Distributed Observer Design For Continuous Time Control System

With the rapid development and integration of computer technology,the estimation and control of networked systems composed of sensors such as intelligent factories and the Internet of Things have received considerable attention in the field of control systems in recent years.Among them,distributed state estimation is one of the key issues in modern sensor networks.Distributed estimation is widely used in target tracking,intelligent control and complex environment monitoring because of its flexibility and robustness.However,there are some difficulties to study the distributed estimation problem because the observed system and the local measurement output cannot form the observable system.Nowadays,distributed estimation has attracted more and more attention and achieved rich research results.However,there are still many problems to be further studied and discussed in the terms of simplifying research methods,boradening application scope and relaxing graph toopology requirements.In this paper,the distributed estimation problem of networked systems with communication link variation and bounded uncertain interference is studied as follows:1.For the problem that the traditional centralized design method lacks adaptability due to the change of communication topology caused by network reconfiguration,communication faults and redundant sensor integration,a full-dimensional state distributed function observer for linear systems is designed.The proposed distributed observer has two characteristics:first,it increases the fault tolerance of communication link failure,and second,it improves the flexibility of integrating additional sensors into the network.Through matrix transformation,recombination,Riccati equation,Lyapunov theory,graph theory and other related theories,the sufficient conditions for the existence of full-dimensional state distributed function observer are found and the effectiveness of the method is verified by a simulation example.2.For the distributed interval estimation problem of systems with known bounded disturbances,the distributed interval observers design based on the Internal Positive Representations is originally proposed.Existing interval observer designs are mainly suitable for cooperative and consistent systems,and cannot be directly extended to distributed estimation applications.For the distributed estimation problem of non cooperative and consistent systems,this paper improves the interval estimation scheme,converts the original system into a positive system by using the positive representation,designs an interval observer for the positive system,and extends the application range of the distributed interval observer.3.For linear time invariant systems with bounded disturbances,an event triggered controller based on event triggered distributed interval observer is proposed.Firstly,a distributed interval observer is established to estimate the upper and lower bounds of the system state using only partial outputs and neighbor communication information.Secondly,the sufficient conditions for the distributed feedback controller stability are given by using the interval estimation information.Finally,a distributed feedback control scheme under event-triggered communication strategy is proposed based on interval estimation information.It is proved theoretically that the method is uniformly ultimately bounded stable and avoids Zeno behavior.4.For linear time invariant systems with bounded disturbances,a fault detection scheme based on distributed interval observers is designed,which expands the application range of distributed interval observers.Firstly,a new distributed interval observer is designed and a fault detection error system is constructed by coordinate transformation and vector rearrangement.Secondly,based on the interval estimation results,each sensor node determines the reasonable interval of the local output of the system.When the local output deviates from the reasonable interval,the fault is detected.Finally,the effectiveness of the proposed method is verified by theoretical proof and simulation examples.