Teaching a conscious use of PI/PID tuning rules

Leva, Alberto; Papadopoulos, Alessandro Vittorio

doi:10.3182/20130828-3-uk-2039.00007

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…There are also other disturbances which are not pre-planned, such as antifoam additions [23][24][25]. The alternative approach for tuning PIDs for a biological process is to wait for a known or planned process disturbance and monitor the process response [26]. Using this wait and watch approach has been used by several mammalian cell studies to refine the PID gains and manipulated variable ranges [27,28].…”

Section: Introductionmentioning

confidence: 99%

PID controls: the forgotten bioprocess parameters

et al. 2022

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The ambr250 high-throughput bioreactor platform was adopted to provide a highly-controlled environment for a project investigating genome instability in Chinese hamster ovary (CHO) cells, where genome instability leads to lower protein productivity. Development of the baseline (control) and stressed process conditions highlighted the need to control critical process parameters, including the proportional, integral, and derivative (PID) control loops. Process parameters that are often considered scale-independent, include dissolved oxygen (DO) and pH; however, these parameters were observed to be sensitive to PID settings. For many bioreactors, control loops are cascaded such that the manipulated variables are adjusted concurrently. Conversely, for the ambr250 bioreactor system, the control levels are segmented and implemented sequentially. Consequently, each control level must be tuned independently, as the PID settings are independent by control level. For the CHO cell studies, it was observed that initial PID settings did not resulted in a robust process, which was observed as elevated lactate levels; which was caused by the pH being above the setpoint most of the experiment. After several PID tuning iterations, new PID settings were found that could respond appropriately to routine feed and antifoam additions. Furthermore, these new PID settings resulted in more robust cell growth and increased protein productivity. This work highlights the need to describe PID gains and manipulated variable ranges, as profoundly different outcomes can result from the same feeding protocol. Additionally, improved process models are needed to allow process simulations and tuning. Thus, these tuning experiments support the idea that PID settings should be fully described in bioreactor publications to allow for better reproducibility of results.

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