apc9 mon 16.35 experiences in building and maintaining mpc

7/23/2019 APC9 Mon 16.35 Experiences in Building and Maintaining MPC

http://slidepdf.com/reader/full/apc9-mon-1635-experiences-in-building-and-maintaining-mpc 1/34

Applied Manufactur ing Technologies AMT

APC9 069 – Experiences in building

and maintaining MPC

Advances in Process Control 9, York,September 2011



Process Performance Specialists AMT

What do AMT do? “Maximize client profitability through expert consulting

and successful advanced control and real-timeoptimisation technology implementation”

We‟re a service company providing technology expertise

throughout the chemical and refining industries

Maintain a “technology-independent” position

Maintain a high standard of practice and skill

Ensure our client‟s long term success by addressing

both application “peak performance” and long term

“average application performance”




AMT – a Global Services Company

Houston

UK

Barcelona

Seoul Tokyo

Expertise is leveraged globally as needed for specific engagements

Currently the most experienced & largest independent APC service group

in the world – approximately 500 man-years of experience, nearly 30 engineers




Areas of Expertise and Offerings Well Established APC

Deployment Capability PID tuning & configuration

APC Project implementation

Optimization Capability Full scope/Reduced scope

optimization implementations

Automated Plant Testing Significant experience in rapid

controller development

Strategy & feasibility studies

Performance reviews (postaudits)

Assistance in basic design ofregulatory control configuration

Troubleshooting processissues

Regulatory configuration andtuning course, Advanced APC

user courses Operator Training

Process and/or Technology ledtraining




Project Implementation Strategy “Process first, technology second”

Primary focus is on process understanding

Quality Advanced Process Control solutions start at theregulatory control layer

Design application with appropriate complexity toachieve sustainable benefits at true plant/process

constraints Software vendor independent

AMT works with all technologies provided by APC andOptimization software vendors




What Tools are Needed for Building and

Maintaining Model Predictive Controllers?

Must have appropriate knowledge

Process and operation experience

Process control at regulatory and advanced layers Computer expertise in software and hardware

integration

Technical skills must be backed up by people

skills Working with operators, technicians, process

engineers, planners and managers

Success and failure are highly visible




War Stories

“Getting it wrong” Management telling operations that APC will reduce manning

levels (it doesn‟t)

Not including time to resolve the regulatory control problems(getting the underlying structure right is key to success with

multivariable control) Being a control engineer rather than a process engineer (it is no

good being a whiz at PID tuning or multivariable controller tuningif you don‟t design right in the first place)

Not investing time in model development and conditioning(getting a good prediction is only part of the story)

Poor set up of variable priorities (a multivariable controllercannot control everything all of the time) and optimizationobjectives

Not investing in on-going maintenance (all multivariablecontrollers require regular attention)

We can illustrate some of these stories with examples




Example 1: Regulatory control is a multivariable

problem also…

Objective is to provide rapid and smoothrejection of disturbances – this is not the role of

APC Flows should be easy

If they‟re not working, is it the valve & related

hardware?

Start with material balance – levels & pressuresNext do the energy balance – temperatures

Tuning software or rules of thumb?

With experience, tuning software is only needed indifficult circumstances




Process Issues & PID tuning/configurationHeat integration and process layout creates

complex interactions

Example is 3 loops interacting with each other: Column C38101 inlet temp controller TC210

Column C38101 bottom level controller LC101

Column C205 bottom level controller LC215

By hand it is easy to tune single loops and eventwo loops that interact, but three can becometedious…



Process Performance Specialists AMTProcess Issues & PID tools

We need to bring this understanding of the processengineering issue to our software tools

After testing all loops in manual the model obtained isthe following (unit step responses)

Can simulate the interactions and tune manually (forexample using Cutler‟s [UPID] and training simulatorsoftware)

Using a commercial package called “Aptitune” we canderive tuning for all three loops simultaneously – hard to

do by hand!




BEFORE AFTER




Benefits of tuning By now, you‟re a hero with the operators – loops

that they have had trouble with for years becomestable in all situations reduced workload

Operators become generous…

Process is in situation where it can move towardconstraints

In one example a single temperature loop was tunedand made 0.25 million $/year

Having won the hearts of the operators and theunit managers you will have a good “advanced

control” project




Example 2: Plant Testing and ModellingObjective to move the process “independent

variables” to get responses in the “dependent

variables”

Can be done by hand, or in recent years withsome automated help

Beware the eager operator…

Beware the lazy operator…

Beware the helpful operator…




Model identification – it’s not just about prediction

A stabiliser column has two products

Bottom C5+, control the Reid Vapour Pressure

Top C4-, control the %C5 lost to the overhead Two handles available to do this

Reflux (top cooling) and reboil (bottom heating)

This is a naturally ill-conditioned problem

Can find models that predict fairly easily but inthis instance successful control requires morethan a good prediction




Two models give equivalent prediction of RVP

Red = measured

Blue = model 1 prediction

Pink = model 2 prediction




Control calculation to reduce RVP and %C5 Typical scenario is running both qualities at their

upper limits

Say the controller needs to make a 0.01 and 0.5reduction in both qualities to achieve targets

Calculate steady-state change in handles bymultiplying required change in CVs by inverse of

model gains

5.0

01.01

1

d c

baCV G MV

ss




Gains for model 1 and model 2 The values a, b, c , d in the equation are the

steady-state gains between the handles (reflux,reboil) and the qualities

Model 1

Model 2

RVP (bar) C5 (mol%)

Reflux (m3/h) 0.000741216 -0.058088677

Reboil (˚C) -0.007069334 0.871968881

RVP (bar) C5 (mol%)

Reflux (m3/h) 0.000588745 -0.084574698

Reboil (˚C) -0.00709939 0.772619199




Resulting control moves for model 1 & 2 For model 1

For model 2

Clearly model 1 would have the controllermoving in the wrong direction, it should increase

reflux and increase reboil to improve thequalities

dMV

Reflux (m3/h) 77.47

Reboil (˚C) 7.83

dMV

Reflux (m3/h) -52.00

Reboil (˚C) -4.04




How come model 2 gives better results? Both models gave adequate predictions

Success in multivariable control requires operationunderstanding to be mapped in to the mathematics

The current commercial packages are still “just maths” Special testing tricks help with this kind of problem

Normally we make independent moves on each handle

But for ill-conditioned problems we find making some of themoves in a correlated way actually helps the identification

software find the correct gain ratiosSo long as the software is a true MIMO identification, older MISOtechniques don‟t work so well

Often we have to “fix” models by hand, sacrificingprediction quality to obtain satisfactory control behaviour




Example 3: But it used to work…? Some MPC technology is robust to numerical problems,

others not

With the following gains a controller had worked for

many years on a vacuum unit furnace … but when the control software vendor was changed

and the model migrated the application was notaccepted by the operators




Robustification? To handle numerical issues with some control

technologies requires human intervention

Relatively small adjustment in gains to get stablecontrol behaviour




Example 4: Process Understanding is the Key Large gasoline feedstock producing unit

Unifiners (H2S removal), Platformer (reactor), Isom (reactor)

Large scope application with 37 MVs & 171 CVs

Has been an application in place for many years, full re-design and revamp with a change in multivariable controltechnology Integrated 14 separate small applications in to one overall

structure to enable plant wide optimization

Some interesting events when controllers taken off-line Operators had become dependent upon the applications and

found the unit hard to operate without the advanced controls –nearly had a shut-down when we turned off the old APC!

Operator training simulators become essential to maintain skills




Heart Cut Column

Pull valuablebenzeneproduct fromthe effluentfrom thePlatformer

reactor Process is very

non-linear

Light Plat

Heavy Plat

Combined

Platformate

Platformate

Steam

Benzene

Heart Cut




Benzene in Heart Cut

Toluene

Pentane+ lights

Concentrationincreasing withincreased heart

cut flow

Benzene

B e n z e n e

c o n c e n t r a

t i o n

Heart-cut flow

T o l u e n e

c o n c e n t r a t i o n




Toluene

Pentane+ lights

Concentration reducingwith too much heart cutflow pulling Toluene up

from base

Benzene

B e n z e n e

c o n c e n t r a t i o n

Heart-cut flow

T o l u e n e

c o n c e n t

r a t i o n

MPC objective is to sit on the optimum point – maximising side draw until breakthrough

of toluene then moving until there is no toluene. This leads to some cycling of theproduct flow, but this is not a problem because the run-down goes to storage.




Control design accommodates non-linear behaviour

The multivariable controller is designed so thatincreasing reboil will potentially always increase the wt%benzene in heart cut, this is to ensure enough duty to

drive benzene up the column Depending on the amount of toluene breakthrough in the

heart cut (side-draw) other MVs (Side-draw flow & TopTemp.) may move differently to maximise the benzenerecovery

Toluene breakthrough case: If wt% bz in heart cut is low, thenreduce Top Temp. and side-draw to compensate until side-drawmoves into toluene free mode

Toluene free case: If wt% of bz in heart cut is low, then increaseboth side-draw and top temp. to compensate, until toluene startsto break through




Benefit of Applying Process Understanding

After nearly 15 years of different attempts thereis now an application which works

During commissioning we gradually increasedthe benzene heart cut flow upper limit

Operators nervous at the amount of product we werepulling

Eventually needed to re-range the flow meterbecause of large increase in the average flow

Planning department were able to make significantsales increase




New Application Working – what about keeping it

working?Monitoring

Reporting

Operations need feedback and support

Tools

Keep talking

Track performance metrics

Strategy analysis




Who is APC Maintenance Engineer’s Key Customer?

Be available to operators to advise and respond toproblems

Meet with operators (at least weekly) to check they are

happy and have no problems with the MPC or relatedapplications, arranging and giving training as necessary Spending a lot of time in the control room is a significant factor in

building operator confidence, getting their feedback always leadsto improvements in design, strategy and acceptance

Finding one or two operators who are very interested in theapplication is a blessing, they can help with training and withkeeping documentation and „self learning‟ materials about the

MPC up to date




APC Maintenance Engineer’s Task List

Understand the process objectives

Understand the process in the context of the refineryplan

Ensure that the MPC design matches those needs and ifpossible at low cost make modifications as appropriate

Review application performance against the aboveobjectives on a regular basis (typically every month)

Review application performance in terms of KPIs andstability of operation (typically every week)

Update controller tuning and models on an as neededbasis to ensure acceptable performance



Process Performance Specialists AMTExample 5: Adapting a strategy may show new

problems in an old controller… new tricks can help

old dogs

Crude Unit application commissioned andrunning for several years

CDU quality objectives changed, a part timequality constraint becomes a full time constraint

Activated different combination of MVs and CVs

Controller makes excessive movement on toptemperature

Model gains seem reasonable, no significantRGA issues, what could be wrong?




Modelling technology has improved

Re-check identification of the problem relationship fromoriginal test data New approach to modelling shows bigger dynamic overshoot in

the modelled response than had been identified previously New modelling software used true MIMO relationships, adding

MV PVs in to the identification gave improved results

Update model curve with better dynamics New dynamic model shows MPC it needs to move slowly to

prevent the oscillation from building as the tower top temperatureswings the qualities




Conclusions

Implementing process control solutions is atough business Front line customer facing, often 24 hours per day

Failure is visible very quickly Success can be hard won – APC may move the plant

more than the operators are used to and it may taketime to “bed in”

Success requires experience and teamworkOnce the application is accepted it must not be

left to die Local engineering and remote support are essential

apc9 mon 16.35 experiences in building and maintaining mpc

Documents