Spatio-Temporal Systems Estimation, Modelling and Analysis
Lead Research Organisation:
University of Sheffield
Department Name: Automatic Control and Systems Eng
Abstract
Systems where the dynamics at any point depends upon the dynamics back in time and the dynamics at neighbouring spatial locations are ubiquitous. These space-time or spatio-temporal systems represent an enormous class of highly complex dynamical systems that have been largely ignored in studies to date. It is the spatial interactions over a neighbourhood of influence that together with the temporal dynamics combine to produce evolving patterns of complex interacting behaviours. Real life examples of spatio-temporal systems are easy to find and range from neuro-imaging applications to stem cells and reaction diffusion systems. The main objective of this research study will be to derive generic systems identification and parameter estimation based procedures to identify models of these complex systems, to develop model validation methods for this model class, to investigate characterisation based on invariant dynamic measures, and to apply the results to a range of both simulated and real spatio-temporal systems.
Organisations
Publications
Akanyeti, O
(2011)
Studying robot environment interaction via transparent controllers
Balikhin M
(2010)
Data based quest for solar wind-magnetosphere coupling function
in Geophysical Research Letters
Balikhin M
(2011)
Using the NARMAX approach to model the evolution of energetic electrons fluxes at geostationary orbit NARMAX MODELLING OF RADIATION BELT ELECTRON FLUXES
in Geophysical Research Letters
Billings S
(2015)
Identification of nonlinear systems with non-persistent excitation using an iterative forward orthogonal least squares regression Algorithm
in International Journal of Modelling, Identification and Control
Billings, SA
(2011)
A time varying model for EEG Granger causality model
Boynton R
(2011)
Data derived NARMAX Dst model
in Annales Geophysicae
Boynton R
(2015)
Online NARMAX model for electron fluxes at GEO
in Annales Geophysicae
Boynton R
(2011)
Using the NARMAX OLS-ERR algorithm to obtain the most influential coupling functions that affect the evolution of the magnetosphere DATA-DEDUCED COUPLING FUNCTIONS
in Journal of Geophysical Research: Space Physics
| Description | Developed new theories, methods and algorithms to analyze, model, simulate and control complex spatio-temporal systems |
| Exploitation Route | Applications range from modelling crystal growth, to space weather forecasting and flow control |
| Sectors | Agriculture Food and Drink Chemicals Communities and Social Services/Policy Environment Healthcare |
| Description | By medics in treating epilepsy and deep brain stimulation. Space weather forecasting models - Real time forecast of the >800 keV electron flux at geosynchronous orbit |
| First Year Of Impact | 2015 |
| Sector | Chemicals,Environment,Healthcare,Pharmaceuticals and Medical Biotechnology |
| Impact Types | Societal |
| Description | Program Grant |
| Amount | $900,000 (USD) |
| Funding ID | RGP0001/2012 |
| Organisation | Human Frontier Science Program (HFSP) |
| Sector | Charity/Non Profit |
| Country | France |
| Start | 05/2012 |
| End | 06/2015 |