Multi-synchronization of chaos via linear output feedback strategy

Abstract

Multi-synchronization of chaotic systems based on the master-slave scheme as an extension of the dual synchronization problem is introduced. It is assumed that the only information available from the master systems is a linear combination of their state vectors. The design procedure for multi-synchronization through output feedback strategy is described and the sufficient condition is given. The performance of the proposed algorithm is numerically examined by applying it to the Chen-Lorenz-Rossler and the Duffing-Van der Pol chaotic systems. Simulation results show the effectiveness of the proposed scheme.

A simple adaptive-feedback scheme for identical synchronizing chaotic systems with uncertain parameters

“…In addition, the proposed adaptive laws for uncertain parameters are very effective and relatively tractable on account of the independence of error dynamical systems. The present synchronization scheme is also available for multi-linearly-coupled chaotic systems [43]. This is because the drive system can drive the uncertain response system via the linear error feedback interactions, no matter how big difference there is in the initial regime.…”

Multisynchronization for Coupled Multistable Fractional-Order Neural Networks via Impulsive Control

“…Synchronization phenomenon within complex networks is one of the most intriguing and valuable issues [13][14][15][16]. Recently, as a special case of an online learning situation, synchronization of neurodynamic systems have been found to be useful in characterizing and validating the consistency of cooperation [1,8,9,11,12].…”

Adaptive observer-based synchronization of two non-identical chaotic systems with unknown parameters

“…Synchronization of two chaotic systems with different dynamics has been studied in several works (Yassen, 2005; Salarieh and Shahrokhi, 2008a). In addition, multi-synchronization of chaos has been studied in (Salarieh et al., 2009). Also various control methods such as feedback linearization (Chen and Han, 2003; Zhang et al., 2007), sliding mode (Alasty and Salarieh, 2008; Dadras and Momeni, 2010), back-stepping (Tan et al., 2003) and etc.…”