System Identification and Model Validation for Spatio-Temporal Dynamical Systems
Lead Research Organisation:
University of Sheffield
Department Name: Automatic Control and Systems Eng
Abstract
Spatio-temporal systems are systems that evolve over both space and time. Until recently the lack of tools for analysing spatio-temporal systems has not been a limitation since most experiments produced purely temporal information in the form of measurements at a specific location or site. But there are many important systems where space and time are essential for explaining the observed phenomena. The main objective of this research study will be to investigate the identification of models of spatio-temporal systems where the cell entries can be either continuous or binary variables and to study the validation and other properties of this important class of nonlinear systems.
Publications

Guo Y
(2014)
An iterative orthogonal forward regression algorithm
in International Journal of Systems Science

Guo Y
(2016)
A New Efficient System Identification Method for Nonlinear Multiple Degree-of-Freedom Structural Dynamic Systems
in Journal of Computational and Nonlinear Dynamics