Passivity And Synchronization Of Multi-weight Coupled Neural Networks Based On PD And PI Contro

In recent years,complex networks have been extensively and deeply studied in the fields of system science,computer and information science,mathematics and so on.In particular,passivity and synchronization,as very important dynamical behaviors of complex networks,have been attracted the attention of many researchers.Considering that in many cases,complex networks can not achieve synchronization by themselves,such as adaptive control,impulse control,pinning control,intermittent control and other appropriate control methods have been proposed for application to the synchronization investigation of complex networks.Because the PID controller structure is simple and does not depend on the model,it is widely used in industry.Therefore,PID control methods are also used to study the dynamical behavior of complex networks.On the one hand,as a special complex network,coupled neural network is composed of multiple neural networks,one node represents a neural network,one side represents the effect of one neural network on another neural network,some researchers have obtained many studies on its dynamical behavior,but few authors have studied the passivity and synchronization of coupled neural network multiple time delays based on PD/PI controller.On the other hand,when electrons are transmitting in asymmetric electromagnetic fields,the phenomenon of reaction-diffusion cannot be avoided.Therefore,it is very meaningful to further study the passivity and synchronization of the multiple state and multiple spatial diffusion couplings neural network based on PD controller.In this paper,the passivity and synchronization of the multi-weighted coupled neural network with uncertain parameters based on PD/PI control method are studied,and the passivity and synchronization of the coupled reaction-diffusion neural network based on PD controller are further discussed.First,a class of coupled neural networks with multiple time delays and uncertain parameters is proposed.By utilizing the Lyapunov functional method and related inequality techniques,the passivity and synchronization of the proposed network are obtained.By designing a suitable PI controller,some criteria for passivity and synchronization of the network are derived.Secondly,two types of coupling reaction-diffusion neural networks with multiple state couplings and multiple spatial diffusion couplings are proposed,and some passivity conditions of the networks are obtained by using the designed PD controller and some inequality techniques.Further use of the obtained output-strict passivity conditions,obtained two sufficient conditions to ensure the synchronization of the network.Finally,some numerical simulation examples are used to verify the validity of the results obtained in this paper.