State Estimation Of Discrete Stochastic Complex Networks Based On Network Communication Protocol

Complex networks are abstract models of many natural and artificial systems.Because of their strong coupling,inherent nonlinearity and large scale it is very difficult to obtain real-time state information of complex networks.In recent decades,the state estimation of complex networks in the field of control has been one of the main research directions of scholars.Due to the rapid development of network communication technology,the measurement information needs to be realized through a shared communication network before being transmitted to the estimator,which can avoid a large number of point-to-point wiring in complex network systems.This arrangement not only makes installation more flexible,but also reduces the cost of installation and later maintenance.However,the introduction of communication network will inevitably lead to networkinduced phenomenon,such as packet dropouts,communication delay,channel fading and quantization effect.The system performance will be seriously affected.Moreover,this thesis considers embedding the communication protocol in communication networks to schedule the nodes in the complex network which need to transmit information,so as to avoid the datagram congestion caused by limited bandwidth.This thesis mainly studies the state estimation problem of complex networks with time-varying delays in discrete time under the influence of communication protocols.According to engineering practice,the system may be affected by uniform quantization,multiplicative noise or sensor resolution.Specific research contents are as follows:The first part introduces the characteristics of complex networks,the current research status at home and abroad,and some network induced phenomena.At the same time,it also introduces three common communication protocols in the field of control,analyzes their characteristics and leads to a new protocol.In the second part,we study the finite time state estimation problem for a class of discrete time nonlinear complex networks with Round Robin protocol and uniform quantization effect.The communication between node information and state estimator in complex networks is affected by uniform quantization,and the information must pass through a shared communication network before being transmitted to the estimator.In order to prevent data collisions,Round-Robin protocol is introduced into the communication channel to arrange the transmission order of scheduling nodes periodically.In which only one node information is allowed to be sent to the estimator at each transmission moment.The main purpose of this study is to design a state estimator,which makes the estimation error system dynamically satisfy stochastic finite time boundedness.Then,the gain of the state estimator is obtained by solving a set of linear matrix inequalities.Finally,a simulation example verifies the effectiveness of the proposed estimator design scheme.In the third part,we consider a class of complex networks with FlexRay protocol,and study the state estimation problem of this network affected by the inherent resolution of sensors.In order to improve the efficiency and flexibility of information transmission,a high-rate communication channel is deployed between the sensor and the estimator.Node information of complex networks is scheduled by FlexRay protocol during transmission of high-rate communication channels.The purpose of this thesis is to design a state estimator,so that the estimation error dynamically satisfies the mean square exponential ultimate boundedness under the influence of state-dependent noise and external disturbance.By using Lyapunov stability theory,a sufficient condition for the existence of the estimator is obtained when the estimation error satisfies the expected performance index.Then the MATLAB LMI toolbox is used to calculate the gain matrix of the estimator.Finally,a set of numerical simulation examples verify the effectiveness of the proposed state estimation method.