Virtual Sensors to Drive Anaerobic Digestion under a Synergetic Controller

The production of biogas via an anaerobic fermentation process is very interesting for various reasons: it not only produces renewable energy, but also facilitates the disposal of organic waste, therefore it preserves the environment, it contributes to the resolution of energy problems in agriculture and agro industry, it’s available for everyone because the waste is available everywhere. This process takes place in continuously stirred tank bioreactor and is described by a highly nonlinear model whose parameters are often uncertain thereby requiring robust control in any process performance enhancement procedure to optimize the biogas production. Thus a robust control technique, synergetic, is proposed to improve the settling time in a fermentation based biogas production in a simulation study; the simulation study is carried out on biotechnological process described by a five-order continuous-time reaction scheme described by three stages. An extended Luenberger observer is proposed under synergetic control to observe the different concentrations because of the high-cost and unavailable measurement instrumentation. The interest of paper lies in controlling the amount of bio methane produced and the observation of all the states of the system (5 different populations of the complex community of bacteria and substrate concentrations acting during anaerobic digestion (AD) processes) by simply measuring the biogas produced. The monitoring, controller and observer performance are evaluated via numerical simulations showing excellent responses under the influence of control input. Key words: Bio methane, anaerobic digestion, synergetic control, extended Luenberger observer, state estimation.

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Estimation and Control of WRRF Biogas Production

Komulainen,

Jonassen,

Antonsen

2024

Energies

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The development of resource-efficient digital technologies is a critical challenge in the wastewater sector. This industrial case study, conducted in collaboration with the Veas Water Resource Recovery Facility in Norway, focused on creating data pre-processing methods and resource-efficient control strategies. Using data from the Veas biogas plant, dynamic models were developed to compare control outcomes. The primary objective was to maximize biogas production and hot water usage while maintaining optimal temperature and hydraulic retention time by adjusting inlet sludge and hot water flow rates. Sequential operations were approximated as continuous operations using a 30-min moving minimum/maximum for bimodal data and a 2-h moving average for noisy data. The data-driven dynamic models achieved an accuracy of up to R2 of 0.85. The control strategy, which included one feedback controller, one ratio controller, and flow rate restrictions, was compared to real production data (baseline) and tested across six scenarios. The best improvement over the baseline scenario resulted in a 3% increase in total biogas production, a 6% increase in total organic loading, a 13% increase in hot water use, and a one-day reduction in hydraulic retention time. Future work should focus on control studies using extended datasets and nonlinear models.

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Virtual Sensors to Drive Anaerobic Digestion under a Synergetic Controller

Cited by 3 publications

References 17 publications

Control of Bioprocess

Control of Bioprocess

Robust Control and State Estimation of a Three-Stage Anaerobic Digestion Process

Estimation and Control of WRRF Biogas Production

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