LFT modelling and identification of anaerobic digestion. (March 2015)

• Record Type: Journal Article
• Authors: Della Bona, Alessandro; Ferretti, Gianni; Ficara, Elena; Malpei, Francesca
• Is Part Of: Control engineering practice. Volume 36(2015)
• Page Start: 1
• Page End: 11
• Publication Date: 2015-03
• Subjects: Anaerobic digestion -- Biogas power plants -- Parameter estimation -- Linear fractional transformation -- System identification; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2014.11.008
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: In this paper, a reduced order model of anaerobic digestion is first proposed, with the main goal to develop an efficient tool for process monitoring and control. Then, in order to perform parameter estimation, the model has been rewritten in a linear fractional transformation (LFT) formulation, using a symbolic tool originally developed for linear models and modified for the processing of nonlinear models. Two different test cases have been considered. In a first case, the data used for parameter identification have been generated by simulating the well known and more complex ADM1 model, considering waste activated sludge as substrate. In a second case, experimental data were collected on a laboratory scale equipment, operated in a semi-batch experiment, performing the anaerobic digestion of ultra-filtered cheese-whey. Abstract : Highlights: A reduced order model of anaerobic digestion is proposed, based on the AMOCO model. In order to perform parameter estimation, the model is rewritten in a linear fractional transformation (LFT) formulation. The data used for identification have been first generated by simulating the ADM1 model, considering waste activated sludge as substrate. Then, experimental data were collected on a laboratory scale equipment, performing the anaerobic digestion of ultra-filtered cheese-whey.