To view the recording of Deminar #8, click on the above picture. If you want to just view the slides click on Deminar #8 - PID Control of Runaway Processes

Self-regulating processes are the easiest to control given similar dynamics (e.g. delays, lags, and gains), nonlinearities, and upsets. In manual, the process variable will eventually reach a steady state for a self-regulating process. Integrating processes are the next most difficult to control because in manual the process variable will always be ramping even if there are no disturbances. Runway processes are the most challenging and potentially the most dangerous because in manual the process variable is always moving and can accelerate in its divergence even if there are no disturbances. Runaway processes are termed "open loop unstable." The acceleration is characterized by a positive feedback time constant. Both integrating and runaway processes have a low gain limit that causes slow rolling oscillations and a divergence off-scale, respectively. Integrating processes are more sensitive to integral action and secondary lags than self-regulating processes and runaway processes are more sensitive to integral action and secondary lags than integrating processes. The most common problem with integrating and runway processes is too much integral action (too small of a reset time) and the omission of derivative action for secondary lags (rate time should be set equal to largest secondary lag). Some highly exothermic polymerization reactors have proportional plus derivative control to avoid the potentially unsafe situation of someone adding too much reset action. I have been in the control room when an exothermic reactor has reached a point of no return where the temperature acceleration was so high despite full cooling, the only thing the operators could do was prepare for the rupture discs to burst and the reactor contents blow over to the flare stack tank. Highly reactive chemicals lead to rapid and complete reactions but can also lead to an uncontrollable temperature rise since the reaction rate and hence heat release doubles for every 6 degree increase in temperature. Runaway processes can look like integrating processes unless the temperature controller is left in manual long enough for the temperature change to be large enough.

Deminar #8 shows the dramatic correction needed for the tuning settings. The factors used in the short cut tuning method for near-integrators in Deminar #6 and the classic Ziegler Nichols ultimate oscillation method are detailed and demoed. Equations are offered to predict the ultimate gain and ultimate period showing the dramatic effect of a secondary process or thermowell lag and loop deadtime. If a secondary lag or the loop deadtime approaches the positive feedback time constant, the window of allowable controller gains closes and the loop is unstable for all tuning settings. The virtual plant is where you want to learn about runaway processes. You can't experiment much or have the loop in manual for more than a few deadtimes with a true runaway process.

The PID enhancement for wireless (PIDPlus) offers an improvement wherever there is an update time in the loop. In the broadest sense, an update time can range from seconds (e.g. wireless updates and valve or measurement sensitivity limits) to hours (e.g. failures in communication, valve, or measurement). Some of the sources of update time are:

(1) Wireless measurement default update rate for periodic reporting (refresh time)
(2) Wireless measurement trigger level for exception reporting (sensitivity limit)
(3) Wireless communication failure
(4) Broken pH electrode glass or lead wires (failure point is about 7 pH)
(5) Large valve operating on upper part of installed characteristic (low sensitivity)
(6) Valve with backlash (deadband) and stick-slip (resolution and sensitivity limit)
(7) Valve with solids, high temperature, or sticky fluid that causes plugging or seizing
(8) Plugged impulse lines
(9) Analyzer sample processing delay and analysis or multiplex cycle time
(10) Analyzer resolution and sensitivity limit

The PIDPlus waits for an update in the measurement whereas a traditional PID continually ramps the output acting on old information. When there is an update, the PIDPlus considers the changes to have occurred over the elapsed time from the last update whereas the traditional PID thinks the entire change occurred in the PID module execution time. The result is a spike from derivative action by a traditional PID that is particularly large when a measurement recovers or a valve trim or solids break free.

The improvement in control by the PIDPlus is most noticeable as the update time becomes much larger than the 63% process response time (defined in the white paper as the sum of the process deadtime and time constant). When the update time becomes 4 times larger than the 63% process response time that roughly corresponds to the 98% response time frequently cited in the literature, the controller gain can be set equal to the inverse of the process gain. This controller gain can provide an exact correction for changes in the measurement and setpoint.

The PIDPlus execution is kept fast so that the PID immediately responds to changes in setpoint, feedforward, mode, tuning, detail display parameters, and remote output. We have the interesting result that when the update is much larger than the 63% process response time so we can set the controller gain equal to the inverse of the process gain, the controller output goes immediately to the value needed to achieve the setpoint. An increase in update time to prolong battery life can actually translate to a faster setpoint response. However, if the process gain changes with time or operating point, the PID will require several updates to home in on the proper correction. An increase in update time will increase the settling time for unrecognized changes in the process gain. The use of an adaptive tuner such as DeltaV Insight that automatically identifies the process gain and schedules the tuning setting accordingly can sustain a fast setpoint response despite nonlinearities and a large update time.

The Emerson White Paper DeltaV-v11-PID-Enhancements-for-Wireless.pdf discusses these opportunities in more detail. Later this month, an entry on this site will show and discuss the trend plots that compare the enhanced PIDPlus with the traditional PID for the applications tested including valves with stick-slip and backlash.

It is important to distinguish between an update time and process deadtime. The update time is the time interval between successive updates by the final control element (initiated changes to the process input) and successive updates by the measurement (reported changes in the process output). The process deadtime is a continuous train of values delayed by the deadtime. The most common source of a pure process deadtime is a transportation delay of temperature and composition changes in a conveyor, extruder, dip tube, heat exchanger, pipeline, sheet line, or any volume where there is plug flow (no back mixing). Small time constants such as thermal lags, sensor lags, signal filter times, transmitter damping settings, effectively become additional deadtime in terms of a first order plus deadtime approximation (single time constant plus deadtime). The PIDPlus algorithm does not correct for process deadtime. As the process deadtime increases and approaches the update time, the opportunity to increase the PIDPlus gain decreases. For compensation of deadtime, a standard deadtime block can be inserted between the BKCAL_OUT of the AO block and the BKCAL_IN of the PID block if the DCS uses the positive feedback method for the integral mode (external reset) as reported in Advanced Application Note 3 "Compensation of Deadtime in PID Controllers".

In a future Deminar we will look in greater detail at the effect of updates time of discontinuous measurements and process deadtimes on the ultimate period and ultimate gain and if there is an improvement in loop performance offered by a combination of PIDPlus and deadtime compensation.

Let's pull together this series on errors and conclude with a check list. The idea was prompted by perusing a popular book written on just the value of check lists. I didn't think you could write a book on just one concept but the result of saving lives for surgical procedures is impressive. I know as I have gotten older, check lists are essential to just remember what I am suppose to be doing. I have found checklists to be helpful for me from both a practical and psychological viewpoint when rushed or overwhelmed with details, tasks, and objectives.

In the following list, increases in on-stream time can increase efficiency besides capacity by eliminating the time and off-spec and waste associated with abnormal operations, startup, and shutdown. An increase in yield or decrease in recycle can be taken as a decrease in raw material costs (same production rate for lower feed rate) or an increase in production rate (higher production rate for the same feed rate). The order of the list is in order of things to check and somewhat in the order of priorities.

Check List to Improve Process On-stream Time, Production Rate, and Efficiency
(composition measurements include conductivity, dissolved oxygen, pH, and turbidity)

1. Use smart transmitters with the best sensor technology and integration of process and ambient conditions compensation.

a. Avoid older technologies particularly ones with mechanical elements

b. Seek sensor and transmitter with the best sensitivity and repeatability

2. Pick sensor location and installation method to provide the most representative measurement in process with no stagnation, best velocity, fastest response, and least noise.

a. For DP and pressure transmitters, avoid impulse lines (sensing lines) by direct mounting transmitters or using diaphragm seals and filled systems

b. For DP and vortex flow meters insure uniform velocity profile

c. For thermowells and electrodes increase velocity to reduce response time and coatings but not so high to cause abrasion, static charge, or vibration

d. For thermowells and electrodes pick location with good mixing, minimal transportation delay, and least bubbles, slime, and solids

3. Use real throttle valves with smart positioners.

a. Avoid on-off and isolation valves posing as throttling valves. Go to a control valve manufacturer instead of a piping valve manufacturer

b. Seek actuator, positioner, and valve type with best sensitivity of installed flow characteristic and signal response with least stick-slip and backlash

c. Verify positioner feedback measurement is representative of internal closure member (e.g. ball, disk, or plug) and not just actuator position

4. Tune control loop with on-demand auto tuner or adaptive controller to meet loop objectives. Tuning speed is chosen to:

a. Insure an exceptionally smooth PV and output response by decreasing transfer of variability from PV to output (increasing Lambda) for:

i. level loops on surge tanks to minimize feed upsets
ii. deadtime dominant loops (deadtime >> process time constant)
iii. interacting loops (e.g. headers)
iv. loops on piping or equipment with no back mixing (e.g. blenders, heat exchangers, extruders, static mixers, sheets, webs, and yarns)

b. Provide good load rejection of moderately fast disturbances by increasing transfer of variability from PV to output (decreasing Lambda) for:

i. Fed-batch and continuous agitated vessel and column composition, level, pressure, and temperature loops

c. Provide good load rejection of extremely fast disturbances by setting the gain and reset as a factor of deadtime rather than the time constant for:

i. Continuous agitated vessel and column composition, pressure, level, and temperature loops

d. Provide minimal overshoot of setpoints of slow lag dominant loops (process time constant >> loop deadtime and slower than 10 minutes) by tuning the loops as near-integrating processes for:

i. Fed-batch and continuous agitated vessels and column composition, pressure, and temperature loops (setpoint changes occur at startup or for changes in batch phase and product grade)

e. Provide minimal peak error by maximizing controller gain even if it requires increasing reset time to maintain robustness for:

i. Prevention of SIS activation
ii. Prevention of pressure relief
iii. Prevention of environmental violation
iv. Prevention of equipment damage

5. Add DCS signal filter or damping adjustment to keep loop output fluctuations from noise less than the valve deadband to prevent excessive valve packing wear and inflicting disturbances on loop. For wireless transmitters use damping adjustment to reduce keep transmitter output fluctuations from noise less than wireless deadband to eliminate unnecessary communication and extend battery life.

6. Eliminate on-off actions

a. Replace on-off control by switches with loops.

b. Eliminate manual actions by adding loops, keeping loops in highest design mode, adding feedforward, and automating and tuning loops to handle startup and abnormal operating conditions

c. Replace pure batch with fed-batch automation by replacing discrete sequential actions (e.g. stepping feeds) with loops (e.g. throttling feeds)

7. Tune loops that create feed disturbances (e.g. surge level loops) to provide a smooth slow transition in feed rate.

8. Add cascade control to compensate for nonlinearities and pressure disturbances (e.g. secondary flow loop and secondary coolant temperature loop).

9. Add feedforward control of measurable fast disturbances not compensated by secondary loop.

10. Optimize setpoints by operating closer to constraints for production rate or product quality spec.

a. Eliminate operating margin imposed by shift's perceived sweet spot or operating margin caused by process variability from not doing check list items 1-9

b. Find more efficient operating points based on R&D reports and virtual plant exploration - confirm with process tests

b. Add model predictive control to optimize setpoints as process conditions and market requirements change.

How does controller tuning affect on-stream time and environmental costs?

The basic process control system (BPCS) forms the inner protective layer for safety instrumentation systems (SIS) as shown on page 5 of EffectsLoopTuning&Dynamics-KPI.pdf. The performance of the BPCS loops must limit excursions to be well within the operating limits that correspond to the trip points of the SIS. Specifically, the peak error for the largest and fastest disturbance should not cause a trip. The SIS should only be activated for failures or extremely abnormal conditions. The trip of a process unit not only causes downtime but can cause off-spec and additional waste during the shutdown and startup of the unit. The start-up of the process unit is often the most operator intensive and hazardous time. The importance of minimizing peak errors to prevent shutdowns can involve all types of loops (e.g. flow, level, pressure, and temperature). We normally think this is important only for continuous loops but I have been able to increase a fed-batch reactor capacity by 25% by eliminating level, pressure, and temperature trips by a series of override controllers tuned to minimize peak errors.

The peak error from the closure of a downstream valves (e.g. trip of reactor feed valves) on the discharge of a compressor controller must not cause an excursion of the operating point of the compressor to the left of the surge curve. If the operating point reaches the negative slope of the characteristic curve, it is like the compressor is falling off a cliff. The operating point jumps to a negative flow operating point in 0.03 seconds. This precipitous drop rivals water hammer in disturbance speed (both phenomena involve momentum balances that are orders of magnitude faster than material balances). Once a compressor gets into surge, the feedback controller is helpless and needs an open loop back-up (e.g. kicker) to get out of trouble as detailed on pages 6 - 8. Surge cycles can cause a decrease in compressor efficiency and damage by excessive vibration. I have also seen where surge caused a runaway speed response.

RCRA environmental regulations may classify a pond as hazardous waste if the pH of an effluent stream going into the volume momentarily ventures outside the permissible 2 to 12 pH range. Even though a short term excursion can not possibly change the pH in the volume and is effectively filtered by the volume where the change in pH is not detectable, the volume may still be classified as hazardous. For these systems, peak errors are incredibly important and kickers are used as shown on page 10 to prevent RCRA violations that not only can cause excessive fines but necessitate the process unit to apply for a new permit that might not be approved. A violation could result in the permanent shutdown of a unit because operation is no longer economically feasible or even allowed under new permit requirements.

Many process units have relief devises (e.g. relief valves and rupture discs) to prevent the over pressurization of piping and equipment. Often, pressure letdown and vent loops are the first line of defense. The peak error for the largest and fastest disturbance should be sufficiently away from the relief device setting to prevent fatigue and activation of the relief device taking into account setting tolerances and fatigue that cause a premature relief. The activation of a relief device is hazardous and causes downtime and waste burned in a flare stack or at best in a waste heat boiler.

So how do we minimize peak error? Given a set of dynamics and disturbances, the solution is to maximize controller gain even if it means increasing the reset time. This is seen in the first equation on page 1 but also intuitively from the realization that gain provides an immediate response whereas reset provides a gradual response. In the fed-batch reactor example cited above, the override controllers were proportional-only with their gains set high enough to cut back the reactant feeds immediately when the reactor pressure and level from the gas released as a byproduct or the temperature from the exothermic reaction approached settings that would cause a trip and the associated delay and disruptive restart of the feeds.

We can reduce the peak error per the first equation on page 2 by increasing the process time constant and decreasing the loop deadtime which increases the maximum allowable controller gain. We can also decrease the open loop error in the time frame of the controller's response by increasing the disturbance time constant. The fastest possible tuning should be able to stop the excursion from a disturbance after the loop deadtime. Thus, slowing down the disturbance slows down the excursion and reduces the peak reached in one loop deadtime (more on this next week). The process time constant is typically set by process equipment size and design, but we as automation engineers can greatly affect the disturbance time constant and the loop deadtime and sensitivity. We can iimprove the degree of automation, interaction, speed, reliability, and precision in automation systems. The opportunity may be larger than we realize. Up to 50% of downtime is attributable to instrumentation problems as noted in the March 2010 Control magazine article "Look to Valves for More Uptime"

Next week we will look at how the dynamics and precision of measurements, valves, and disturbances affect peak and integrated errors. We conclude this series with a check list for improving loop performance (Part 4).

Knowledge of the flows and the accumulation of material in a unit operation are fundamental to the understanding and analysis of process and equipment performance. Flows are the primary way of affecting the process. Root cause analysis requires sensitive and repeatable flow measurements. I have seen costly expert systems fail to deliver benefits because of missing or inaccurate flows ("Drowning in Data, Starving for Information - 1").

The process gains of the more important process variables (e.g. composition, pH, and temperature) are best quantified and visualized in a plot versus a ratio of flows (e.g. coolant/feed, reactant A/reactant B, reagent/feed, reflux/feed, and steam/feed). If you are still into differential equations, you can checkout my Advanced Application Note 4 to see how process gains are dependent upon the ratios of flows.

The importance of flow ratios for affecting the process is seen in the prevalence of flow ratio control as detailed in my entries "What Have I Learned? - Flow Ratio Control" on this website.

The amount of time material spends in a unit operation is critical for crystallization and reaction. For continuous operation of well mixed volumes, the amount of time is the residence that is the fluid volume divided by the total throughput flow. Conversion is maximized by increasing volume or decreasing feed flows. For batch processes, the amount of time is the cycle time. Conversion is maximized by charging the feeds as fast as possible (increasing feed flows), to leave more of the batch cycle time for conversion.

In the direct material balance control scheme where the distillate flow is manipulated for overhead receiver level control, the sensitivity of the temperature and hence the composition control requires an exceptionally sensitive level measurement, low noise, and a high controller gain. Changes in distillate flow do not affect the column until there is a corresponding change in the reflux flow that maintains the material balance.

Then of course, there is the need to minimize the amount of storage of materials in the process. Ideally, storage tanks would be almost empty with just enough raw materials and intermediates to continually meet the flow demand of downstream operations and just enough products to continually meet the flow demand of customers.

For more information on how advances in flow and level measurements can improve material balance control, residence time control, inventory control, and process analysis and modeling, checkout "Advances in Flow and Level Measurements Enhance Process Knowledge, Control"

This piece could have been titled "Exceptional Failures in Process Control." Despite my 25 years of explaining the importance of using middle signal selection, I don't see much evidence of what I have said has taken root outside of Monsanto and its spin-off Solutia, where it became a part of the culture and best practices to use middle signal of three pH electrodes for all important pH control loops. We ended up taking a view that all pH loops are important because if they are unimportant why should we go through the maintenance headaches and the risk of control system failure by installing a loop dependent upon the integrity of a single electrode. I think the main hurtle besides hardware and installation cost is the feeling that if one electrode requires so much effort, why should I add more? If the electrode life expectancy is too short, the feeling is right. We should not add more of a bad application or installation. Instead, we need to find a better design, technology, implementation, and location verified in testing via wireless pH or an alternate measurement (e.g. conductivity for concentrated acids or bases).

As an important side note, the use of three transmitters and middle signal selection on all of the important measurements (e.g. flow pressure, temperature, and level besides pH) used in the control system and safety system for a large intermediates plant has consistently eliminated false trips saving several million dollars per year.

What boggles my mind is that the risk of poor product quality and an environmental violation do not provide a wakeup call that the lifecycle cost of the measurement itself is insignificant in comparison to the risk. A simple quick ball park benefit versus cost analysis would show the absurdity of when the dollars of events likely to occur each year is more than 1000 times the dollars of the additional automation to prevent them. Unfortunately, we tend to get too focused on short term costs. Consider bioreactor batches worth millions of dollars each of a sold out pharmaceutical that are dependent pH upon control to within 0.02 pH. A second electrode is added but I am not sure it helps or just adds to the confusion. I find it almost bizarre how favorite electrodes are picked for the loop's PV and the stories that ensue about which one is best. It is a "fact of life" that electrodes will not agree in the short term due to non-ideal effects too numerous to get into here (check out my ISA book Advanced pH Measurement and Control for more info and previous blogs by searching for "pH"). The continual disagreement between two electrodes often leads to calibration adjustments chasing calibration adjustments. If left alone, the electrode that reads high today may in a couple of hours or at least by tomorrow read low. Electrodes can fail anywhere on the scale (including the most insidious failure of all type where the bad electrode signal is stuck at the pH set point). I maintain that the correct use of middle signal selection will actually reduce the long term maintenance cost by simple observation and the use of more intelligent practices eliminating unnecessary calibration and removal of electrodes.

A middle signal selection inherently ignores a single failure of any type and avoids the slowest electrode (e.g. coated electrode). This selection reduces noise and eliminates spikes without any addition of a signal lag like what you get from signal filtering. Middle signal selection also ignores an electrode with lower efficiency (shorter span) or that is drifting. Theoretically, electrodes of different "in service" time should be used to reduce the occurrence of concurrent failures. The middle electrode is the best signal on the average, but please don't use the average. I have seen some very smart attempts of computing average signals with built in intelligence on signal rejection that were out foxed by a single electrode failure scenario. You would think you could devise something smarter than the simple middle signal selection when in fact inherently it is impossible for a single failure. There can be additional intelligence for more than three electrodes or for protection against multiple concurrent failures.

To summarize, middle signal selection can improve process quality and on-stream time, reduce maintenance, and prevent environment violations by adding understanding and ignoring spurious signals, inaccurate measurements, and failures.

A prolonged deviation from the middle should be alarmed because if you don't fix the first failure or sustained error, middle signal section has a fifty-fifty chance of preventing the next failure or electrode inaccuracy. I could go on and on but I suspect you are pressed to move on. Before I go let's be frank with closing remarks in recognition of an engineer named Frank who was particularly astute at telling it the way it is.

There is an opportunity to use a statistical or first principle model based on titration curves to generate a third signal. Even if the model is wrong, it will be ignored by middle signal selection. There appears to be here mostly an upside where you will at least learn more about your process by developing a model.

I have no illusions as to whether this blog will change one person's mind enough to install middle signal selection even though it is a feature of a standard function block. I also have no expectations that enough users will see the need to take advantage of wireless measurements to eliminate the wiring installation and maintenance costs of going to three measurements. Even more unlikely is that users will end up using middle signal selection enough that it will be offered in a smart transmitter that inputs three electrodes even though electrodes are the weak link in regards to accuracy and reliability.

Startups, grade transitions, and abnormal conditions are the most difficult, operator intensive, hazardous, and inefficient periods of plant operation. Operators often believe these conditions require operator evaluation and action. The conditions are thought to be too special and the response too situation dependent to automate. The operators are right in saying these periods of operation require the best in operator expertise. However, case histories show that the power of the PID can be used to automate the best operator responses and build on them to provide faster, safer, and more efficient plant operation during these difficult process conditions. For some specific examples dealing with compressors and reactors check out the two chapters "Wally and the Beave Automate Reactor Startups" and "Wally and the Beave Return to Automate Another Reactor Startup" in my E-book on this website A Funny Thing Happened on the Way to the Control Room. For impressive examples for chemical, mining, and pulp and paper operations, check out the Control Talk columns "Show Me the Money - Part 1" (November 2009) and "Show Me the Money - Part 2" (December 2009) in Control magazine.

An extensive interview of the operators and process engineers is necessary to capture the best responses for a preliminary functional description of the control system. There are often a lot of surprises hidden by the diversity of actions that are inevitable from human responses. Free will implies these decisions are basically unpredictable. The operator actions consistent with first principles and process knowledge offer a good starting point but not the final strategy. During the commissioning of the control system, the plant response must be carefully observed and the best operator actions verified and improved by the use of the many options built into a PID loop to deal with rampant problems as the plant goes from zero to full rate, or vice versa. For example, output tracking, dynamic reset limiting, set point ramping, PID structure, gain scheduling, adaptive control, and override control can be used to deal with the problems at low rates such as noisy or inaccurate flow signals, excessive valve stick-slip near the closed position, larger transportation delays, and unrepresentative measurements. One of the common solutions is to head start (initialize) the controller output via output tracking to the best valve position for startup, transition, or abnormal situation. The initial position can be a "Full Throttle" position for fastest set point response. When the set point approaches the set point, the controller output can be momentarily set to a resting value based on experience or average position captured from a representative operating point from the last run. For fast loops such as flow and pressure, the resting value can be used as the "head start". One of the common mistakes is for process engineers to get carried away with trying to sequence the PID controller output too much or hold the controller output in the track mode for too long. For shutdown, the output must normally be held but otherwise the PID controller should be returned to automatic as soon as possible to deal with disturbances, unknown process effects, raw material variability, and nonlinearities. The process is not known or measured well enough to sequence flows without feedback control. It is particularly important to return pressure loops to automatic as fast as possible. Smart techniques for startup, transitions, and abnormal situations that take full advantage of the flexibility of the PID controller have been the source of the most impressive benefits in process control improvement. In general, these were also "quick hits" in that they were implemented in a matter of a couple of weeks by just configuration changes and controller tuning.