slide 28
Automated TestAutomated TestAutomated TestAutomated Test
[File Name or Event]Emerson Confidential27-Jun-01, Slide 29
Models Automatically Identified by RegionsModels Automatically Identified by RegionsModels Automatically Identified by RegionsModels Automatically Identified by Regions
[File Name or Event]Emerson Confidential27-Jun-01, Slide 30
Customer Beta Test ProgramCustomer Beta Test ProgramCustomer Beta Test ProgramCustomer Beta Test Program
• Phase 1 – first three months– Install beta system and provide initial training for instrumentation
and control
– Monitor the process models and recommended tuning that is automatically identified by DeltaV Adapt. No impact on operations
• Phase 2 – Second three months– Provide more extensive training for operators, instrumentation and
control, and management
– Commission adaptive closed loop control on some of the loops monitored in phase 1. Operators may operate adaptive loops using their normal interface to the control system.
[File Name or Event]Emerson Confidential27-Jun-01, Slide 31
Phase 1 ObjectivesPhase 1 ObjectivesPhase 1 ObjectivesPhase 1 Objectives
• Identify loops that must address changes in process gain and dynamics as a function of operating condition as indicated by PV, OUT or other measured parameters e.g. plant throughput
• Quantify process variability for existing PID control
[File Name or Event]Emerson Confidential27-Jun-01, Slide 32
Beta Implementation– DeltaV to Beta Implementation– DeltaV to DeltaVDeltaV
Beta Implementation– DeltaV to Beta Implementation– DeltaV to DeltaVDeltaV
Parameters Accessed Using OPC and Mirror
Application Station
[File Name or Event]Emerson Confidential27-Jun-01, Slide 33
Beta Module – DeltaV to DeltaVBeta Module – DeltaV to DeltaVBeta Module – DeltaV to DeltaVBeta Module – DeltaV to DeltaV
[File Name or Event]Emerson Confidential27-Jun-01, Slide 34
Pre-Configured Modules for Each SitePre-Configured Modules for Each Site Pre-Configured Modules for Each SitePre-Configured Modules for Each Site
[File Name or Event]Emerson Confidential27-Jun-01, Slide 35
Beta Implementation – DeltaV to ABBBeta Implementation – DeltaV to ABBBeta Implementation – DeltaV to ABBBeta Implementation – DeltaV to ABB
OPC I/F
ABB Controller
Parameters Accessed Using OPC and Mirror
ABB OPC Server
PID LoopPID
LoopPID Loop
Any ABBOperator Console
[File Name or Event]Emerson Confidential27-Jun-01, Slide 36
Beta Module – DeltaV to ABBBeta Module – DeltaV to ABBBeta Module – DeltaV to ABBBeta Module – DeltaV to ABB
[File Name or Event]Emerson Confidential27-Jun-01, Slide 37
Canfor, Northwood Mill, CanadaCanfor, Northwood Mill, CanadaCanfor, Northwood Mill, CanadaCanfor, Northwood Mill, Canada
• Beta addresses a wide variety of loops in the Pulping Group and Power House
• Beta system interfaces to existing Provox control system using OPC
[File Name or Event]Emerson Confidential27-Jun-01, Slide 38
Canfor –Loop Types AddressedCanfor –Loop Types AddressedCanfor –Loop Types AddressedCanfor –Loop Types Addressed
• 8 – Consistency
• 5 – Density
• 15 Level
• 5 pH
• 4 Pressure
• 10 Temperature
[File Name or Event]Emerson Confidential27-Jun-01, Slide 39
What have we learned so far?What have we learned so far?What have we learned so far?What have we learned so far?
• Seeing good model quality on self-regulating and integrating processes
• Very encouraged with the insights we are gaining about modeling dynamics across the operating range of the loops
• Model identification alone is a powerful tool for tuning or control design
• Health view has been enhanced and we are excited about the diagnostic capabilities for troubleshooting
[File Name or Event]Emerson Confidential27-Jun-01, Slide 40
B Digester Temperature Loop B Digester Temperature Loop B Digester Temperature Loop B Digester Temperature Loop
B Digester Temperature Loop
Gain change by factor of 10
TC change by factor of 3
DT change by factor of 2.5
[File Name or Event]Emerson Confidential27-Jun-01, Slide 41
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Husky Energy, Prince George, CanadaHusky Energy, Prince George, CanadaHusky Energy, Prince George, CanadaHusky Energy, Prince George, Canada
• Beta addresses all DeltaV loops implemented in the refinery
• Beta system interfaces to the DeltaV control system using OPC
[File Name or Event]Emerson Confidential27-Jun-01, Slide 43
Husky Energy - Initial ResultsHusky Energy - Initial ResultsHusky Energy - Initial ResultsHusky Energy - Initial Results
• Two(2) process control engineers and one(1) Norpac’s field support person attended training on DeltaV Adaptive control
• After the first full day of operation, DeltaV adaptive control automatically identified feedback and feedforward models for 25 of 42 loops based on typical operator changes in setpoint. Preliminary model evaluation indicates good match to the real process. Identification of remaining loops will continue over next 3 months.
• Monitoring will be extended to cover plant expansion for clean fuel production – may be an opportunity to quantify expected time that can be saved on new plant startup.
[File Name or Event]Emerson Confidential27-Jun-01, Slide 44
Husky Energy –Loop Types AddressedHusky Energy –Loop Types AddressedHusky Energy –Loop Types AddressedHusky Energy –Loop Types Addressed
• 12 – Flow
• 14 - Level
• 10 - Pressure
• 6 - Temperature
[File Name or Event]Emerson Confidential27-Jun-01, Slide 45
• 17-TIC-008 HP Receiver Condenser Temperature (A Fin Fan Cooler for the High Pressure Receiver)
• 20-LIC-001 Rich Amine Flash Tank • 23-FIC-023 Stabilizer Bottoms A/C Gasoline (Flow
Through an Air Cooler (A/C) from Stabilizer Tower)• 23-LIC-020 CGHT (Cat Gas Hydrotreater Treater)
Stabilizer Level• 23-PIC-173 HDS Reactor Heater Fuel Gas (Fuel
Pressure Control Loop • 23-PIC-179 Splitter Tower Heater Fuel gas (Fuel
Pressure Control Loop)• 23-TIC-123 Splitter Overhead Air Cooler Out (Fin fan
Control Loop)
Husky Energy – Some interesting loopsHusky Energy – Some interesting loopsHusky Energy – Some interesting loopsHusky Energy – Some interesting loops
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Eastman Chemical – Longview, TexasEastman Chemical – Longview, TexasEastman Chemical – Longview, TexasEastman Chemical – Longview, Texas
• Beta addresses a wide variety of loops in the hydrocarbon-cracking units, for the manufacture of solvents, alcohol, ethers, and polyethylene
• Beta system interfaces to existing DeltaV control system using OPC
[File Name or Event]Emerson Confidential27-Jun-01, Slide 51
Eastman –Loop Types AddressedEastman –Loop Types AddressedEastman –Loop Types AddressedEastman –Loop Types Addressed
• 39 Flow
• 50 Level
• 31 Pressure
• 24 Temperature
• 1 Position
[File Name or Event]Emerson Confidential27-Jun-01, Slide 52
Lubrizol – Deer Park, TexasLubrizol – Deer Park, TexasLubrizol – Deer Park, TexasLubrizol – Deer Park, Texas
• Beta addresses a wide variety of loops in continuous and batch processing in the manufacturing of lubricants
• Beta system interfaces to existing DeltaV and ABB control systems using OPC
[File Name or Event]Emerson Confidential27-Jun-01, Slide 53
Lubrizol –Loop AddressedLubrizol –Loop AddressedLubrizol –Loop AddressedLubrizol –Loop Addressed
• 180 Loops – DeltaV
• 170 Loops – ABB
[File Name or Event]Emerson Confidential27-Jun-01, Slide 54
Results – Automatic Model Identification in Results – Automatic Model Identification in First Two Months - Phase 1 of the beta testFirst Two Months - Phase 1 of the beta testResults – Automatic Model Identification in Results – Automatic Model Identification in First Two Months - Phase 1 of the beta testFirst Two Months - Phase 1 of the beta test
51%
3%10%
36% No Models
One Region
Two Regions
Three RegionsLubrizol – DeltaV
Control Network
14%
51%
19%
16%
Lubrizol – ABB Control Network
22%
14%
45%
19%
Canfor
39%
48%
12%1%
Eastman Chemical
12%
65%
21%2%
Husky Energy
[File Name or Event]Emerson Confidential27-Jun-01, Slide 55
SummarySummarySummarySummary
• The DeltaV adaptive control technology is being extensively tested at 4 customer beta sites and three internal sites within Emerson.
• Data on process variation and the identified process models has been collected on over 700 control loops.
• Process models have been automatically identified for a wide variety of loops. Performance improvement will be quantified in Phase 2 of the beta.
• Please direct questions or comments on the DeltaV Adaptive control products to John Caldwell ([email protected]).
[File Name or Event]Emerson Confidential27-Jun-01, Slide 56
Where To Get More InformationWhere To Get More InformationWhere To Get More InformationWhere To Get More Information
• “The Next Generation – Adaptive Control Takes a Leap Forward”. Gregory McMillan, Mark Sowell, Peter Wojsznis, Chemical Processing, September, 2004
• Utilizing DeltaV Adaptive Control (Presentation), Peter Wojsznis, Terry Blevins, Darrin Kuchle, Gregory McMillan, Willy Wojsznis, Emerson Exchange, 2004
• Theoretical Analysis of a Class of Multiple Model Interpolation Controllers (Presentation), Dale Seborg and Joao Hespanha, AIChE Annual Meeting, San Francisco, November 21, 2003
• “Adaptive Feedback/Feedforward PID controller”, Willy Wojsznis, Terry Blevins, and Peter Wojsznis, ISA Conference, 2003
• “User Interface For Adaptive Controller”, Peter Wojsznis, Yan Zhang, and Terrence L. Blevins, ISA Conference, 2003