Adaptive identification of anaerobic digestion process for biogas production management systems.

To achieve the goals of sustainable development, supplies of renewable energy must be increased and methods of stable production developed. This study focused on the anaerobic digestion process using biomass as a raw material, which represents a renewable energy resource which is robust to environmental change and can be adjusted to suit supply and demand. A state-space model of the process was built in this study, consisting of two differential equations and one algebraic equation. The parameters included in the model are dependent on the operating conditions of the process. Automatic estimation of parameters from the input and output data of the process enables easy use of the model under any operating conditions. An adaptive-identifier control system was introduced as the parameter-estimation system, which made it possible to obtain the least squares estimate of parameters. When accumulated biogas generation per day was predicted using the model, goodness-of-fit analysis indicated an accuracy of over 80% in all cases, validating the model and estimated parameters. Future tasks will involve implementation of model predictive control into anaerobic digestion processes with the model and parameter-estimation system developed in this study.