Fluctuations and correlations in sandpiles and interfaces with boundary pinning

Interfaces are studied in an inhomogeneous critical state where boundary pinning is compensated with a ramped force. Sandpiles driven off the self-organized critical point provide an example of this ensemble in the Edwards-Wilkinson (EW) model of kinetic roughening. A crossover from quenched to thermal noise violates spatial and temporal translational invariances. The bulk temporal correlation functions have the effective exponents β1D∼0.88±0.03 and β2D∼0.52±0.05, while at the boundaries βb,1D/2D∼0.47±0.05. The bulk β1D is shown to be reproduced in a randomly kicked thermal EW model.

Fluctuations and correlations in sandpiles and interfaces with boundary pinning

Interfaces are studied in an inhomogeneous critical state where boundary pinning is compensated with a ramped force. Sandpiles driven off the self-organized critical point provide an example of this ensemble in the Edwards-Wilkinson (EW) model of kinetic roughening. A crossover from quenched to thermal noise violates spatial and temporal translational invariances. The bulk temporal correlation functions have the effective exponents β1D∼0.88±0.03 and β2D∼0.52±0.05, while at the boundaries βb,1D/2D∼0.47±0.05. The bulk β1D is shown to be reproduced in a randomly kicked thermal EW model.

The role of pinning and instability in a class of non-equilibrium growth models

We study the dynamics of a growing crystalline facet where the growth mechanism is controlled by the geometry of the local curvature. A continuum model, in (2+1) dimensions, is developed in analogy with the Kardar-Parisi-Zhang (KPZ) model is considered for the purpose. Following standard coarse graining procedures, it is shown that in the large time, long distance limit, the continuum model predicts a curvature independent KPZ phase, thereby suppressing all explicit effects of curvature and local pinning in the system, in the "perturbative" limit. A direct numerical integration of this growth equation, in 1+1 dimensions, supports this observation below a critical parametric range, above which generic instabilities, in the form of isolated pillared structures lead to deviations from standard scaling behaviour. Possibilities of controlling this instability by introducing statistically "irrelevant" (in the sense of renormalisation groups) higher ordered nonlinearities have also been discussed.

Probabilistic synchronisation of pinning control

This paper is concerned with synchronization of complex stochastic dynamical networks in the presence of noise and functional uncertainty. A probabilistic control method for adaptive synchronization is presented. All required probabilistic models of the network are assumed to be unknown therefore estimated to be dependent on the connectivity strength, the state and control values. Robustness of the probabilistic controller is proved via the Liapunov method. Furthermore, based on the residual error of the network states we introduce the definition of stochastic pinning controllability. A coupled map lattice with spatiotemporal chaos is taken as an example to illustrate all theoretical developments. The theoretical derivation is complemented by its validation on two representative examples.

Comparison between conventional and stochastic pinning control

Theoretical developments on pinning control of complex dynamical networks have mainly focused on the deterministic versions of the model dynamics. However, the dynamical behavior of most real networks is often affected by stochastic noise components. In this paper the pinning control of a stochastic version of the coupled map lattice network with spatiotemporal characteristics is studied. The control of these complex dynamical networks have functional uncertainty which should be considered when calculating stabilizing control signals. Two feedback control methods are considered: the conventional feedback control and modified stochastic feedback control. It is shown that the typically-used conventional control method suffers from the ignorance of model uncertainty leading to a reduction and potentially a collapse in the control efficiency. Numerical verification of the main result is provided for a chaotic coupled map lattice network. © 2011 IEEE.

Generalised Riccati solution and pinning control of complex stochastic networks

This paper considers the global synchronisation of a stochastic version of coupled map lattices networks through an innovative stochastic adaptive linear quadratic pinning control methodology. In a stochastic network, each state receives only noisy measurement of its neighbours' states. For such networks we derive a generalised Riccati solution that quantifies and incorporates uncertainty of the forward dynamics and inverse controller in the derivation of the stochastic optimal control law. The generalised Riccati solution is derived using the Lyapunov approach. A probabilistic approximation type algorithm is employed to estimate the conditional distributions of the state and inverse controller from historical data and quantifying model uncertainties. The theoretical derivation is complemented by its validation on a set of representative examples.