An Improved Robust ISS-satisfying Control for Synchronization of FHN Neurons

In the conventional robust ISS (input to state stable) which satisfies control strategy, all parameters of the system must be known and deterministic. Since it confines the application, in this paper an attempt is made to create a bridge between two important design techniques, i.e., the robust ISS-satisficing control strategy and the variable universe indirect fuzzy control strategy, to offset this weakness. The new control method proposed has the inverse optimality of robust ISS-satisficing control and the robust and predictive performance of fuzzy control. Due to the control Lyapunov method, the overall closed-loop system is shown to be stable. In this work, the new control strategy is used in synchronization of two FHN neurons. The simulation results are given to confirm the control algorithm is feasible and performances well.