Multiobjective synchronization of coupled systems

Abstract

Copyright @ 2011 American Institute of PhysicsSynchronization of coupled chaotic systems has been a subject of great interest and importance, in theory but also various fields of application, such as secure communication and neuroscience. Recently, based on stability theory, synchronization of coupled chaotic systems by designing appropriate coupling has been widely investigated. However, almost all the available results have been focusing on ensuring the synchronization of coupled chaotic systems with as small coupling strengths as possible. In this contribution, we study multiobjective synchronization of coupled chaotic systems by considering two objectives in parallel, i. e., minimizing optimization of coupling strength and convergence speed. The coupling form and coupling strength are optimized by an improved multiobjective evolutionary approach. The constraints on the coupling form are also investigated by formulating the problem into a multiobjective constraint problem. We find that the proposed evolutionary method can outperform conventional adaptive strategy in several respects. The results presented in this paper can be extended into nonlinear time-series analysis, synchronization of complex networks and have various applications

Identifying Controlling Nodes in Neuronal Networks in Different Scales

“…Using an appropriate encoding scheme, differential evolution (DE) is used to select driver nodes and design control gains. Evolutionary algorithms have been successfully used in the synchronization of two coupled systems in [55], the coordination of unmanned aircraft vehicle [43] and networks topology with optimal synchronizability [56]. Here, adaptive differential evolution is adopted to identify the controlling nodes [38].…”

On Controllability of Neuronal Networks With Constraints on the Average of Control Gains

“…1. The control systems under saturation has been investigated in model predictive control (MPC) [48], networked control systems [31], [49] and synchronization of coupled systems [30]. In [21], the impacts of control gains on distributed synchronization are shown analytically and an upper bound of control gains was derived.…”

“…In [29], pinning state feedback controllers have been designed to synchronize a state coupled dynamical networks. In addition to the mathematical methods to study the controllability of complex networks, some efforts on choosing key nodes by utilizing evolutionary methods have been made [27], [28], [30]. The problem of pinning control of complex networks has been converted into an unconstrained problem [27] and a constrained one [28], respectively.…”

Passive synchronization for Markov jump genetic oscillator networks with time-varying delays

“…Synchronization, as an emerging phenomenon of dynamically interacting systems, has played an important role in different fields, such as biology, ecology, sociology and technology [7][8][9]. Recently, some researchers have sparked an interest in the synchronization of GONs to offer insight into the nature of diverse biological systems and to design coupled GONs in practice [10][11][12][13].…”