Simple Gain-Scheduled Control System for Dissolved Oxygen Control in Bioreactors

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.

On the control of coolant parameters in long-life facilities

When nuclear power plants with heavy coolants are brought to operating mode as well as during their operation, it is necessary to control and maintain the oxygen content in the coolant within the specified limits. As a rule, the oxygen content in metal melts is controlled by sensors based on solid oxygen-ionic electrolytes. The article presents an analysis of the methodological aspects of dissolved oxygen control in non-isothermal circulating loops with metal coolants, using such sensors. It is shown that in the presence of dissolved loop wall materials and suspensions of their various oxides in the coolant, control over the values of the oxygen activity and concentration calculated for a pure coolant is in general unjustified. The authors present the experimental results of the distribution of oxidation potentials along the loop depending on the coolant temperature, obtained during long-term tests of cladding samples in a lead melt in two circulation facilities – SM2-M and TsU1-M – which differ in principal methods for maintaining specified oxygen conditions. In the low temperature region, the experimental values of the oxidation potential in both facilities are lower than those calculated for pure lead, which leads to a difference by two or more times of the calculated oxygen concentrations for the regions of the loop with Тmin and Тmax, i.e., the so-called oxygen ‘non-isoconcentration’ is observed along the loop. In deoxidation mode during hydrogen ejection into the coolant, the oxidation potential in the loop changes in a complex way, and it makes no sense to talk about the oxygen concentration. It is concluded that in long-life facilities, the coolant parameters for oxygen must be controlled not by the calculated oxygen activity or concentration but by the oxidation potential in the maximum temperature region. To obtain the correct values of the oxidation potential, measurements should be carried out in temperature-stable modes of throughout the facility.

A pretreatment method of wastewater based on artificial intelligence and fuzzy neural network system

A pretreatment method of industrial saline wastewater based on Artificial Intelligence based fuzzy neural network analysis was proposed to improve the pretreatment accuracy of industrial saline wastewater. This method uses a four-layer AI fuzzy neural network model and proposes a graded fuzzy neural network model for pretreatment method of industrial saline wastewater, it includes input layer, fuzzification layer, fuzzy logical layer and output layer, and designs the framework and calculation mode of the fuzzy function block and the neural network module. Finally, the dynamic simulation experiments of dissolved oxygen control in the fifth zone and nitrate nitrogen control in the second zone are carried out based on the simulation benchmark model (BSM1) platform. The experimental results show that this approach can effectively raise the adaptive control accuracy of the system compared with PID, feed forward neural network and conventional recurrent neural network.

Automatic Dissolved Oxygen Control to Oreochromis Fish’s Crop into Geomembrane Tank

Huila is a Colombian state with a high production of Oreochromis fish, its contribution to national production is of 53%, that is distributed in 338 hectares of ponds on land and floating cages. The environmental and climatic characteristics of the region allow having dissolved oxygen production in the ponds between 4ppm and 12ppm during the day, but at night the situation is unfavorable, since the amount of dissolved oxygen can decrease up to 1ppm while carbon dioxide increases. Therefore, it is necessary to have adequate oxygenation equipment and systems to prevent delayed in fish growth and to decrease death rates. This article presents the design and implementation of an automatic dissolved oxygen control system by manipulation of a water recirculation flow that operates in parallel with an industrial oxygen generator. The implemented system tracks and records the temperature and oxygen variables present in the geomembrane tank to evaluate the process evolution for different periods of the fish development cycle. The data was acquired using an Atlas Scientific dissolved oxygen sensor kit and a DS18B20 temperature probe they send the data directly to a Raspberry Pi that transmits by wireless the information collected from the process to the SISCEFA web server and a mobile application through which users can observe the data traceability. The dissolved oxygen concentration was maintained within the threshold established and the fish rate death decrease.