ABSTRACT
Objective To study the self-adaptive anti-control of a single H-R neuronal system transformed from periodic dynamics pattern to chaos. Methods Numerical analysis was performed by adding sine function self-delay feedback while coupling intensity and time-delay, respectively, as the control parameters. Results By numerical simulation and analysis, it was found that in a certain range of the combination of coupling intensity and time-delay, the time-interval sequences of the dynamical pattern of a single H-R neuronal system could be controlled from a periodical pattern of 3 spikes onto chaos and other periodical patterns. Conclusions The method of self-adaptive feedback of sine function is effective for the anti-control of H-R neuron, and the coupling intensity and time-delay are both important parameters. The particular self-adaptive dynamics of information identification to neuron is reflected in the control process.
ABSTRACT
With regard to the bounded linear continuous-time system, a universal chaotic anti-controlling method was presented on the basis of tracking control. A tracking controller is designed to such an extent that it can track any chaotic reference input, thus making it possible to chaotify the linear system. The controller is identical in structure for different controlled linear systems. Computer simulations proved the effectiveness of the proposed method.
ABSTRACT
With regard to the bounded linear continuous-time system, a universal chaotic anti-controlling method was presented on the basis of tracking control. A tracking controller is designed to such an extent that it can track any chaotic reference input, thus making it possible to chaotify the linear system. The controller is identical in structure for different controlled linear systems. Computer simulations proved the effectiveness of the proposed method.