Finite-time And Fixed-time Synchronization Control For Two Types Of Fuzzy Inertial Neural Networks

In this thesis,the synchronization problem of two class of fuzzy inertial neural networks is studied based on the non-reduced order method.By using the maximum-value approach of functions instead of the finite-time stability theorem,two class of finite-time synchronization criteria of fuzzy inertial neural networks are obtained by constructing suitable Lyapunov function and feedback controller.Using the fixed-time stability theorem and inequality technique,the fixed-time synchronization problem of two class of systems is discussed.The existence and uniqueness of the equilibrium point in fuzzy inertial BAM neural network is proved by using the contraction mapping principle.Finally,the validity of the theoretical results in this thesis is verified by numerical simulation.This thesis is divided into four chapters:Chapter 1 mainly introduces the research overview of fuzzy inertial neural network,Cohen-Grossberg neural network synchronization and BAM neural network synchronization,and also explains some symbols in this thesis.In Chapter 2,the finite-time and fixed-time synchronization of fuzzy inertial neutral Cohen-Grossberg neural networks is studied.A new function maximum lemma is proposed and used to obtain sufficient conditions for finite-time synchronization by designing an adaptive controller.In addition,the fixed-time synchronization criterion is acquired by using the fixed-time stability theorem and inequality technique.In Chapter 3,the finite-time and fixed-time synchronization of fuzzy inertial BAM neural networks are studied.The existence and uniqueness of the system equilibrium point is proved by using the contraction mapping principle.This thesis improves the fixed-time stability theorem in the existing literature and uses it to discuss the problem of fixed-time synchronization.By constructing an appropriate feedback controller and using the maximumvalue approach of functions,the sufficient conditions for the finite-time synchronization of the system are obtained.Chapter 4 summarizes the main work and innovation of this thesis,and gives the direction of further research for the future study.