Synchronization of Coupled Chaotic Neurons with Unknown Time Delays via Adaptive Backstepping Control
نویسندگان
چکیده
In this study, an adaptive Neural Network (NN) based backstepping controller is proposed to realize chaos synchronization of two gap junction coupled FitzHugh-Nagumo (FHN) neurons with uncertain time delays. In the designed backstepping controller, a simple Radial Basis Function (RBF) NN is used to approximate the uncertain nonlinear part of the error dynamical system. The weights of the NN are tuned on-line. A LyapunovKrasovskii function is designed to overcome the difficulties from the unknown time delays. Moreover, to relax the requirement for boundness of disturbance, an adaptive law to adapt the disturbance in real time is given. According to the Lyapunov stability theory, the stability of the closed error system is guaranteed. The control scheme is robust to the uncertainties such as approximate error, ionic channel noise and external disturbances. Chaos synchronization is obtained by proper choice of the control parameters. The simulation results demonstrate the effectiveness of the proposed control method.
منابع مشابه
ADAPTIVE FUZZY TRACKING CONTROL FOR A CLASS OF NONLINEAR SYSTEMS WITH UNKNOWN DISTRIBUTED TIME-VARYING DELAYS AND UNKNOWN CONTROL DIRECTIONS
In this paper, an adaptive fuzzy control scheme is proposed for a class of perturbed strict-feedback nonlinear systems with unknown discrete and distributed time-varying delays, and the proposed design method does not require a priori knowledge of the signs of the control gains.Based on the backstepping technique, the adaptive fuzzy controller is constructed. The main contributions of the paper...
متن کاملAdaptive Fractional-order Control for Synchronization of Two Coupled Neurons in the External Electrical Stimulation
This paper addresses synchronizing two coupled chaotic FitzHugh–Nagumo (FHN) neurons with weakly gap junction under external electrical stimulation (EES). To transmit information among coupled neurons, by generalization of the integer-order FHN equations of the coupled system into the fractional-order in frequency domain using Crone approach, the behavior of each coupled neuron relies on its pa...
متن کاملAnti-Synchronization of Complex Chaotic T-System Via Optimal Adaptive Sliding-Mode and Its Application In Secure Communication
In this paper, an optimal adaptive sliding mode controller is proposed for anti-synchronization of two identical hyperchaotic systems. We use hyperchaotic complex T-system for master and slave systems with unknown parameters in the slave system. To construct the optimal adaptive sliding mode controller, first a simple sliding surface is designed. Then, the optimal adaptive sliding mode controll...
متن کاملADAPTIVE FUZZY OUTPUT FEEDBACK TRACKING CONTROL FOR A CLASS OF NONLINEAR TIME-VARYING DELAY SYSTEMS WITH UNKNOWN BACKLASH-LIKE HYSTERESIS
This paper considers the problem of adaptive output feedback tracking control for a class of nonstrict-feedback nonlinear systems with unknown time-varying delays and unknown backlash-like hysteresis. Fuzzy logic systems are used to estimate the unknown nonlinear functions. Based on the Lyapunov–Krasovskii method, the control scheme is constructed by using the backstepping and adaptive techniqu...
متن کاملSynchronization of a Heart Delay Model with Using CPSO Algorithm in Presence of Unknown Parameters
Heart chaotic system and the ability of particle swarm optimization (PSO) method motivated us to benefit the method of chaotic particle swarm optimization (CPSO) to synchronize the heart three-oscillator model. It can be a suitable algorithm for strengthening the controller in presence of unknown parameters. In this paper we apply adaptive control (AC) on heart delay model, also examine the sys...
متن کامل