By Gregory K. McMillan and Mark S. Sowell
Nearly every plant has pH control applications, even if only a plant waste-treatment system. The performance of the pH system is important, not only from the viewpoint of environmental regulation compliance, but also in terms of reagent consumption, direct costs and as an indicator of upstream process problems. Additionally, pH can be critical in the process operation of crystallizers, fermenters, reactors and strippers For example, a 0.2 pH variation from the optimum pH for a mammalian cell culture can decrease cell growth, viability or product formation by 10%. Therefore, proper control of the pH system is an important part of profitable and safe plant operation.
Great Expectations and Practical Limitations
In terms of hydrogen ion concentration, a pH system seeks to achieve a degree of concentration control that is extraordinary. No other measurement offers a rangeability of 1014 (0-14 pH scale) or a resolution of 10-7 (neutrality). While we tend to focus on the configuration of the DCS, achieving the full potential of the pH measurement requires exceptional attention to every aspect of the system design. Deficiencies in the equipment, piping, valves or sensor selection or installation can cause the system to fail miserably. However, advanced process control and high-resolution control valves can get the most out of the system and potentially eliminate a stage of neutralization or an agitated vessel.
For pH electrodes, some plants have established the middle selection of three electrodes as a best practice. (See items 1-3 in the Extra Credit sidebar, located at the end of this story.) Many users have moved to two electrodes, but since the electrodes never agree, using two raises more questions than answers and offers no improvement in reliability if the wrong electrode is chosen.
Manual and automated logic that establish one electrode as the favorite would make an interesting article. Middle signal selection, on the other hand, is quite boring, since it inherently provides protection against a single failure of any type, including the most insidious of all, a failure to a value that matches the pH set point, a very real possibility for pH. Using the middle value can also reduce noise and improve the accuracy of the signal.
The Art of Simulation
A virtual plant was recently used to prototype and test new advanced control strategies for a plant waste-treatment system. The virtual plant consists of a first-principle dynamic model of the pH system and the control system configuration running on the same PC. (See items 4 and 5 in Extra Credit sidebar, located at the end of this story.) The model includes component, charge and energy balances for various types of equipment and piping designs. The task of setting one up is a lot less intimidating, both in terms of numerical computation and physical properties, than is normally associated with high-fidelity process models if one focuses on simplification and attention to details that really matterthe essence of the art of dynamic simulation. For example, the effect of valve resolution, dip tube volume, transportation and mixing delays are modeled because these are often the large sources of dead time. The name of the game with pH is to minimize the loop dead time to minimize the excursion along the highly nonlinear titration curve.
Process models may have hundreds of thousand of compounds and millions of details on physical properties, but often assume perfect valves, perfectly mixed volumes and perfect injection of reagents, all of which cause a serious underestimation of the loop dead time, leading to erroneous conclusions and bizarre controller tuning. (See Items 6, 7, and 8 in sidebar, located at the end of this story.) For pH modeling for process control of environmental systems, about 20 acids and bases cover about 90% of the applications. The physical properties requirements are much less (just molecular weight, density and dissociation constants of each acid and base). The waste treatment systems are normally dilute enough so that activity coefficients are not needed.
We tested the online pH model in a plant waste-treatment system that had two stages of inline pH control followed by a tank, as shown in Figure 1. Each stage consisted of a static mixer, multiple reagent control valves in parallel, and the middle selection of three pH electrodes to improve the resolution and reliability of the final element and measurement. The big downstream tank with three electrodes was not particularly well mixed, but still provided significant attenuation (smoothing) of the pH oscillations from the inline systems. There was a complex custom fuzzy logic control system on the tank that worked, but sometimes made changes operators could not understand. The engineer who implemented the fuzzy logic had moved on, and its detailed functionality was a mystery to us, let alone to those not privy to its origin.