LSSVM based initialization approach for parameter estimation of dynamical systems

2nd International Conference on Mathematical Modeling in Physical Sciences 2013

物理学;数学

Mehrkanoon, Siamak^1 ; Quirynen, Rien^1 ; Diehl, Moritz^1 ; Suykens, Johan A. K.^1

KU Leuven, ESAT-SCD, Kasteelpark Arenberg 10, B-3001 Leuven (Heverlee), Belgium^1

关键词: De-noising;    Estimation of parameters;    Euler discretization;    Filtered signals;    First order;    Integration method;    Non-linear optimization problems;    Parameter estimation problems;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/490/1/012004/pdf
DOI  :  10.1088/1742-6596/490/1/012004

来源: IOP

【 摘 要 】

In this study the estimation of parameters in dynamical systems governed by parameter-affine ordinary differential equations is explored. The described method by Mehrkanoon et al.∼ in [1] is utilized as an initialization of the nonlinear optimization problem for parameter estimation. In contrast to existing convex initialization approaches [2] that use a first order Euler discretization, we do not require any integration method to simulate the dynamical system. Furthermore, a denoising scheme using LSSVM is proposed to first filter the measured data then proceed with the filtered signals for parameter estimation problem. Experimental results demonstrate the efficiency of the proposed method, compared to alternative approaches on different examples from the literature.