Research On The Fusion Estimation Of Distributed Network Systems Under Time Delay

Cyber-Physical System(CPS)is a comprehensive technology system that integrates computer technology,wireless communication and physical process deeply.CPS enables the virtual information world and physical world to continuously complete dynamic interaction and cooperation,and at the same time realizes intelligent data processing,distributed sensing,dynamic information control and other functions.With the wide development of digitalization,networking and intelligence in its application field,CPS and its related technologies have continuously increased people’s control of the observable controllability of the objective world from the perspective of new fusion space.The spatial environment of CPS is complex and changeable.As the degree of networking deepens,multiple factors such as high-frequency data interaction between operating systems and related execution devices,limited communication bandwidth and complexity of topology structure affect the real-time transmission of network nodes,and system instability problems such as data confusion,loss and timely delay of network attacks frequently occur.To some extent,it leads to CPS security threats and greatly increases the complexity of controlled system analysis and data processing.CPS has a high requirement for real-time performance,so it has important reference significance for the state and performance of the target system.This paper focuses on the fusion estimation of CPS distributed network systems with time delay.The main contents are as follows:(1)The research work introduces the degree of networking development in the field of information physical system technology,and leads to the relevant research questions of integration in CPS time-delay.For the abstract state space model of distributed multi-sensor system,through the recursive analysis of the "prediction-update" process of remote state estimator,combined with the knowledge of multi-sensor data fusion architecture,The theoretical basis for the subsequent fusion estimation scheme is further laid.(2)For the research on weighted fusion estimation of distributed network systems with time delay,firstly,combined with CPS classical model,based on the known correlation of mutual covariance between nodes,the model of fixed measurement delay and stochastic delay in the system is constructed,and the corresponding fusion algorithm is designed through local state estimator recursion.Based on the influence of different estimation accuracy on fusion schemes,the effectiveness and reliability of different fusion algorithms are compared by MATLAB numerical simulation.(3)For the research on fusion estimation of multi-layer distributed network system with time delay,different from the known case of mutual covariance between nodes,considering more complex and practical application scenarios,it is difficult to accurately obtain correlation,and artificial neglect of correlation calculation will lead to adverse effects such as filtering divergence.Covariance Intersection(CI)was introduced to handle the unknown correlation fusion state estimation problem,and it was extended to the multi-layer distributed cross fusion algorithm to further improve the multi-layer cross fusion method and improve the fusion accuracy.Finally,the effectiveness and reliability of the proposed algorithm are verified by MATLAB simulation.(4)For the research on BCI fusion estimation of distributed network systems with time delay,based on the cross fusion algorithm theory of unknown correlation between nodes,the model transformation of correlation noise is completed for the CPS system with unrelated noise in the time-delay phase and the system model with correlation noise in the multi-time delay phase of the measurement phase,and a piecewise BCI fusion structure algorithm is proposed.Considering the accuracy of fusion estimation and the execution speed,a piecewise BFCI fusion algorithm is further proposed.Finally,the effectiveness and reliability of the proposed fusion algorithm are verified by MATLAB numerical simulation comparison.