AI Article Synopsis
- A mass balanced model for anaerobic digesters has been developed to create software sensors that accurately predict concentrations of inorganic carbon, alkalinity, and volatile fatty acids.
- The model also facilitated the design of both an adaptive linearizing controller and a fuzzy controller aimed at keeping the ratio of intermediate alkalinity to total alkalinity below a critical value of 0.3 for process stability.
- Extensive simulations confirmed the controllers' effectiveness in managing alkalinity ratios, even when faced with significant changes in organic load.
Article Abstract
A mass balanced based model representing the dynamical behaviour of anaerobic digester has served as a basis for the design of software sensors for the concentration of inorganic carbon, alkalinity and volatile fatty acids. The predictions of the sensors are close to the actual off-line measurements. The model has also been used to design a model-based adaptive linearizing controller and a fuzzy controller whose objective is to regulate the ratio of the intermediate alkalinity over the total alkalinity below some desired value (0.3) under which the process is assumed to remain in stable conditions and avoid VFA accumulation. Both controllers were calibrated via extensive numerical simulations and implemented. The controllers proved successful in maintaining the ratio of TA over PA below 0.3, even in presence of large variations of the organic load.
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