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Mar
29

Exceptional Opportunities in Process Control – Peak and Integrated Error – Part 3

At my recent presentation to the ISA Saint Louis section meeting on “pH measurement”, I had several people around my age say how nice it was to see me still involved in advancing our profession. Maybe it was the beer and the top ten lists but just maybe it was also that I represent a generation of expertise rapidly disappearing via retirement. The ability to still learn and share keeps me going but I realize time is running out so I intend to take this blog to the next level by coupling it with a web lab series to provide an interactive self-learning experience for exploring process control improvements (PCI). I intend to start the web lab series on April 7. Recordings of the PCI topics and demos along with instructions on using the associated labs will be viewable anywhere anytime.

In the meantime, we need to finish up this series so let’s see what we can do as automation engineers to minimize loop errors.

The first thing is to make sure the measurement is fast and precise enough. So far as loop performance is concerned, precision is more critical than accuracy. The bias or offset in a measurement and control valve position can be corrected by feedback control. The offset in valve position is eliminated by the process loop. Similarly, the offset in a process loop is eliminated when the loop is in cascade or remote cascade modes. For loops operated in the auto mode, operations have often compensated for the measurement offset by tweaking the set point. This is not to say that measurement accuracy is not important.

Improving the loop’s speed of response often comes down to keeping sensors clean (e.g. electrodes and thermowells), minimizing signal damping and filtering, selecting sensor locations that eliminate transportation and stagnation delays, using boosters for big valves, maximizing positioner sensitivity, minimizing deadband, and maximizing the controller gain (last week’s blog).

Control loops have a difficult time dealing with the poor precision experienced as excessive stick-slip and backlash (deadband) in control valves and insufficient resolution, repeatability, and sensitivity in measurements (older measurements technologies, such as floats and rotameters can also exhibit stick-slip and backlash). Fortunately, an increase in A/D input card bits have greatly improved the resolution of transmitted signals so that sensitivity and repeatability is the remaining focus. This is unfortunately not the case for variable frequency drives manufacturers whose standard input cards have only 8 bits. A resolution limit is more degrading than a sensitivity limit. For example for a 1% resolution and 1% sensitivity and a change in the true process variable of 1.5%, the changes in measurement would be 1% and 1.5%, respectively. The deadband setting in wireless transmitters is really a sensitivity setting. When the change in a wireless transmitter measurement exceeds this setting regardless of the direction, the full change in the process variable is communicated.

Slides 12 through 15 of Effects-of-Loop-Tuning-and-Dynamics-on-KPI.pdf show the relative effect of measurement accuracy and resolution on variability. For control valves, process variability is introduced when excessive slip-stick and deadband causes an appreciable limit cycle in loops that have single and two or more integrators, respectively (slides 19 and 20).

The total loop deadtime can be approximated as the sum of all the delays and small lags in the loop whether they are in the DCS, valve, process, or measurement. For flow, pressure, level, and inline temperature and pH loops, most of the loop deadtime comes from the automation system. If you consider that the remaining loops that have significant process deadtime, such as vessel or column temperature, have seriously detuned controllers that create an effective deadtime per Advanced Application Note 5, you realize you have the opportunity as a process control engineer to make big reductions in loop deadtime that are also low cost and quick compared to changing process piping or equipment to reduce transportation or mixing delays.

Fast disturbance originate from manual operation, on-off actions, sequences, or setpoint changes. The elimination of operator actions, on-off control (e.g. level switches), and the use of set point rate of change limits and fed-batch rather than pure sequential batch, can dramatically slow down disturbances since throttling control by intention is smooth. If we keep all loops in their highest design mode and limit on-off valves to SIS actions and isolation, we could eliminate step disturbances. Slide 22 shows how slowing down the disturbance dramatically reduces the peak and integrated errors for an integrating process. Not shown here is the fact that slowing down disturbances can also reduce interaction between loops. This phenomenon explains why it is difficult to get pharmaceutical companies excited about doing a better job of bioreactor control after reaching setpoint. The disturbances from cells are incredibly slow (e.g. process time constants of days).

Maybe we should not slow down disturbances because all of our control texts are based on step disturbances. Slowing down the upsets relegates us to improving the set point response in the startup of a continuous process or for changes in phase in a batch process. Whoops, even here we could use strategies such as “Full Throttle Batch and Setpoint Response” to eliminate most of the job of the loop.

There are always opportunities to make us more appreciated even when we are not improving loops. Since spouses were at the ISA Section Saint Louis Meeting, I interjected the following list. The spouses laughed although a second opinion was suggested for some of the items. See what your spouse or significant other thinks.

Top Ten Reasons Why an Automation Engineer Makes a Great Spouse or at Least a Wedding Gift

(10) Reliable from day one

(9) Always on the job

(8) Low maintenance – minimal grooming, clothing, and entertainment costs

(7) Many programmable features

(6) Stable

(5) Short settling time

(4) No frills or extraneous features

(3) Relies on feedback

(2) Good response to commands and amenable to real time optimization

(1) Readily tuned