Extended State Dependent Parameter modelling with a Data-Based Mechanistic approach to nonlinear model structure identification

A unified approach to Multiple and single State Dependent Parameter modelling, termed Extended State Dependent Parameters (ESDP) modelling, of nonlinear dynamic systems described by time-varying dynamic models applied to ARX or transfer-function model structures. Crucially, the approach proposes an...

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Bibliographic Details
Published in:Environmental modelling & software : with environment data news 2018-06, Vol.104, p.81-93
Main Authors: Mindham, David A., Tych, Wlodzimierz, Chappell, Nick A.
Format: Article
Language:English
Subjects:
Computer simulation
Data analysis
Data based mechanistic modelling
Dynamic models
Dynamical systems
Hydrologic data
Hydrologic modeling
Hydrologic models
Hydrological modelling
Hydrology
Information Criterion
Model identification
Modelling
Nonlinear dynamic systems
Nonlinear systems
Parameter identification
State-dependent parameters
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Summary:A unified approach to Multiple and single State Dependent Parameter modelling, termed Extended State Dependent Parameters (ESDP) modelling, of nonlinear dynamic systems described by time-varying dynamic models applied to ARX or transfer-function model structures. Crucially, the approach proposes an effective model structure identification method using a novel Information Criterion (IC) taking into account model complexity in terms of the number of states involved. In ESDP, model structure involves not only the model orders, but also selection of the states driving the parameters, which effectively prevents the use of most current IC. This leads to a powerful methodology for investigating nonlinear systems building on the Data-Based Mechanistic (DBM) philosophy of Young and expanding the applications of the existing DBM methods. The methodologies presented are tested and demonstrated on both simulated data and on high frequency hydrological observations, showing how structure identification leads to discovery of dynamic relationships between system variables. •Extension of Data-Based Mechanistic modelling of non-linear systems.•Identification of model structure for a significant class of non-linear systems.•State-Dependent Parameters extended for irregularly spaced data.•Application to environmental systems – water quality dynamics.
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2018.02.015