Premium
Synchronization and control in a cellular neural network of chaotic units by local pinnings
Author(s) -
Jankowski S.,
Londei A.,
Lozowski A.,
Mazur C.
Publication year - 1996
Publication title -
international journal of circuit theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.364
H-Index - 52
eISSN - 1097-007X
pISSN - 0098-9886
DOI - 10.1002/(sici)1097-007x(199605/06)24:3<275::aid-cta916>3.0.co;2-t
Subject(s) - chaotic , synchronization (alternating current) , cellular neural network , lorenz system , control theory (sociology) , synchronization of chaos , connection (principal bundle) , computer science , artificial neural network , state (computer science) , topology (electrical circuits) , control (management) , mathematics , algorithm , artificial intelligence , geometry , combinatorics
We present a new technique for controlling the behaviour of a large system composed of chaotic units by using only a few control units referred to as pinnings. Our model can be regarded as an extension of cellular neural networks to chaotic cells, in this paper described by Lorenz equations, locally coupled by identical connections. The network is of moderate size, 27 × 27. By tuning the connection strength D , a large variety of global behaviours can be obtained: from fully turbulent to fully coherent spatiotemporal states. In between the system exhibits unstable partial synchronization. We show that by using one (or only a few) unit(s) controlled on a chosen unstable periodic orbit by the standard method of Ott, Grebogi and Yorke (OGY), the global dynamics can be substantially changed: all units tend to obey periodic dynamics. By appropriate placement of pinnings the spatiotemporal state of the network can be ordered and shaped.