This contribution discusses the main challenges related to successful application of automatic control systems used to control specific growth rate in industrial biotechnological processes. It is emphasized that, after the implementation of basic automatic control systems, primary attention shall be paid to the specific growth rate control systems because this process variable critically affects the physiological state of microbial cultures and the formation of the desired product. Therefore, control of the specific growth rate enables improvement of the quality and reproducibility of the biotechnological processes. The main requirements have been formulated that shall be met to successfully implement the specific growth rate control systems in industrial bioreactors. The relatively easy-to-implement schemes of specific growth rate control systems have been reviewed and discussed. The recommendations for selection of particular control systems for specific biotechnological processes have been provided.

For historic reasons, industrial knowledge of reproducibility and restrictions imposed by regulations, open-loop feeding control approaches dominate in industrial fed-batch cultivation processes. In this study, a generic gray box biomass modeling procedure uses relative entropy as a key to approach the posterior similarly to how prior distribution approaches the posterior distribution by the multivariate path of Lagrange multipliers, for which a description of a nuisance time is introduced. The ultimate purpose of this study was to develop a numerical semi-global convex optimization procedure that is dedicated to the calculation of feeding rate time profiles during the fed-batch cultivation processes. The proposed numerical semi-global convex optimization of relative entropy is neither restricted to the gray box model nor to the bioengineering application. From the bioengineering application perspective, the proposed bioprocess design technique has benefits for both the regular feed-forward control and the advanced adaptive control systems, in which the model for biomass growth prediction is compulsory. After identification of the gray box model parameters, the options and alternatives in controllable industrial biotechnological processes are described. The main aim of this work is to achieve high reproducibility, controllability, and desired process performance. Glucose concentration measurements, which were used for the development of the model, become unnecessary for the development of the desired microbial cultivation process.

An adaptive control system for the set-point control and disturbance rejection of biotechnological-process parameters is presented. The gain scheduling of PID (PI) controller parameters is based on only controller input/output signals and does not require additional measurement of process variables for controller-parameter adaptation. Realization of the proposed system does not depend on the instrumentation-level of the bioreactor and is, therefore, attractive for practical application. A simple gain-scheduling algorithm is developed, using tendency models of the controlled process. Dissolved oxygen concentration was controlled using the developed control system. The biotechnological process was simulated in fed-batch operating mode, under extreme operating conditions (the oxygen uptake-rate’s rapidly and widely varying, feeding and aeration rate disturbances). In the simulation experiments, the gain-scheduled controller demonstrated robust behavior and outperformed the compared conventional PI controller with fixed parameters.

Journal provides a multidisciplinary forum for scientists, researchers and engineers involved in research and design of nonlinear processes and phenomena, including the nonlinear modelling of phenomena of the nature.

A new composting technology of waste with high fat content was developed in JSC “Biocentras”. The composting technology of fat‐contaminated waste is based on the use of fat‐oxidizing microorganisms. Developed technology is commended for cleaner production/pollution prevention approach as well as meets strict environmental and hygiene requirements. The composting process was investigated for the process optimization by applying the response surface methodology. Values of parameters of composting process were monitored in lab‐scale composters. The optimal composition of the composing mixture was determined: the initial fat content – 5%, the concentration of bacterial preparation cells – 109 CFU/g, the quantity of structural materials – 9.5%. Fat degradation rate slowed down 3 times if the initial fatty concentration increased from 5% to 20%. Concentrated fatty‐waste disposal site prototype was designed. Composting process duration lasted 1 to 1.5 year. Santrauka UAB “Biocentre” sukurta nauja riebalais užterštu atlieku kompostavimo technologija, pagrista riebalus oksiduojančiu mikroorganizmu panaudojimu. Ši technologija pažangesne taršos prevencijos požiūriu, jos privalumas – švaresne gamyba. Sukurtoji technologija atitinka griežtus aplinkos apsaugos ir higienos reikalavimus. Tyrimai atlikti laboratorinemis salygomis. Riebaliniu atlieku kompostavimo procesu technologiniams parametrams optimizuoti taikyta faktoriniais eksperimentais grista reakcijos paviršiaus analizes metodologija. Nustatyta optimali eksperimentine kompostuojamo mišinio sudetis: pradinis riebalu kiekis – 5 %, biopreparato lasteliu koncentracija – 109 KSV/g, struktūrines medžiagos kiekis – 9,5 %. Padidinus pradine riebalu koncentracija nuo 5 % iki 20 %, riebalu skaidymo sparta suleteja apie 3 kartus. Suprojektuotas koncentruotu riebaliniu atlieku utilizavimo aikšteles modelis. Kompostavimo proceso trukme 1–1,5 metu. Резюме В ЗАО “Biocentras” была создана новая технология компостирования отходов с высоким содержанием жира. Технология компостирования загрязненных жирами отходов основана на использовании микроорганизмов, окисляющих жиросодержащие вещества. Разработанная технология является привлекательной для более чистого производства/предупреждения загрязнения окружающей среды, а также удовлетворяет строгим экологическим и гигиеническим требованиям. Исследован процесс компостирования. Для оптимизации процесса применен метод математического моделирования. Опыты проведены в лабораторных условиях. Определен оптимальный состав смеси: начальное содержание жира – 5%, концентрация бактериальных клеток в препарате – 109 КОЕ/г, количество структурных материалов – 9,5%. Деградация жиров замедляется в 3 раза, если первоначальная концентрация жиров увеличивается от 5% до 20%. Разработан и построен прототип площадки для компостирования жировых отходов. Процесс компостирования длится от 1 до 1,5 лет.