Title :
Identification of non-linear stochastic spatiotemporal dynamical systems
Author :
Hanwen Ning ; XingJian Jing ; Li Cheng
Author_Institution :
Dept. of Mech. Eng., Hong Kong Polytech. Univ., Kowloon, China
Abstract :
A systematic identification method for non-linear stochastic spatiotemproal (SST) systems described by non-linear stochastic partial differential equations (SPDEs) is investigated in this study based on pointwise observation data. A theoretical framework for a semi-finite element model approximating to an infinite-dimensional system is established, and several fundamental issues are discussed including the approximation error between the underlying infinite-dimensional dynamics and the model to be identified, and its rationality etc. Based on the proposed theoretical framework, a general identification method with irregular observation data is provided. These results not only provide an effective method for the identification of non-linear SST systems using measurement data (both offline and online), but also demonstrate a potential solution for the analysis, design and control of non-linear SST systems from a numerical point of view.
Keywords :
control system synthesis; identification; nonlinear differential equations; nonlinear dynamical systems; partial differential equations; stochastic systems; SPDE; SST systems; approximation error; general identification method; infinite-dimensional dynamic system; irregular observation data; measurement data; nonlinear stochastic partial differential equations; nonlinear stochastic spatio-temporal dynamical system; pointwise observation data; semifinite element model; systematic identification method;
Journal_Title :
Control Theory & Applications, IET
DOI :
10.1049/iet-cta.2013.0150