Identification of N-state spatio-temporal dynamical systems using a polynomial model

A multivariable polynomial model is introduced to describe n-state spatio-temporal systems. Based on this model, a new neighbourhood detection and transition rules determination method is proposed. Simulation results illustrate that the new method performs well even when the patterns are corrupted by static and dynamical noise

Control of spatio-temporal pattern formation governed by geometrical models of interface evolution

Numerous natural phenomena are characterized by spatio-temporal dynamics which give rise to time evolving spatial patterns. Although studies that address the problem of modelling these complex dynamics exist, a model based control approach for such systems is still a challenging task. The work in this thesis is concerned with the development of control methods for such spatio-temporal systems, where interface growth is represented using a geometric evolution law. In particular, the focus is set on the control of dendritic crystal growth and wind-aided wildfire sprea