title: Identifiability of large-scale non-linear dynamic network models applied to the ADM1-case study.
abstract: In this work, both the structural and practical identifiability of the Anaerobic Digestion Model no. 1 (ADM1) is investigated, which serves as a relevant case study of large non-linear dynamic network models. The structural identifiability is investigated using the probabilistic algorithm, adapted to deal with the specifics of the case study (i.e., a large-scale non-linear dynamic system of differential and algebraic equations). The practical identifiability is analyzed using a Monte Carlo parameter estimation procedure for a 'non-informative' and 'informative' experiment, which are heuristically designed. The model structure of ADM1 has been modified by replacing parameters by parameter combinations, to provide a generally locally structurally identifiable version of ADM1. This means that in an idealized theoretical situation, the parameters can be estimated accurately. Furthermore, the generally positive structural identifiability results can be explained from the large number of interconnections between the states in the network structure. This interconnectivity, however, is also observed in the parameter estimates, making uncorrelated parameter estimations in practice difficult.
authors.affiliation: KU Leuven, Department of Chemical Engineering, BioTeC+ & OPTEC, Gebroeders De Smetstraat 1, 9000 Ghent, Belgium.
authors.forename: Philippe
authors.initials: P
authors.lastname: Nimmegeers
authors.affiliation: KU Leuven, Department of Chemical Engineering, BioTeC+ & OPTEC, Gebroeders De Smetstraat 1, 9000 Ghent, Belgium.
authors.forename: Joost
authors.initials: J
authors.lastname: Lauwers
authors.affiliation: KU Leuven, Department of Chemical Engineering, BioTeC+ & OPTEC, Gebroeders De Smetstraat 1, 9000 Ghent, Belgium.
authors.forename: Dries
authors.initials: D
authors.lastname: Telen
authors.affiliation: KU Leuven, Department of Chemical Engineering, BioTeC+ & OPTEC, Gebroeders De Smetstraat 1, 9000 Ghent, Belgium.
authors.forename: Filip
authors.initials: F
authors.lastname: Logist
authors.affiliation: KU Leuven, Department of Chemical Engineering, BioTeC+ & OPTEC, Gebroeders De Smetstraat 1, 9000 Ghent, Belgium. Electronic address: jan.vanimpe@cit.kuleuven.be.
authors.forename: Jan Van
authors.initials: JV
authors.lastname: Impe
mesh_terms: D000465:Algorithms; D000693:Anaerobiosis; D001421:Bacteria, Anaerobic / Q000378:metabolism*; D008954:Models, Biological; D015233:Models, Statistical; D009010:Monte Carlo Method; D017711:Nonlinear Dynamics
keywords: Anaerobic digestion model no.1; Non-linear biological models; Practical identfiability; Structural identifiability