Optimal reduced-order synchronization of chaotic neuron models with unknown parameters

摘要: In this paper, reduced-order synchronization of uncertain chaotic neuron models with different orders is investigated. The identifier and controller modules are designed completely independently. A modified recursive least square algorithm used to identify the unknown parameters slave system, control module based on optimal strategy. performance index introduced, by minimizing a Hamiltonian function both deviation from desired trajectory needed signal minimized. HR model cable cylindrical cell considered as master systems, respectively. Simulation results confirm effectiveness proposed method, even in present parameter variations.