Identification and estimation of continuous-time, data-based mechanistic (DBM) models for environmental systems

Young, Peter C.; Garnier, Hugues

doi:10.1016/j.envsoft.2005.05.007

Cited by 108 publications

(67 citation statements)

References 64 publications

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“…The continuous-time approach has its usual advantages (e.g. [Young and Garnier, 2006]) but it is computationally more intensive: the continuous-time algorithms are approximately ten times slower than the equivalent discrete-time algorithms.…”

Section: Discussionmentioning

confidence: 99%

A Refined Iv Method for Closed-Loop System Identification

Gilson

Garnier

Young

et al. 2006

IFAC Proceedings Volumes

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Section: Discussionmentioning

confidence: 99%

A Refined Iv Method for Closed-Loop System Identification

Gilson

Garnier

Young

et al. 2006

IFAC Proceedings Volumes

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“…Transfer function models relating the input (here, a time series of rainfall, R) to the output (here, a time series of either discharge, Q, or phosphorus load, TP load) were identified using continuous-time models (Young and Garnier, 2006) where possible, or in cases where data were missing or identification was difficult, with discrete time models (Young, 2003), the estimation of which handles missing data more robustly. Continuous-time models are more numerically robust and have a direct interpretation as systems of differential equations (Young, 2011).…”

Section: Transfer Function Model Identificationmentioning

confidence: 99%

Prediction of storm transfers and annual loads with data-based mechanistic models using high-frequency data

Ockenden

Tych

Beven

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Excess nutrients in surface waters, such as phosphorus (P) from agriculture, result in poor water quality, with adverse effects on ecological health and costs for remediation. However, understanding and prediction of P transfers in catchments have been limited by inadequate data and over-parameterised models with high uncertainty. We show that, with high temporal resolution data, we are able to identify simple dynamic models that capture the P load dynamics in three contrasting agricultural catchments in the UK. For a flashy catchment, a linear, second-order (two pathways) model for discharge gave high simulation efficiencies for short-term storm sequences and was useful in highlighting uncertainties in out-of-bank flows. A model with nonlinear rainfall input was appropriate for predicting seasonal or annual cumulative P loads where antecedent conditions affected the catchment response. For second-order models, the time constant for the fast pathway varied between 2 and 15 h for all three catchments and for both discharge and P, confirming that high temporal resolution data are necessary to capture the dynamic responses in small catchments (10-50 km 2 ). The models led to a better understanding of the dominant nutrient transfer modes, which will be helpful in determining phosphorus transfers following changes in precipitation patterns in the future.

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“…The identified model can be either discrete (Ljung (1987)) or continuous (Garnier and Young (2004); Young and Garnier (2006); Bingulac and Sinha (1989)). In this paper, a continuous-time identification 3 method (Garnier and Wang (2008)) is considered, for several reasons:…”

Section: On the Identification Technique Usedmentioning

confidence: 99%

Identification of nonlinear dynamic models of electrostatically actuated MEMS

Casenave

Montseny

Camon

2010

Control Engineering Practice

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This paper focuses on the identification of nonlinear dynamic models for physical systems such as electrostatically actuated micro-electro-mechanical systems (MEMS). The proposed approach consists in transforming, by means of suitable global operations, the input-output differential model in such a way that the new equivalent formulation is well adapted to the identification problem, thanks to the following properties: first, the linearity with respect to the parameters to be identified is preserved, second, the continuous dependence on noise measurements is restored. Consequently, a simple least-square resolution can be used, in such a way that some of the difficulties classically encountered with identification methods are by-passed. The method is implemented on real measurement data from a physical system.

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Identification and estimation of continuous-time, data-based mechanistic (DBM) models for environmental systems

Cited by 108 publications

References 64 publications

A Refined Iv Method for Closed-Loop System Identification

A Refined Iv Method for Closed-Loop System Identification

Prediction of storm transfers and annual loads with data-based mechanistic models using high-frequency data

Identification of nonlinear dynamic models of electrostatically actuated MEMS

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