control using two manipulated parameters terry blevins (principal technologist) and greg mcmillan...

Control Using Two Manipulated Control Using Two Manipulated Parameters Parameters

Terry Blevins (Principal Technologist) andGreg McMillan (Principal Consultant)

[File Name or Event]Emerson Confidential27-Jun-01, Slide 2

PresentersPresenters

• Terry Blevins

• Greg McMillan


IntroductionIntroduction• Overview – Typical Examples• Split-Range Control

– Concept, variations in implementation– Setup in field vs. Splitter Block and IO for each valve. – Using Splitter Block, Example.

• Valve Position Control– Concept and typical implementation– Setup of I-only control in implementation – Impact of mode/status, Example.

• Combining Split Range and Valve Position Control– How to implement in DeltaV– Example

• Utilizing Predict/PredictPro for Control Using Two Manipulated Parameters– Advantage if process has large deadtime, difference in dynamics– Setup of MPC and MPC-Pro Blocks– Example Applications

• Summary• References


Control Using Two Manipulated ParametersControl Using Two Manipulated ParametersControl Using Two Manipulated ParametersControl Using Two Manipulated Parameters

• Under specified problem that has multiple solutions for unlimited operation.

• Extra degree of freedom is used to achieve unique solution that satisfied specific control objective.

• Most common techniques are: split range, valve position control.

• Combination of these technique and MPC offer new capability to address this class of problems

Controller Process

SP

Unmeasured Disturbance

One(1) Controlled Parameter

Two(2) Manipulated Parameters


Split Range – Traditional Implementation Split Range – Traditional Implementation Split Range – Traditional Implementation Split Range – Traditional Implementation

IP101

TT101

TIC101

Process

• Sequencing of valve accomplished through calibration of positioner, selection of actuator (A/O or A/C)

• Pro – Less expensive installation (1 pair of wires to field and 1 I/P)

• Con – You are not using the best technology for valve performance (e.g. digital positioners).

• Con -Difficult to initially calibrate and continuously improve to get best gap and most constant gain.

• Con -Individual valves not accessible for trouble shooting loop and actuator/valve problem.

• Con – The actuator, pneumatic positioner, and I/P performance shift with time and field conditions

• Con – I/P failure disables 2 valves• Con - Replacements in the night

may not have the special settings

Temperature Example

4-20ma

Heating

Cooling

3-15PSI

ValvePosition(% of Span)

IP Output ( PSI )153

0

100

Cooling

Heating

A/C

A/O


Split Range – Traditional ImplementationSplit Range – Traditional ImplementationSplit Range – Traditional ImplementationSplit Range – Traditional Implementation

• Sequencing of fine and coarse valve requires pressure switch, two solenoid valves and associated wiring and tubing

• Con – Complex installation • Con – You are not using the best

technology for valve performance (e.g. digital positioners).

• Con -Difficult to initially calibrate and continuously improve to get best gap and most constant gain.

• Con -Individual valves not accessible for trouble shooting loop and actuator/valve problem.

• Con – The switch, actuator, pneumatic positioner, and I/P performance shift with time and field conditions

• Con – I/P failure disables 2 valves• Con - Replacements in the night

may not have the special settings

IP102

AT102

AIC102

Process

pH Example

4-20ma

Coarse Valve

Fine Valve

3-15PSI

A/O

pH


I/P Output ( PSI ) 1530

100

Fine ValveCoarse Valve

A/O

PS102


Split Range – DeltaV Implementation Split Range – DeltaV Implementation Split Range – DeltaV Implementation Split Range – DeltaV Implementation • Splitter bock is used

to implement split range control.

• When using traditional valves, split range control may implemented in DeltaV Controller using two(2) current outputs

• Split range control may be partially or fully assigned to fieldbus devices.

AI PID SPLT

AO

AO

AI PID SPLT

AO

AO


Split Range Control in DeltaVSplit Range Control in DeltaVSplit Range Control in DeltaVSplit Range Control in DeltaV


Splitter Block CalculationSplitter Block CalculationSplitter Block CalculationSplitter Block Calculation


IN_ARRAY ParameterIN_ARRAY ParameterIN_ARRAY ParameterIN_ARRAY Parameter

• The SP range associated with each output is defined by IN_ARRAY.

• SP range of outputs may be defined to overlap

• The SP upper end of range must be greater that lower end of range for each output

SP range associated with OUT1

SP range associated with OUT2


OUT_ARRAY ParameterOUT_ARRAY ParameterOUT_ARRAY ParameterOUT_ARRAY Parameter

• When SP is outside defined range, then the value at the end of range is used to determine the output.

• LOCKVAL determines if OUT1 value is held if SP is greater that the upper end of range defined for OUT1.

• No restrictions are placed on the output range.

OUT1 Range for associated SP range


Splitter BlockSplitter BlockSplitter BlockSplitter Block

SP

0 1000

100

0

100

0

100

100

100

0

0

OUT_1

OUT_2

LOCK_VAL “holds”

LOCK_VAL “is zero”

OUT_ARRAY 0 100 0 100

IN_ARRAY 0 100 0 100

OUT_ARRAY 100 0 0 100

IN_ARRAY 0 40 35 100

OUT_ARRAY 0 100 0 100

IN_ARRAY 0 40 35 100HYSTVAL


AI PID SPLT

AO

AO

IP103A IP

103B TT103

FY103

TIC103

COOLERHEATER

TT103 TIC103 FY103 IP103A

IP103B

Heating-Cooing ExampleHeating-Cooing ExampleHeating-Cooing ExampleHeating-Cooing Example



TIC103 Output (% of Span)1000

0

100

Cooling (IP103B)

Heating (IP103A)

Split Range Output (FY103)Split Range Output (FY103)Split Range Output (FY103)Split Range Output (FY103)


AI PID SPLT

AO

AO

IP104A

IP104B

PT104

FY104

PIC104

PT104 PIC104 FY104 IP104A

IP104B

Steam Header ExampleSteam Header ExampleSteam Header ExampleSteam Header Example

400# Header

1475# HeaderBoiler

Turbo Generator



PIC104 Output (% of Span)1000

0

100

Valve 104A

Valve 104B

Split Range Output (FY104) - CapacitySplit Range Output (FY104) - CapacitySplit Range Output (FY104) - CapacitySplit Range Output (FY104) - Capacity


Basic Neutralizer ExampleBasic Neutralizer ExampleBasic Neutralizer ExampleBasic Neutralizer Example

Neutralizer

Discharge

Reagent

AI PID SPLT

AO

AOAT105 AIC105 FY105 IP105A

IP105B

AIC105

AT105

IP105B

FY105

IP105A

Coarse Valve

Fine Valve


pH Nonlinearity and SensitivitypH Nonlinearity and SensitivitypH Nonlinearity and SensitivitypH Nonlinearity and Sensitivity

pH

Reagent FlowInfluent Flow

6

8


Split Range Output – Valve SequencingSplit Range Output – Valve SequencingSplit Range Output – Valve SequencingSplit Range Output – Valve Sequencing


AIC105 Output (% of Span)1000

0

100

Fine Valve (IP105B)

Coarse Valve (IP105A)

HYSTVAL


Calculating Splitter SP RangesCalculating Splitter SP RangesCalculating Splitter SP RangesCalculating Splitter SP Ranges• A 1% change in controller

output to the splitter should have the same impact on control parameter when operating with either valve.

• When manipulating the same or similar material e.g. steam flow to header, then the range may be calculated based on valve rating.

• Tests may be performed to determine impact of each valve on the controlled parameter.

Example: Steam flow to Header, splitter interfacing directly to PRV’s, no overlap

Valve 1 rating = 50kph

Valve2 rating = 150kph

Desired Splitter Span valve 1 = 100*(50/(150+50)) = 25%

SP range for valve 1 = 0-25%

SP range for valve 2 = 25-100%


Testing Process to Determine Testing Process to Determine Splitter SP RangesSplitter SP Ranges

Testing Process to Determine Testing Process to Determine Splitter SP RangesSplitter SP Ranges

• With the process at steady state and AO’s in Auto mode, determine the magnitude of change in the controlled parameter for a 1 percent change in each valve.

• Calculate the splitter SP span and range for each output based on the observed response

Time

Cooling

Heating 1%

1%

1.1degF 2.2degF

Desired Splitter Span cooling valve = 100*(1.1/(1.1+2.2)) = 33%

SP range for cooling valve = 0-33%SP range for heating valve = 33-100%

Controlled Temperature

Example: Slaker feed temperature controlled using heating and cooling valves


Example – Split RangeExample – Split RangeExample – Split RangeExample – Split Range


Response to SP Change – Split Range Response to SP Change – Split Range Output To Large Valve/Small ValveOutput To Large Valve/Small Valve

Response to SP Change – Split Range Response to SP Change – Split Range Output To Large Valve/Small ValveOutput To Large Valve/Small Valve

Small Valve

Large Valve

PID OUT

SP

PV


Split Range – Strengths and WeaknessesSplit Range – Strengths and WeaknessesSplit Range – Strengths and WeaknessesSplit Range – Strengths and Weaknesses

• Pro - Process operation in simplified since two actuators are treated as one control manipulated parameter.

• Pro – immediate change in target actuator position can be achieved over the entire operating range independent of the size of change in the splitter SP

• Con – To achieve stable control over the entire operating range, Controller tuning must be established based on the slower responding manipulated parameter.

• Con- Does not take advantage of difference in resolution of actuator e.g. fine vs. coarse valve.

• Valve position control may be used in place of split range control when there are differences in dynamic response or resolution in actuators.


Valve Position Control – Traditional Valve Position Control – Traditional Implementation Implementation

Valve Position Control – Traditional Valve Position Control – Traditional Implementation Implementation

IP106A

AT106

AIC106

Process

• PID control is implemented using the actuator with finer resolution or fastest impact on controlled parameter

• The actuator with coarse resolution or slower impact on the controlled parameter is adjusted by an I-only controller to maintain the long term output of the PID controller at a given target

• I-Only controller must be disabled when the PID controller is not in an Automatic mode.

pH Example

Fine Valve

A/O

ZC106

IP106B

Coarse Valve

I-Only Controller

Mode

Target Valve Position

Time

pH

Fine Valve

Coarse ValveTarget Valve Position


Valve Position Control – DeltaV Valve Position Control – DeltaV Implementation Implementation

Valve Position Control – DeltaV Valve Position Control – DeltaV Implementation Implementation

• I-Only control is achieved by configuration of the PID Block STRUCTURE, GAIN and RESET parameters.

• It is possible to implement valve position control in the DeltaV controller or for this function to be distributed to fieldbus devices.

AI PID AO

AI PID

AO

AO

I-Only AO

I-Only

Traditional field devices

Fieldbus devices


Valve Position Control in DeltaV Valve Position Control in DeltaV Valve Position Control in DeltaV Valve Position Control in DeltaV

• Actuator with fastest impact or highest resolution is used to maintain the controlled parameter at setpoint.

• The OUT of the PID used for control is wired to IN on the PID block used for I-Only regulation of slower responding or coarse resolution.

PID configured for I-Only control


Configuring PID for I-Only ControlConfiguring PID for I-Only ControlConfiguring PID for I-Only ControlConfiguring PID for I-Only Control

• The STRUCTURE parameter should be configured for “I action on Error, D action on PV”

• The GAIN should be set to 1 to allow normal tuning of RESET (even though proportional action is not implemented.

• RESET should be set significantly slower than that the product of the PID gain and reset time used for control e.g. 5X slower


AI PID AO

IP107A

IP107B

FT107

FIC107

FT107 FIC107IP107A

Precise Flow Using Big/Small ValvePrecise Flow Using Big/Small ValvePrecise Flow Using Big/Small ValvePrecise Flow Using Big/Small Valve

ZC107

I-Only AOIP107B

ZC107


Neutralizer Using Valve Position ControlNeutralizer Using Valve Position ControlNeutralizer Using Valve Position ControlNeutralizer Using Valve Position Control

Neutralizer

Discharge

Reagent

AIC108

AT108

IP108A

IP108B

Coarse Valve

Fine Valve

AI PID AOAT108 AIC108

IP108A

ZC108

I-Only AOIP108B

ZC108


Example -Boiler BTU DemandExample -Boiler BTU Demand Example -Boiler BTU DemandExample -Boiler BTU Demand

ZC109

FT109A

IP109B

AI PID AOFT109B FIC109

IP109A

ZC109

I-Only AOIP109B

FIC109

FT109B

IP109A

FY109

Low BTU – Waste Fuel

HI BTU Fuel Boiler

BTU Demand

AIFT109A

SUM

FY109


Example –Reformer Air DemandExample –Reformer Air Demand Example –Reformer Air DemandExample –Reformer Air Demand

ZC110

AI PID AOFT110 FIC110

IP110

ZC110

I-Only AOSC110

FIC110

FT110

SC110

Air Machine

Secondary Reformer

Total Air Demand

IP110


Example – Valve Position ControlExample – Valve Position ControlExample – Valve Position ControlExample – Valve Position Control


Response to SP Change - Valve Position Response to SP Change - Valve Position Control with Large Valve/Small Valve Control with Large Valve/Small Valve

Response to SP Change - Valve Position Response to SP Change - Valve Position Control with Large Valve/Small Valve Control with Large Valve/Small Valve

Fine Valve

Coarse Valve

SP

PV

• Target position for fine valve is 30%.

• When the fine valve saturates, then response is limited to be reset of the I-Only control

Limited


Valve Position Control – Strengths and Valve Position Control – Strengths and WeaknessesWeaknesses

Valve Position Control – Strengths and Valve Position Control – Strengths and WeaknessesWeaknesses

• Pro – Immediate control response is based on actuator with finest resolution and/or faster impact on controlled parameter.

• Pro – Actuator with coarse resolution or slower impact on controlled parameter is automatically adjusted to maintain the output of the controller output long term at a specified operating point.

• Con – The controller output may become limited in response to a large disturbance or setpoint change. For this case, the dynamic response becomes limited by the slower tuning of the I-only controller.

• Con – Since stick-slip or resolution limits are a % of stroke, the big valve will go into a slow limit cycle

• The features of split range control and valve position control may be combined to provide immediate response to large changes in demand while retaining the features of valve position control for normal changes.


Combining the Best Features of Combining the Best Features of Split Range and Valve Position ControlSplit Range and Valve Position Control

Combining the Best Features of Combining the Best Features of Split Range and Valve Position ControlSplit Range and Valve Position Control

• A composite Block can be created that combines the features of split range and valve position control

• Support for BKCAL_IN and BKCAL_OUT can be implemented to provide bumpless transfer


Composite AlgorithmComposite AlgorithmComposite AlgorithmComposite Algorithm

Filter

CAS_IN

MODE

SPx +

x

x

T

ScalingRANGE SPAN

NORMAL

OUT_1

OUT_2

BKCAL_OUTBKCAL_IN1

BKCAL_IN2

Balance Calculation

-

-FILTER_TC


Composite ImplementationComposite ImplementationComposite ImplementationComposite Implementation• Parameters that

must be configure are: FILTER_TC, SPAN (of SP), RANGE (of OUT1), and NORMAL (desired position of

• The FILTER_TC should be configured similar to the reset time of the I-Only Controller that would be used for valve position control.


Demo – Composite Combining Valve Demo – Composite Combining Valve Position and Split Range ControlPosition and Split Range Control

Demo – Composite Combining Valve Demo – Composite Combining Valve Position and Split Range ControlPosition and Split Range Control


Example: Response to SP Change Example: Response to SP Change Example: Response to SP Change Example: Response to SP Change

SP, PV

OUT of PID

Fine Valve

Coarse Valve

• For small changes in SP or load disturbance, the response is similar to that provided by valve position control

• For large changes in SP or load disturbance, the immediate response is similar to split range control

Small change Large change


Composite for Valve Position/Split Range Composite for Valve Position/Split Range Control – Strengths and WeaknessesControl – Strengths and Weaknesses

Composite for Valve Position/Split Range Composite for Valve Position/Split Range Control – Strengths and WeaknessesControl – Strengths and Weaknesses

• Pro – All the advantage of valve position control without the dynamic limitations on large setpoint change or load disturbance.

• Con – If there is a significant delay in the control parameter response to changes in the two valves, then this limits the response that can be achieved using PID for the control .

• Model Predictive control automatically compensates for process dynamic and may be configured to provide the best features of valve position and split range control and can also address operating constraints.


Example of Different Dynamic Response – Example of Different Dynamic Response – Waste Fuel Boiler ControlWaste Fuel Boiler Control

Example of Different Dynamic Response – Example of Different Dynamic Response – Waste Fuel Boiler ControlWaste Fuel Boiler Control

• Objective: Maximize use of bark, only use gas when required to maintain Steam SP.

• Steam response to change in bark is much slower than for a change in gas.

• Bark alone may not be sufficient to address a sudden increase in steam demand.

o o o

MPC

Steam Flow Constraints

Bark Gas

Hi Cost FastFuel Gas

Lo Cost Slow Waste Bark

Steam Flow

Steam SP

20 Desired Response to unmeasured disturbance


Example of Different Dynamic Response – Example of Different Dynamic Response – Bleach Plant ControlBleach Plant Control

Example of Different Dynamic Response – Example of Different Dynamic Response – Bleach Plant ControlBleach Plant Control

• Objective: Maintain KAPPA target though the addition of Chemical 1 and Chemical 2. Minimize the use of Chemical 2.

• Desired operation is for Chemical 2 to be used for short term correction in KAPPA to replace Chemical 2 with Chemical 1 in the longer term.

AT

MPC

20 minutes

60 minutes

Lo Cost SlowChemical 1

Hi Cost Fast Chemical 2

Hi Cost Fast Chemical 2

Lo Cost SlowChemical 1

KAPPA

KAPPA SP

Desired response to unmeasured disturbance


Utilizing MPC for ControlUtilizing MPC for ControlUtilizing MPC for ControlUtilizing MPC for Control

• Both Predict and PredictPro can be configured and tuned for maintaining the critical controlled variable (CV), such as steam or composition, at its target and maximizing the low cost slow MV set point as an optimization variable.

manipulated variables

High Cost FastFeed SP

Critical PV(normal PE)

Low Cost SlowFeed SP

(lowered PE)

contr

olled

vari

able

Maximize

MPC Low Cost SlowFeed SP

null

opti

miz

ati

on

vari

able


MPC Guidelines for This ApplicationMPC Guidelines for This ApplicationMPC Guidelines for This ApplicationMPC Guidelines for This Application

• The best load and set point response for the critical CV is obtained with a short term tradeoff in efficiency by reducing the penalty on error (PE) for the optimization variable.

• When riding the low cost MV maximum set point, this PE lets both the slow and fast MV to move to improve the load and set point response of the critical CV.

• When riding the high cost MV low set point limit, it does not slow down the response of the other MV to upsets and set point changes to the critical CV. Only the response of the optimization variable is slowed down. This is consistent with the general theme that disturbance rejection must be fast while optimization can be slow.

• For coarse and fine valve control, the small valve is a low cost (low stick-slip) fast MV and the big valve is a high cost (high stick-slip) slow MV. The optimization variable is fine valve set point with a strategy of keeping it within limits (mid range throttle position). The PE for the optimization variable is reduced rather then the PM increased for the coarse valve so that both are available for load disturbance rejection.

• For the following examples, the slow MV has a lower cost, so its optimization strategy is maximization.


DeltaV Predict ConfigurationDeltaV Predict ConfigurationDeltaV Predict ConfigurationDeltaV Predict Configuration• MPC block

should be configured for two control and two manipulate parameters.

• The controlled measurement is wired to CNTRL1


DeltaV Predict Configuration (Cont)DeltaV Predict Configuration (Cont)DeltaV Predict Configuration (Cont)DeltaV Predict Configuration (Cont)

• CNTRL2 is configured as an optimized parameter - Maximize (not wired)


Control Generation - DeltaV Predict Control Generation - DeltaV Predict Control Generation - DeltaV Predict Control Generation - DeltaV Predict

• In Predict, the Penalty on Error (PE) is significantly decreased on the “Controller Generation” screen as shown in this example.

• The PE was lowered form 1.0 to 0.1 to make the optimization of the slow MV much less important than the control of the critical PV at its target


MPC Response to Disturbance and Set MPC Response to Disturbance and Set Point Changes Point Changes

MPC Response to Disturbance and Set MPC Response to Disturbance and Set Point Changes Point Changes

• In this example, low cost MV initially is riding its maximum set point, which leaves the fast cost MV free to respond

• Later, the maximum for the low cost MV has been increased to the point where it is no longer achievable, which drives the high cost MV to its low set point limit.

Riding Max SPon Lo Cost MV

Riding Min SPon Hi Cost MV

Critical CV

Lo Cost Slow MV

Hi Cost Fast MV

LoadUpsets

Set PointChanges

LoadUpsets

Set PointChanges

Low Cost MV Maximum SP Increased

Low Cost MV Maximum SP Decreased

Critical CV


• When configuring the MPC-Pro block, selects “Target” in the optimize column for the critical PV, and “Maximize” for the low cost MV.

• Browse to specify the RCAS_IN of the low cost slow MV (FC1-2) to specify the measurement associated with the low cost slow MV..

DeltaV PredictPro ConfigurationDeltaV PredictPro ConfigurationDeltaV PredictPro ConfigurationDeltaV PredictPro Configuration


Control Parameter - MPC-Pro BlockControl Parameter - MPC-Pro BlockControl Parameter - MPC-Pro BlockControl Parameter - MPC-Pro Block


Control Generation - DeltaV PredictProControl Generation - DeltaV PredictProControl Generation - DeltaV PredictProControl Generation - DeltaV PredictPro

• The Penalty on Error (PE) is significantly decreased on the “Controller Generation” screen

• In this example, the PE was lowered form 1.0 to 0.1 to make the optimization of the slow MV much less important than the control of the critical PV at its target.


MPC-Pro Response to Disturbance and Set MPC-Pro Response to Disturbance and Set Point ChangesPoint Changes

MPC-Pro Response to Disturbance and Set MPC-Pro Response to Disturbance and Set Point ChangesPoint Changes

• In this example, the low cost MV initially is riding its maximum set point, which leaves the fast cost MV free to respond

• Later, the maximum for the low cost MV has been increased so it is no longer achievable, which drives the high cost MV to its low set point limit.

Riding Max SPon Lo Cost MV

Riding Min SPon Hi Cost MV

Critical CV

Lo Cost Slow MV

Hi Cost Fast MV

LoadUpsets

Set PointChanges

LoadUpsets

Set PointChanges

Low Cost MV Maximum SP Increased

Low Cost MV Maximum SP Decreased

Critical CV


SummarySummarySummarySummary

• Split range control allows fully dynamic response to major setpoint of load disturbance changes. Valve position control may be used to takes advantage of any difference in control response or resolution in the manipulated parameters. A composite block has been demonstrated that combines the best features of split range and valve position control.

• DeltaV Predict and PredictPro and the associated MPC and MPC-Pro blocks may be effective used to address control using two manipulated parameters. Improved performance over PID is expected if the process has significant dead time or the manipulated variables have significantly different dynamics. Also, using this approach allow operating constraints and feedforward to be easily incorporated into the control strategy.

• Please direct questions or comments on this presentation to Terry Blevins ([email protected]) or Greg McMillan ([email protected] ).


Where To Get More InformationWhere To Get More InformationWhere To Get More InformationWhere To Get More Information

• “Effectively Addressing Control Applications”, Terry Blevins, Emerson Exchange, 2004.

• “Addressing Multi-variable Process Control Applications”, Dirk Thiele, Willy Wojsznis, Pete Sharpe, Emerson Exchange, 2004

• “Advanced Control Unleashed, Plant Performance Management for Optimum Benefit”. Terry Blevins, Gregory McMillan, Willy Wojsznis, Mike Brown, ISA Publication, ISBN 1-55617-815-8, 2003.

control using two manipulated parameters terry blevins (principal technologist) and greg mcmillan...

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