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.

To view the recording of Deminar #7, click on the above picture. If you want to just view the slides click on Deminar #7 - PID Control of True Integrating Processes

Time is money. If you can get to optimum setpoints faster during fed-batch operations and for startup and product transitions of continuous operations, the increase in production revenue can be significant. For continuous operations there may also be an appreciable decrease in the processing, recycle, and waste treatment costs of off-spec material.

For cascade control, the speed of the secondary PID setpoint response largely determines the ability of the primary PID to get to its setpoint quickly and reject disturbances in the primary loop. A slow secondary PID setpoint response may require detuning of the primary PID to prevent interactions between the secondary and primary loops.

In Deminar #7 we explored how we could use PID structure options, setpoint feedforward, and bang-bang control to improve the setpoint response for integrating (e.g. batch) processes. The concepts are also applicable to the continuous process startup and transitions. The demos showed a big reduction in rise time (time to reach setpoint) by the use of "PID on Error" instead of "I on Error, PD on PV." The benefit of the additional bump from derivative action on error is rather marginal for the small rate setting used. In other words most of the speedup in the setpoint response could be achieved by "PI on Error, D on PV" unless there is a large secondary lag and hence a large rate time setting. The use of setpoint feedforward helped reduce overshoot, rise time, and settling time by about 25%. For deadtime dominant self-regulating processes, the improvement would have been more impressive. The most dramatic improvement occurred for full throttle bang-bang control. With some adjustment of logic and resting value as noted on slide 6, the bang-bang logic can also be effectively used for self-regulating processes. You can try out setpoint feedforward and bang-bang control on the virtual plant website starting August 20.

If you are intrested in reducing batch cycle time and startup time, check out Deminar #7 at 10:00 am CDT on Aug 11.

To attend the event, go to http://bit.ly/JC-LiveMeeting
Use the information below to connect (if you're not using the available computer audio):
• Toll-free: +1 (877) 771-7176
• Toll: +1 (225) 383-1099
• Participant code: 264679

Higher value added products are generally produced by batch operations. Often these products are sold out and extra batches translate to significant increases in revenue. Prime opportunities are specialty chemicals and drugs, especially new biopharmaceuticals where optimization took a backseat to time to market in the initial plant and automation system design.

I looked over my past experience with Monsanto, Solutia, and Emerson and have come up with myriad of methods to reduce batch cycle time. I have divided them up into opportunities to help feedback loops to get to setpoint faster that are important for Fed-Batch operations and for startups and transitions of continuous operations (Part 1) and opportunities to shorten phases and holds that are important for Pure-Batch operations (Part 2). These techniques like all new configurations and strategies should be thoroughly tested by simulation and closely monitored and adjusted for safe and efficient operation. Today's blog is a preview of Deminar #7 on July 14.

Fed-Batch Opportunities

1) PID on Error Structure - This structure maximizes the kick of the controller output for a setpoint change. The overdrive (driving of output past resting point) is essential for getting slow loops, such as temperature, to the optimum setpoint as fast as possible.

2) SP Track PV - With this control option the setpoint is changed to its optimum with the controller in automatic providing the kick from the PID structure (1). For batch operations this option is commonly used. For continuous operations with few setpoint changes (no grade transitions) and extremely long run time (e.g. years), the setpoint is held at its last value. However, even here loops with slow reset action (large reset times), such as level, the use of the SP Track PV option can prove useful when putting these loops back in service after maintenance.

3) SP Feedforward - For low controller gains (controller gain less than inverse of process gain), a setpoint feedforward is useful. The setpoint feedforward gain is the inverse of the dimensionless process gain minus the controller gain on a percent basis. If the setpoint and controller output are in engineering units the feedforward gain must be adjusted accordingly. The feedforward action is the process action, which is the opposite of the control action, taking into account valve action. In other words for a reverse control action, the feedforward action is direct provided the valve action is inc-open or the analog output block, I/P, or positioner reverses the signal for a inc-close (fail open) valve.

4) Output Lead-Lag - A lead-lag on the controller output or in the digital positioner can kick the signal though the valve deadband and sticktion, get past split range points, and make faster transitions from heating to cooling and vice versa. When combined with the enhanced PID algorithm described in Deminar #1, the lead-lag can potentially provide faster control when online analyzers are used for closed loop control of the integrating response associated with batch operations.

5) Deadtime Compensation - The simple addition of a delay block with the deadtime set equal to the total loop deadtime to the external reset signal for the positive feedback implementation of integral action (see Deminar #3). The controller reset time can be significantly reduced and the controller gain increased if the delay block deadtime is equal or slightly less than the process deadtime (see Advanced Application Note 3 entry March 25, 2009 on this website).

6) Full Throttle Batch - The controller output is put at its output limit to maximize the rate of approach to setpoint. When the projected PV equals the setpoint less a bias, the controller output is repositioned to the final resting value captured from the last batch. The output is held at the resting value for one deadtime. For more details, check out the Control magazine article "Full Throttle Batch and Startup Response."

7) Feed Maximization - Valve position control, Model Predictive Control (see Advanced Application Notes 1 and 2 entries March 25, 2009 on this website), or override control is used to maximize feeds to limits of operating constraints (e.g. maximum vent, overhead condenser, or jacket valve position with sufficient sensitivity). Alternatively, the limiting valve can be set wide open and the feeds throttled for temperature or pressure control. For pressure control of gaseous reactants, this strategy can be quite effective. For temperature control of liquid reactants, the user needs to confirm that the inverse response from the addition of cold reactants to an exothermic reactor and the lag from the concentration response does not cause temperature control problems. All of these methods require tuning and may not be particularly adept at dealing with fast disturbances unless some feedforward is added. Fortunately the prevalent disturbance is a feed concentration change that is often slow enough due to raw material storage volume to be corrected by feedback control.

8) Profile Control - If you have a have batch measurement that should increase to a maximum at the batch end point (e.g. maximum reaction temperature or product concentration), the slope of the batch profile of this measurement can be maximized to reduce batch cycle time. For application examples checkout "Direct Temperature Rate of Change Control Improves Reactor Yield" in a Funny Thing Happened on the Way to the Control Room E-book April 3, 2009 entry on this website and the Control magazine article "Unlocking the Secret Profiles of Batch Reactors"

This blog was kind of fun to write "With A Little Help from My Friends" (beer and music). By the way, the album "Joe Cocker" was apparently only produced on vinyl and 8-track tape. I fondly remember riding in my roadster with the top down listening to "Saint James Infirmary Blues" on the way to Monsanto's New Orleans plant. There are great songs on this album that carried me through startups that never made it onto a CD.

If you look at all the features and options of a PID controller that are sitting idle, you realize only a small fraction of the power of the PID is used even if you make the big assumption that the controller is tuned. How many loops use integral deadband, nonlinear gains, dynamic reset limits, setpoint velocity limits, or anything but the default PID structure?

The Deminar series started in April and continuing through July provides dynamic examples of how PID power can be used to reduce process variability and make batches and startups faster. In particular, the demanding and critical role of integrating processes is being revealed. We normally think of level as the primary integrating process and may dismiss the tightness of control as not important. Also statistics would say most of the loops are self-regulating. If you look closer you realize that the main reason for the large number of self-regulating loops is that the fact there are more flow loops than any other type of loop. Sure flow loops can be screwed up but auto tuners can find the right settings in matter of minutes and process control improvements can be quickly tested. What we often do not realize is that the really difficult and important loops have either a true integrating response (e.g. gas pressure and batch temperature and composition loops) or are so slow they are best treated as having a near integrating response (e.g. continuous temperature and composition loops). Furthermore, few realize that integrating processes are more sensitive to secondary lags, less than ideal valves, and have counter intuitive tuning rules. I would maintain that 90% of the loops with integrating processes are not tuned correctly and probably have too small of a reset time. The Deminar series and access to the web labs online should provide a source of exploring the opportunity to do better with these loops that matter the most. Check out the Deminar May 12 at 1:00 CDT to see how integrating loops suffer from slow valves and slow secondary loops.

To attend the event, go to http://bit.ly/JC-LiveMeeting
Use the information below to connect (if you're not using the available computer audio):
• Toll-free: +1 (877) 771-7176
• Toll: +1 (225) 383-1099
• Participant code: 264679

(1) PID Control of Sampled Measurements (How to Eliminate Oscillations from Analyzers and Wireless Measurements with a PID Enhancement) - April 7, Wed 1:00 pm CDT

(2) PID Control of Valve Sticktion and Backlash (How to Eliminate Continual Oscillations with the "Integral Deadband" PID option) - April 21, Wed 1:00 pm CDT

(3) PID Control of Slow Valves and Secondary Loops (How to Eliminate Bursts of Oscillations with the "Dynamic Reset Limit" PID option) - May 12, Wed 1:00 pm CDT

(4) Web Lab Access and Use Instructions (How to Use Free Online Process Control Labs for Fun and Profit and Become Famous by Friday or at Least Saturday) - May 27, Thurs* 1:00 pm CDT (* - Thursday date is to avoid conflict with the World Batch Forum)

(5) PID Tuning for Self-Regulating Processes (How to Compensate for Nonlinearities in Flow and Liquid Pressure Loops) - June 9, Wed 10:00 am CDT

(6) PID Tuning for Near-Integrating Processes (How to Reduce the Tuning Time for Column and Vessel Temperature and Pressure Loops by 90%) - June 23, 10:00 am CDT

(7) PID Control of True Integrating Processes (How to Reduce the Batch Cycle Time for Temperature and pH Loops by 25%) - July 14, 10:00 am CDT

(8) PID Control of Runaway Processes (How to Improve the Performance of Exothermic Reactor Temperature Loops) - July 21, Wed 10:00 am CDT

I will be doing the presentation McMillanISABostonExceptionalOpportunities.pdf next week at the Boston ISA section meeting. I will be giving out 10 free copies of my book The Funnier Side of Retirement for Engineers and People of the Technical Persuasion to balance out the serious stuff.

When?
Tuesday, October 20, 2009
6:00 - 7:00 Reception and registration
7:00 - 8:00 Dinner
8:00 - 9:00 Presentation

Where?
Best Western, Waltham, MA
380 Winter Street, Waltham, Massachusetts, 02451-8700, US
Phone: 781/890-7800 Fax: 781/890-4937

The opportunity afforded by online metrics is worth summarizing in this series even though it has been discussed in several entries on this website.

The need to cut costs has translated to an increased emphasis on process efficiency and the ability to justify software, hardware, and personnel. Increasingly these need to be hard benefits (e.g. reduction in raw material, downtime, and energy costs).

When I worked in process control improvement (PCI) in the technology department of a large chemical company, we had to show new benefits each year that were at least twice our salary to justify our job. By the end of the five year process control improvement effort we had 75 million dollars per year in savings documented. The PCI core group had 5 modeling and control specialists working with 20 or more process control engineers at key plants. The benefits reported depended upon the skills of particularly one person Glenn Mertz) who was extremely proficient in cost sheet analysis and working with operations and process technology.

Some companies are fortunate enough to have PCI as part of their culture as seen in the Control Talk Columns "Going, Going, Gone - Part 2" (September) and Part 3 (October) for examples. For many companies, benefits need to be reported in order for PCI and our profession to move forward or even exist. See the December 1 and 5, 2008 entries on this website "Past, Present, and Future of Automation - Part 5 (Benchmarking and Opportunity Assessment)" and Part 6 (Operator Interface) and the December 28, 2007 entry "Biggest Opportunities in Process Control Improvement - The Operator (Online Metrics) for more discussion of the aspects and importance of identifying and showing PCI benefits.

There are a lot of initiatives in the plant to improve plant operation by better operating procedures, equipment, and maintenance. All of these people take great pride in their work and are naturally eager to attribute better process operation to their efforts. Process technology often has the last say. The best way for PCI to get credit for improvement in plant operation is for the improvement and change to be visible in the data historian. A visible change in capacity, efficiency, or quality after a change in the process control system provides the documentation needed. If the PCI could be turned on and off, the correlation would be irrefutable but this is usually not practical. If no other events occurred when the PCI went online, a beginning of improved plant operation coinciding with the completion of the PCI, and a good explanation of cause and effect, will normally suffice for PCI to get credit. To help guide management and operations, comments should be entered in the historian and event makers for PCI provided.

PCI metrics for continuous process capacity are generally available from product flow measurements, downtime due to trips, and the time to startup or make a product grade transitions. PCI metrics for batch process capability can be generated from batch size, end point concentration, batch cycle time, and time in between batches. Quick and dramatic improvements in batch capacity have been achieved be the elimination of operator attention requests, manual actions, trips, and wait times for resource allocation (e.g. utility or charge systems), lab results, and reaction completion. Model predictive control and override control applications have been very successful for fed-batch processes. Reductions of 25% or more in batch cycle time are common for PCI. For a summary of some of the many possible batch control opportunities see BatchCycleTimeReduction.pdf from my PCI days.

PCI metrics for process efficiency are best expressed as a ratio of kilogram (pound) of input used (e.g. feed, fuel, reagent, and utility) per kilogram (pound) of product produced. For fuels, the numerator in the ratio may be expressed in thermal units, such as kilojoules (BTUs). For batch processes, the totalized input flow is divided by the batch size multiplied by the fractional product end point concentration. For continuous processes the instantaneous input flows are divided by intermediate or final product flow multiplied by the fractional product concentration. Synchronization of input flows to output flows can be done by the addition of a time constant equal to residence time and a time delay equal to the transportation delay. The flows can be totalized to compare shifts and periods of operation. Online process efficiency measurements require online or at-line analyzers or inferential measurements from first principle, neural network, polynomial, or statistical (e.g. PLS) models. These models in turn require flow measurements because nonlinear valve characteristics, backlash, and stick-slip make the use of controller outputs directly as model inputs ineffective and misleading. While reactant and fuel flows are typically measured, utility and reagent flows are often not. This short sightedness by plant projects (figuratively and literally), severely limits the ability to make improvements in the efficiency of use of these process inputs. I would wager a 10% reduction in the use of these inputs would more than pay for the flow meters. The old saying, you cannot control what you don't measure holds true for process efficiency. If I was a project manager, I would have a flowmeter on any input flow whose usage cost per year exceeded twice the installed cost of the flowmeter. I would at least provide the process connections for inserting a mobile wireless flowmeter. Where energy heat transfer rate calculations (e.g. heat removal rate as an inference of reaction rate) would be useful, I would install wireless RTD temperature transmitters on the streams entering and exiting the coils, exchangers, and jackets. Wireless transmitters allow the user to find during actual process operation the applications with the maximum benefit.