Clustering control of chaos universal learning network
Kotaro Hirasawa, Junichiro Misawa, Junichi Murata, Machiko Ohbayashi, Jinglu Hu · 2002
Recently many researchers have paid much attention to chaotic systems since chaos is a key phenomena in complex systems. Chaos control methods such as that due to Ott, Grebogi and Yorke (1990) have been developed in order to stabilise chaotic phenomena. This paper presents a new method for controlling the clustering of chaotic phenomena in stead of restraining them. A chaos network showing chaotic phenomena is constructed by the universal learning network which has been proposed as a general and effective tool for modeling and control of nonlinear large-scale complex systems including physical, social and economical phenomena. From simulations, it has become clear that the clustering of chaotic phenomena can be controlled easily and effectively by the proposed method.