start-ups do not have to be difficult - top control · distributed with permission of authors by...

Distributed with permission of authors by ISA 2011

Presented at ISA Expo 2011; http://www.isa.org

START‐UPS DO NOT HAVE TO BE DIFFICULT

Michel Ruel1

1‐ BBA‐ Top Control Inc., Green Bay, WI, USA

Keywords: Process Model, PID Algorithm, Loop Tuning, Control Strategy, Alarm

Management, Performance 1. ABSTRACT

Between design and start‐up, much can be done to rationalize, standardize, and anticipate problems. In

addition, selecting the right options and parameters can greatly reduce issues at start‐up.

During the design phase, engineers can astutely make the proper choices without additional costs to prepare a

successful start‐up. For instance, traditionally, programmers have much flexibility during the programming

phase; design documents do not always specify the selection of algorithms, default values, options, and

selections. Similarly, HMIs should be designed according to standards.

This paper will suggest steps and actions to reduce start‐up time substantially. A series of tips and tricks are

presented, especially to select most parameters in advance. These steps will guide the programmers by

providing standardization, default values, and better choices for options.

Finally, a series of analyses are suggested for the start‐up phase. It will be shown that very few tests are

necessary when using modern tools, since operational data are usually sufficient.

Examples of successful start‐ups will be presented using modern tools and appropriate programming

standards. Performance evaluation should also be part of the start‐up phase and appropriate measurement

should be defined to detect bad actors.

2. INTRODUCTION

Many projects are designed without considering commissioning right from the start. Start‐up and

commissioning should be considered in every step, starting with design. The designers will decide on

equipment selection specification, programming language, communication protocols, programming standards,

and commissioning methodology.

The budgets will include the time required to perform the steps described in this paper; following these

guidelines will reduce the start‐up time and savings will be used to ensure better planning and buy software

tools. The start‐up and commissioning budget will include the software tools required to manage the field

equipment, as well as to tune and optimize the loops.

This paper will focus on process control but a similar approach should be used for motors, conveyors, pumps,

and other equipment.

3. EQUIPMENT SELECTION

Copyright 2011 ISA. All Rights Reserved


Presented at ISA Expo 2011 http://www.isa.org

The proper selection of instruments and valves can significantly reduce the time required for calibration and

commissioning; digital instruments and digital communications will allow the technician to manage this work.

Detailed instructions for configuration and calibration will be provided. All filters from instruments will be

removed; filters should be configured in the control system and be part of the tuning methodology. It is also

the responsibility of the designer to document special functions and specific configurations.

The number of authorized suppliers should be limited. Communications have to be standardized between the

field devices and control system, between the control system and HMI, the control system and historian, and

the control network and specialized software tools.

Universal protocols will be used and proprietary communication networks should be avoided.

When selecting equipment, sizing and quality will determine controllability. An oversized valve will correspond

to a large process gain (%/%) while the valve characteristic will determine the process linearity. Table 1

suggests limits on equipment quality; this depends mostly on the valve or final control element. Process gain

and linearity will depend on equipment sizing and choice; for example, selecting the proper valve characteristic

will modify linearity.

Hysteresis and stiction will depend on valve/positioner assembly and quality. Vendors can guarantee values bit

it will be true only for new equipment. Positioner overshoot will be adjusted when configuring the positioner.

TABLE 1 – ACCEPTABLE EQUIPMENT PERFORMANCE

Acceptable

Value

Target

Value

Process gain > 0.5 and < 2 1

Linearity (Gprocess max/Gprocess min) < 2 1

Hysteresis, Dead band < 2% 0%

Stiction <0.2% 0%

Positionner overshoot < 20% 0%

4. PROGRAMMING

Traditionally, programmers have much flexibility during the programming phase. Using well‐defined standards

will guide the programmers for the DCS (Distributed Control System), PLC (Programmable Logic Controller), and

HMI (Human Machine Interface).

These standards must be enforced, even if many suppliers participate in the project; this becomes even more

crucial when several groups program and design the control strategies.




4.1 Points to consider

Points to consider when defining standards:

Tag numbering (following ISA and other standards)

Data flow, data communication, data exchange

Network hierarchy

Tasks scheduling, load sharing, scan time

Programming language part of the IEC 61131 standard

Functions defined in details, for basic PID controllers for instance (refer to Section 4.2.2)

Control strategies structure properly defined and standardized

o Cascade, ratio, override, feedforward, etc.

Transfer switches standardized: Manual/Auto, Remote/Local, etc.

Alarms

Others

4.2 PID Function

The PID function requires special attention. Hence, most systems offer several PID structures and many

parameters. One PLC manufacturer offers 11 different PID algorithms and some of these algorithms have

defects and bugs in their code. Another manufacturer offers a powerful PID algorithm with more than 200

parameters to select; unfortunately, some of the default values are unacceptable, a proportional gain of zero

for instance.

4.2.1 PID algorithm structure

Which algorithm should be preferred? Ideal (also frequently named ISA)? Parallel? Series?

Unfortunately, the names of these algorithms are not standard: one named “independent” could correspond

to a Parallel algorithm with a given manufacturer but be Ideal with another. The designer will prefer Ideal or

Series algorithm since the Parallel algorithm is not intuitive when manipulating the parameters. For most loops,

the derivative is not used and if so, the Ideal and Series algorithms become identical.

4.2.2 Parameters and selections

The designer will not only impose the use of a one and only algorithm, but will decide how to select all key

options and parameters. The designer should consider building a meta‐block with all proper selections and

options already in place. Some manufacturers use non‐sense default values.

For instance, the following parameters will be selected:

Measurement filter




o First order or second order

o Moving average is used only if the noise period is constant; this filter adds more dead time to the measurement and is a non‐linear function.

Output slew rate, limiting rate, maximum step change per scan

o Not used

o Used exceptionally to protect equipment or process.

Filter on derivative

o Always used. If adjustable, use a filter time constant approximately 1/10 of the derivative time

o If no filter is available for the derivative block, remove the derivative option.

Derivative on Process Variable (PV) or Error

o Unless specified, the default value should be on PV to avoid brutal output changes when manipulating the setpoint.

Integral on PV or Error

o Unless specified, the default value should be on PV to avoid slow SP changes when manipulating the setpoint

o However, useful for level loops or large lag to avoid overshoot on SP changes.

Lead/Lag filter on SP

o Default value should be NO which is equivalent to Integral on Error.

o If a Lag value= Lead value; this is equivalent to NO

o If Lead=0 and Lag=Integral time (not true for Parallel algorithm); this is equivalent to Integral on PV.

Scaling

o If the PID control block manipulates numbers without scaling them 0‐100%, add a scaling function for the process variable, setpoint, and controller output.

Special functions: P2ID, PI2D, PID gap, PID non linear, PID, gap on Integral, etc.

o Should be considered as special algorithms and be programmed as control strategies.

Default parameter values (refer to next section) for Proportional, Integral, Derivative, and Filter.

4.2.3 Summary of PID controller choices:




Algorithm specified, Series or Ideal preferred

All selections and basic parameters defined

Adding a measurement filter function if not part of the PID basic function

Adding a characterizer at the output (or in digital positioner)

Avoid limiters and special non‐linear functions.

4.2.4 Control strategies

The designer will develop programming standards for all control strategies; structure, parameters, default

values, and transfer switches.

Following are the common control strategies to be defined:

Cascade

Ratio

Constraint or override

Supervisory

Feedforward

4.2.5 PIDF default parameters

The programmers should use the suggested values for each type of loop.

Table 2 suggests the default value for common loops; these values are conservative and will produce a smooth

sluggish response. Before start‐up a process control engineer should revise the values using process

knowledge. This person will also validate the controller action (direct or reverse) depending on the process and

equipment

Table 2 – Usual tuning parameter values for common loops

P I D F Scan rate ~settling

time Kp Ti Td TF tscan

units

second second second second minute

Flow, Pressure (liquid) 0.1 10 0 0.5 <0.5 1




Flow, Pressure (gas) 0.2 30 0 0.5 <0.5 1

Level 5 600 0 5 1 10

Level (buffer) 1 1000 0 5 1+ 50

Temperature 1 600 10 2 1+ minutes

Analysis 1 600 0 5 1+ minutes

Others 0.2 5td 0 td/5 < td 10 td

4.2.6 Tests

The programmers should test every function and then encapsulate the code and default values. An easy way to

test the PID functions consists in simulating the process using a series of lag functions.

4.2.7 Variable speed drives used as control element

All variable speed drives (VSD) used as a final control element should be configured adequately, without

excessive ramps and limiters.

The controller output limits are taken into account when adjusting the minimum and maximum values. The

limits selected in PDI function and the limits for the command speed sent to the drive should be identical.

The low limit should be adjusted to correspond to minimum flow; it is common to observe that the speed much

reach a certain speed to build enough pressure to overcome static pressure.

Even though the electrical group is responsible for VSD, a process control engineer should review the

parameters selection.

5. COMMISSIONING AND START‐UP

At start‐up, the punch lists and detailed checking are defined in advance. The malfunction, improper design,

and wrong selection should generate immediate warnings and an escalation process should be in place.

Most commissioning procedures will detail visual inspection, power and grounding procedures, calibration,

instrument and valve checkout, software tests, etc.

What is missing?

At start‐up, it is essential to validate:

Valve performance

Control loop performance in different conditions

Controller stability, control loop response




Hence, all loops must perform adequately, be stable, and be tuned to obtain the expected settling

time.

6. OPTIMIZING AND TUNING LOOPS AT START‐UP

How to conduct the tests?

How to analyze equipment behaviour?

Which steps are required?

If default values from Table 2 are used, the loops will be stable. In addition, since operators manipulate

setpoints, switch modes, start and stop, etc. at start‐up, all these steps generate sufficient data to model the

process, to detect equipment problems, and to select tuning parameters.

Modern tools will detect whether the process model is linear; otherwise, the valve performance test should be

conducted.

Indeed, normal operational data and their analysis using appropriate software tools will guarantee a smooth

and very quick start‐up.

6.1 Open Loop or Closed Loop test?

Traditionally, loops were tuned in open loop using bump tests. Most tuning tools use this technique. When

analyzing process data in open loop, one must be careful since everything that is programmed in the control

system will not be part of the test. For instance, the controller execution time, filters, ramp limiters, and

characterizers will not be considered.

Also, simple bump tests require special techniques to detect process defects such as dead band, backlash,

hysteresis, stiction, and non‐linearities.

When analyzing in closed loop, the controller sampling time is included, process defects are part of modeling (if

setpoint moves in both directions), and special configuration and programming are included.

Hence, when using closed loop testing techniques, the results obtained include every part of the loop and if the

tool is powerful enough, even non‐linearities will be included in the model. Non‐linearities are usually

amplitude dependent. Also, the amplitude of setpoint changes should reflect usual process variable excursions

from setpoint.

6.2 DATA SUITABLE FOR CLOSED LOOP TESTING

What is needed to have sufficient data to model a process? The first simple answer is: moves in the controller

output sufficient to cause process variable movement superior to noise. Fortunately, this happens all the time

at start‐up. Modern tools will detect if the process model is linear; if not, valve performance should be verified,

if not this step is skipped.

6.2.1 An example

A flow loop where setpoint changes occur is used to demonstrate how to tune this loop without extra tests.




Figure 1: Data used for analyses. (The grey area has been sliced out since the pump was stopped.)

We observe very aggressive tuning on this loop. Most software will disregard this data and will be unable to

model the process since oscillations and non linearities are present.

Figure 2: Model found, and uncertainty.

Strong non linearities are present but the software identifies a grade A model (high quality) with a small error.




Figure 3: Tuning pane and simulation.

Even with non linearities, those tuning parameters will maintain this loop stable in all situations.

6.3 Control strategies

Advanced regulatory control strategies such as cascade, ratio, feedforward will also be tuned under normal

operation without bump tests. For instance, cascade loops are tuned while the master controller is in

automatic mode and the secondary in cascade mode. SP changes on the master controller from normal

operation or with small steps generated by the software produce sufficient movement in the controller outputs

to model the process, verify non‐linearities, and tune the loops.

Figure 4. The model quality for both the primary and secondary loops

in a cascade temperature control scheme is an ‘A’




7. CONTROL PERFORMANCE MONITOR

Control performance monitoring consists of analyzing incoming signals (process variables, set points,

Monitoring PID control loops is another very useful tool for start‐up.

and state/mode) and outgoing signals (controller outputs) in order to determine if the expected performance is

reached. All signals are read from the control system (distributed control system, programmable logic

controller, quality control system, etc.) via digital communications. The system detects oscillations and

equipments (valves transmitters, variable speed drives, etc.) that do not behave as benchmarked, as well as

process control problems, process problems, operation problems, etc.

The system must detect all problems related to control loops, process equipments, operations, and production.

It must also handle special control strategies (cascade, feedforward, override, ratio, etc.) and generate

predefined reports.

It is a condition‐based application that monitors, identifies, diagnoses, and remedies control asset issues across

all plant layers. This software tool also offers modeling and tuning tools. This technology not only helps

improve control performance, but it also helps to sustain it. It continuously monitors all regulatory control

assets, detects and prioritize problems, and notify the appropriate personnel.

The system monitors PID loops, advance process control (APC), analyzers, and soft sensors. Since the PID loop

layer is particularly important for pulp and paper mills, we will focus on that layer in this article.

Figures 5, 6, and 7 show examples of simple web reports.




Figure 5. Summary report of aggregated areas

Figure 6. Summary report of areas, using filters to identify loops with problems

Figure 7. Treemap screenshot

All graphics have been generated using the Matrikon TaiJi‐PID tuning tool.

8. CONCLUSION

FROM design TO start‐up, much can be done to rationalize, standardize, anticipate problems, and select right

options and parameters to reduce the pain at start‐up.




The following list is used:

Design

o Standardize, limit number of suppliers, determine in advance parameters and functions

O Define network architecture, communication and data flow Programming

o Standardize, impose algorithm, parameter default values

o Select PIDF parameters accordingly to loop type

o Standardize control strategies implementation

Commissioning and start‐up

o Use punch lists

o Use modern software tools to verify equipment performance, model the process and

determine optimal tuning parameters.

9. REFERENCES

Brisk, M. L., “Process Control: Potential Benefits and Wasted Opportunities”, 5th Asian Control Conference, vol.

1, 2004, 20‐23.

Brittain, H. and Ruel, M. Optimize Your Process Using Normal Operation Data, NPRA Conference, Houston TX,

October 2008

Gosselin, C., and Ruel, M.,“Advantages of Monitoring the Performance of Industrial Process”, ISA Management

Newsletter, January 2007, 6‐8.

Ruel M., Control Valve Performance, Chemical Engineering, October 2000, 64‐67

Zhu, Y.C. Multivariable process identification for MPC: the asymptotic method and its applications. Journal of

Process Control (1998), Vol. 8, No. 2, 101‐115.

Instrument Engineers' Handbook , chapter 5.6 Plantwide Control Loop Optimization (3rd Edition, edited by Bela G

Liptak, CRC Press, Boca Raton FI, 2002), 40 pages


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