Nonparametric identification and adaptive control of an anaerobic fluidized bed digester

In this paper, a new adaptive and robust control algorithm that is able to successfully deal with unpredictable internal changes (unmodeled dynamics) and external disturbances (changes in input) of the processes in an anaerob ic digestion bioreactor is presented. The adaptive controller is based on a nonparametric statistical approach of the process identification. The regu lation is done by optimally adapting the input liquid flow rate of the wast ewater to designated changes in the output flow rate of the biogas (methane and carbon dioxide) resulting from the biological reaction. The fundamenta l advantage of this approach is its freedom from any a priori modeling assu mptions about uncertain dynamic components. Experimental results, obtained using a pilot-scale 150 1 fluidized bed reactor for the treatment of indust rial wine distillery liquid wastes, demonstrates the usefulness of this app roach in controlling biological processes. (C) 2000 Elsevier Science Ltd. A ll rights reserved.