Fault Diagnosis For Complex Networks With A Class Of Incomplete Measurement

The development scale of modern industrial engineering system is getting larger and larger,and the structure is becoming more and more complex.A fault in the system may lead to system malfunction or even disasters,it may result in huge loss of people and property.Therefore,the safety of modern complex systems is crucial.Due to the emergence of fault diagnosis technology,the research on the reliability of complex network systems has also been improved.In the past few decades,fault diagnosis technology has developed rapidly,and has been applied in aviation,aerospace,robotics and other fields.Complex networks are composed of nodes,edges and topological matrices.The establishment of small-world and scale-free models has made complex network models gradually applied to different disciplines such as life,engineering and social sciences.The state information of complex network plays a key role in synchronization,topology identification,synchronization control and fault diagnosis of complex networks.However,in real networks,state information cannot be obtained because of the complex topological relationship,noise,communication delay,and measurement difficulty among network nodes.Therefore,for some factors existing in the above complex networks,the fault diagnosis problem under a kind of incomplete measurement is studied.The main contributions of this paper are as follows:1.For a class of discrete coupled complex network systems with model uncertainties and stochastic communication protocols,state estimation and fault estimation are studied.The random variable is used to describe the packet loss phenomenon,and the gain criterion of the state estimator is given by the augmented state and the solution of the Kalman matrix recursive equation.Through numerical simulation,the state estimator designed in this thesis can estimate the original network state information and fault information.2.For a class of nonlinear coupled complex network systems,the state and fault estimation are studied in the event of event triggering.Using the method of augmented state variable,a state estimator capable of estimating fault information is designed.Based on the solution of the Riccati-like difference equation,the analytic expression of the state estimator parameters is given.Finally,it is meaningful to use numerical simulation to verify the proposed approach.