Full-Scale Digesters: An Online Model Parameter Identification Strategy

This work presents a new standard in the model, identification, and control of monitoring purposes over anaerobic reactors. One requirement that guarantees normal controller operation is for faculty to measure data needed periodically. Due its inability easily obtain concentrations acidogenic bacteria methanogenic archaea periodically using reliable commercial sensors, this paper an algorithm composed asymptotic observer (considering reaction rates are unknown), aiming estimate these concentrations. method represents significant advantage because it possible perform resource-saving strategy measurements, such as pH or alkalinity, calculate them analytically natural environments. Additionally, two yield parameters were included original model (AM2) unlock implementations wide range organic substrates. The static parameter identification was improved called step-ahead optimization. It demonstrates improvements fitting mathematical until 78.7% increase efficiency (compared with traditional optimization genetic algorithm). After period convergence, state evidences small error maximum 2% deviation. Finally, numerical simulations demonstrate structure’s strengths, which constitutes step paving way further implement feasible, cost-effective controls systems industry.