Control Using Two Manipulated Parameters

Terry Blevins – Principal Technologist and Greg McMillan – Principal Consultant

Presenters

§  Terry Blevins §  Greg McMillan

Introduction §  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.

§  §  § 

Concept and typical implementation Setup of I-only control in implementation Impact of mode/status, Example.

§  § 

How to implement in DeltaV Example

§  §  § 

Advantage if process has large deadtime, difference in dynamics Setup of MPC and MPC-Pro Blocks Example Applications

§  Valve Position Control

§  Combining Split Range and Valve Position Control §  Utilizing Predict/PredictPro for Control Using Two Manipulated Parameters

§  Summary §  References

Control Using Two Manipulated Parameters

One(1) Controlled Parameter

Controller SP Unmeasured Disturbance

§  Under specified problem that has multiple solutions for unlimited operation. Two(2) Manipulated §  Extra degree of freedom Parameters is used to achieve unique solution that satisfied specific control objective. §  Most common techniques are: split Process range, valve position control. §  Combination of these technique and MPC offer new capability to address this class of problems

Split Range – Traditional Implementation Temperature Example

TIC 101

4-20ma 3-15PSI

§  § 

IP 101

§ 

A/C

Cooling A/O

Process

TT 101

Heating 100 Valve Position (% of Span) 0

§  §  §  § 

Cooling Heating 3

IP Output ( PSI )

15

§ 

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

Split Range – Traditional Implementation pH Example

AIC 102

4-20ma 3-15PSI

IP 102

§  §  § 

PS 102

§  pH

A/O

A/O

Fine Valve

Process

AT 102

§  § 

Coarse Valve § 

100 Valve Position (% of Span)

Fine Valve Coarse Valve

0 3

I/P Output ( PSI ) 15

§ 

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

Split Range – DeltaV Implementation AI

PID

SPLT

AO AO

AI

PID

SPLT

AO AO

§  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.

Split Range Control in DeltaV

Splitter Block Calculation

IN_ARRAY Parameter §  The SP range associated with each output is defined by IN_ARRAY. §  SP range of outputs may be defined to overlap SP range associated with OUT1 SP range associated with OUT2

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

OUT_ARRAY Parameter §  When SP is outside defined range, then the value at the end of range is used to determine the output.

OUT1 Range for associated SP range

§  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.

Splitter Block OUT_1

100

0

OUT_2

OUT_ARRAY 0 100 0 100 IN_ARRAY 0 100 0 100

0

100 OUT_ARRAY 100 0 0 100 IN_ARRAY 0 40 35 100

100

0

100

0 100 LOCK_VAL “holds ”

HYSTVAL 0

LOCK_VAL “is zero ”

0

100

SP

OUT_ARRAY 0 100 0 100 IN_ARRAY 0 40 35 100

Heating-Cooing Example AI

PID

TT103

TIC103

SPLT FY103

AO IP103A

AO TIC 103 FY 103 IP 103A

HEATER

IP 103B COOLER

TT 103

IP103B

Split Range Output (FY103)

100

Valve Position (% of Span)

Cooling (IP103B) Heating (IP103A)

0 0

TIC103 Output (% of Span)

100

Steam Header Example AI

PID

PT104

PIC104

SPLT FY104

AO IP104A

AO IP104B

1475# Header

Boiler IP 104A

FY 104 IP 104B

400# Header

PIC 104

PT 104

Turbo Generato r

Split Range Output (FY104) - Capacity

100

Valve Position (% of Span)

Valve 104A Valve 104B

0 0

PIC104 Output (% of Span)

100

Basic Neutralizer Example AI

PID

AT105

AIC105

SPLT FY105

AO IP105A

AO IP105B

Reagent

IP 105A

Coarse Valve Fine Valve

IP 105B

FY 105 AIC 105

Neutralizer

AT 105

Discharge

pH Nonlinearity and Sensitivity pH

8 6

Reagent Flow Influent Flow

Split Range Output – Valve Sequencing

100

HYSTVAL Valve Position (% of Span)

Fine Valve (IP105B) Coarse Valve (IP105A)

0 0

AIC105 Output (% of Span)

100

Calculating Splitter SP Ranges 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%

§  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.

Testing Process to Determine Splitter SP Ranges Example: Slaker feed temperature controlled using heating and cooling valves Controlled Temperature

Heating

1.1degF

1%

Cooling

1% Time

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%

2.2degF

§  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

Example – Split Range

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

SP Small Valve

PID OUT PV

Large Valve

Split 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 Implementation pH Example

AIC 106

Mode Target Valve Position

IP 106A ZC 106

IP 106B

I-Only Controller

A/O Coarse Valve

§  PID control is implemented using the actuator with finer resolution or fastest impact on controlled parameter Fine Valve

Process

AT 106

pH Fine Valve

Coarse Valve Time

§  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. Target Valve Position

Valve Position Control – DeltaV Implementation AI

PID

AO I-Only

AI

PID

Fieldbus devices

Traditional field devices

AO I-Only

AO

AO

§  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.

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 IOnly regulation of slower responding or coarse resolution. PID configured for I-Only control

Configuring 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

Precise Flow Using Big/Small Valve AI

PID

FT107

FIC107

AO IP107A

I-Only ZC107

IP 107A

FIC 107 FT 107 ZC 107

IP 107B

AO IP107B

Neutralizer Using Valve Position Control AI

PID

AT108

AIC108

AO IP108A

IZC108 Only Reagent

IP 108B

Coarse Valve Fine Valve

IP 108A

AO IP108B

ZC 108

AIC 108 Neutralizer

AT 108

Discharge

Example -Boiler BTU Demand AI FT109B

AI

SUM

PID

FY109

FIC109

AO IP109A

IZC109 Only

FT109A

BTU Demand FY 109

FIC 109

IP 109A

FT 109B

FT 109A

HI BTU Fuel ZC 109

IP 109B

Low BTU – Waste Fuel

Boiler

AO IP109B

Example –Reformer Air Demand AI

PID

FT110

FIC110

AO IP110

ZC 110 SC 110

Air Machine

I-Only

AO

ZC110

SC110

FIC 110

Total Air Demand

IP 110 FT 110

Secondary Reformer

Example – Valve Position Control

Response to SP Change - Valve Position Control with Large Valve/Small Valve §  Target position for fine valve is 30%. PV SP Coarse Valve

Limite d

Fine Valve

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

Valve Position Control – Strengths and Weaknesses §  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 Split 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 Algorithm NORMAL SP

CAS_IN

FILTER_TC

T

-

+

x

OUT_1

Filter

-

x x

MODE

RANGE SPAN

OUT_2

Scaling

BKCAL_IN1 Balance Calculation BKCAL_IN2

BKCAL_OUT

Composite 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 Position and Split Range Control

Example: Response to SP Change §  Small change

Large 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

Composite for Valve Position/Split Range Control – 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 – Waste Fuel Boiler Control Steam Flow

Constraints ooo

MPC

Bark

Gas

Steam SP Steam Flow

20 Lo Cost Slow Waste Bark Hi Cost Fast Fuel Gas

Desired Response to unmeasured disturbance

§  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.

Example of Different Dynamic Response – Bleach Plant Control AT

MPC Hi Cost Fast Chemical 2 20 minutes

Lo Cost Slow Chemical 1

60 minutes

KAPPA SP KAPPA Lo Cost Slow Chemical 1 Hi Cost Fast Chemical 2

Desired response to unmeasured disturbance

§  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.

Utilizing 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

Maximize

optimization controlled variable variable

MPC

High Cost Fast Feed SP

Critical PV (normal PE)

Low Cost Slow Feed SP (lowered PE)

null

Low Cost Slow Feed SP

MPC 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 stickslip) 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 Configuration §  MPC block should be configured for two control and two manipulate parameters. §  The controlled measurement is wired to CNTRL1

DeltaV Predict Configuration (Cont)

§  CNTRL2 is configured as an optimized parameter Maximize (not wired)

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 Point Changes § 

Riding Max SP on Lo Cost MV Load Upsets

Riding Min SP on Hi Cost MV

Critical CV

Set Point Changes

Load Upsets Low Cost MV Maximum SP Increased

Critical CV

Set Point Changes

Low Cost MV Maximum SP Decreased

Lo Cost Slow MV Hi Cost Fast MV

§ 

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.

DeltaV PredictPro Configuration § 

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..

Control Parameter - MPC-Pro Block

Control 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 Point Changes

Riding Max SP on Lo Cost MV Load Upsets

Critical CV

Set Point 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 Min SP on Hi Cost MV Load Upsets

Low Cost MV Maximum SP Increased

Critical CV

Set Point Changes

Low Cost MV Maximum SP Decreased

Lo Cost Slow MV

Hi Cost Fast MV

Summary §  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 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.