Recent Advances in Nonlinear Dynamics and Synchronization -

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Résumé :
In essence, the dynamics of real world systems (i.e. engineered systems, natural systems, social systesms, etc.) is nonlinear. The analysis of this nonlinear character is generally performed through both observational and modeling processes aiming at deriving appropriate models (mathematical, logical, graphical, etc.) to simulate or mimic the spatiotemporal dynamics of the given systems. The complex intrinsic nature of these systems (i.e. nonlinearity and spatiotemporal dynamics) can lead to striking dynamical behaviors such as regular or irregular, stable or unstable, periodicity or multi-periodicity, torus or chaotic dynamics. The various potential applications of the knowledge about such dynamics in technical sciences (engineering) are being intensively demonstrated by diverse ongoing research activities worldwide. However, both the modeling and the control of the nonlinear dynamics in a range of systems is still not yet well-understood (e.g. system models with time varying coefficients, immune systems, swarm intelligent systems, chaotic and fractal systems, stochastic systems, self-organized systems, etc.). This is due amongst others to the challenging task of establishing a precise and systematic fundamental or theoretical framework (e.g. methods and tools) to analyze, understand, explain and predict the nonlinear dynamical behavior of these systems, in some cases even in real-time. The full insight in systems? nonlinear dynamic behavior is generally achieved through approaches involving analytical, numerical and/or experimental methods.

Sommaire:
Theoretical Aspects and Recent Trends.- Some Recent Advances in Complex Networks Synchronization.- Networks of Limit Cycle Oscillators with Parametric Learning Capability.- Ragged Synchronizability and Clustering in a Network of Coupled Oscillators.- Cumulant Analysis of Strange Attractors: Theory and Applications.- On Synchronization of Coupled Delayed Neural Networks.- Some Modelling and Simulation Examples.- Multiset of Agents in a Network for Simulation of Complex Systems.- Simulation of Nonlinear Dynamics and Synchronization for Structural Control at Seismic Excitations.- Applications in Transportation.- Emergence of Synchronization in Transportation Networks with Biologically Inspired Decentralized Control.- Synchronization of Movement for a Large-Scale Crowd.- Applications in Security Related System Concepts.- Adaptive Synchronization of Chaotic Systems and Its Uses in Cryptanalysis.- Trust-Based Collaborative Control for Teams in Communication Networks.- Further Application Areas - Pattern Recognition and Communications Engineering.- Coupled Oscillator systems for Microwave Applications: Optimized Design Based on the Study and Control of the Multiple Coexisting Solutions in Systems with Symmetry.