Research On Lag Synchronization Control Of Several Classes Of Complex Networks

The dynamic analysis and control problem of complex neural network systems is a hot issue in recent years.It aims to study the influence of network topology and node dynamics on network synchronization.As we all know,synchronization is a very important cluster dynamics behavior.The phenomenon of synchronization has a profound impact on the work of the real system,which may improve the effect and performance of the work,and may also seriously hinder the normal operation of the system.Therefore,it is a very practical work to study the synchronization behavior of network systems and realize favorable guided control.In this paper,several control methods are used to study the lag synchronization of complex networks and neural networks.The main research contents are as follows:Firstly,the lag synchronization of time-delay complex network under pulse control is studied.By constructing a suitable Lyapunov function,designing an appropriate pulse controller,applying the average pulse interval and the comparison theorem,a sufficient criterion for the lag synchronization of complex networks with time-delay under any initial conditions is obtained.Numerical simulations show the effectiveness of the scheme.Secondly,the lag synchronization of neural networks with time-delay under twocycle intermittent control is studied.Based on the limitation of the single-cycle intermittent control method in practical application,a more flexible and widely used two-cycle intermittent control is proposed.Under this control strategy,the proper Lyapunov function is constructed to verify that the time-delay neural network can achieve lag synchronization,and a sufficient criterion for global exponential stability is obtained.Then,the time-delay neural network lag synchronization based on adaptive control is studied.An adaptive feedback controller is designed based on Cohen-Grossberg model.On this basis,using Lyapunov stability theory,inequality technique and invariant principle,the sufficient conditions for the drive-response system to achieve lag synchronization are obtained.The effectiveness of the method is verified by an example.Finally,the fixed time lag synchronization of inertial time-delay neural networks is studied.Fixed time lag synchronization is bounded by a fixed time constant,which can be calculated according to system parameters and controller parameters.This method solves the problem that the synchronization convergence time of the neural network must depend on the initial state.By designing an appropriate feedback controller and using Lyapunov stability theory and inequality principle,the fixed time lag synchronization of inertial time-delay neural networks is realized.The feasibility of the theoretical results is verified by numerical simulation.