Title :
Identification of LPV partial differential equation models
Author :
Schorsch, J. ; Gilson, M. ; Laurain, V. ; Garnier, H.
Author_Institution :
CRAN, Univ. of Lorraine, Vandoeuvre-les-Nancy, France
Abstract :
This paper deals with the identification of linear parameter varying (LPV) models described by partial differential equations (PDE). A direct identification of continuous space-time LPV-EDP systems in an input-output setting is investigated in the case of an additive output noise. The continuous space-time LPV-PDE model is firstly proposed to be rewritten as a multi-input single-output linear time-space invariant model and an iterative optimization is then developed to estimate efficiently the model parameters. The performance of the proposed method is then illustrated via a representative simulation example based on an Alsace river-flow measurement.
Keywords :
continuous time systems; iterative methods; linear systems; optimisation; parameter estimation; partial differential equations; Alsace river-flow measurement; LPV partial differential equation model identification; additive output noise; continuous space-time LPV-EDP system identification; input-output setting; iterative optimization; linear parameter varying models; model parameter estimation; multiinput single-output linear time-space invariant model; Approximation methods; Equations; Iterative methods; Mathematical model; Noise; Noise measurement; Rivers;
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
Print_ISBN :
978-1-4673-5714-2
DOI :
10.1109/CDC.2013.6760590