Synchronization Control Of Markovian Jumping Complex Networks And Its Application In Multi Motor System

In real life,there are many networked systems formed by node coupling.Due to the influence of environment,fault,control demand and other factors,the system state or network topology will change randomly,so it has important application value to study Markovian jumping complex network synchronous control.At the same time,with the continuous improvement of production efficiency,the coordinated operation of motor interconnection has gradually become the mainstream operation mode of modern industry.This paper studies the Markovian jumping complex network with different weights,establishes the model and designs the corresponding finite time synchronous controller.It analyzes the nonlinearity of the permanent magnet synchronous motor,and applies it to the Markovian jumping complex network composed of permanent magnet synchronous motor to realize the finite time synchronous control and parameter identification.The main work is as follows:(1)Firstly,the mathematical model of single-weight Markovian jumping complex networks with stochastic perturbations,uncertain parameters and different initial conditions is constructed.Secondly,based on the ItO's formula and the stability theory of finite-time,a reliable finite time adaptive controller is proposed to ensure the synchronization of the network in different situations.At the same time,the corresponding sufficient conditions are given to ensure that the uncertain parameters in the network with stochastic perturbations can be identified accurately.Finally,the effectiveness of the control strategy is proved by numerical simulation.(2)Based on the analysis of single-weight Markovian jumping complex network,the synchronization of double-weights Markovian jumping complex network is studied.First of all,a network splitting method is proposed,which divides different coupling structures into different subnetworks,so as to build a mathematical model of double-weights Markovian jumping complex network.Secondly,the corresponding finite time adaptive controller is obtained.Finally,the synchronization control and parameter identification of complex networks with stochastic perturbations and double-weights Markovian jumping are realized,and the feasibility of the conclusion is verified by numerical simulation.(3)In the Markovian jumping complex network composed of permanent magnet synchronous motor,the unstable operation of nodes can reduce the performance of the system,even destroy the synchronization state of the network.Therefore,it is necessary to analyze the nonlinear behavior of PMSM to ensure the stable operation of the node system and the network,and then to apply synchronization and parameter identification to the network.In order to reduce the complexity of system parameters,a new compact representation method of nonlinear dynamic differential equation of PMSM is established by using affine transformation method.Based on this,the numerical simulation of different parameters is given,and the dynamic characteristics of the system are analyzed in detail.Secondly,the 2D/3D model of 30kW permanent magnet synchronous motor is designed.The nonlinear behavior of the system is analyzed when the flux ?f changes,and the corresponding rated parameters and dimension data are obtained when the motor works in the optimal state.According to the research conclusion of Markovian jumping complex network synchronization,the synchronization control and parameter identification of multi motor Markovian jumping complex network composed of permanent magnet synchronous motor are finally realized.The control strategy proposed for multiple weight Markovian jumping complex networks can achieve limited time synchronization better and are easy to implement,so it has broad application prospect in the field of complex networks.In addition,the nonlinear dynamics of PMSM is analyzed,and the finite time synchronous control and parameter identification of Markovian jumping complex network composed of PMSM are completed,which can be applied to the field of multi motor operation.