Research On Recursive Filtering For Time-Varying Systems In The Sense Of Energy-Saving And Secure Transmission

Improving quality and efficiency is a long-term strategic measure for China's oil industry to achieve high-quality development,and the intellectualized transformation of oilfields is imperative.With the development of information technology and the continuous advancement of smart oilfields construction,the application of wireless communication networks is becoming more and more extensive.Sensors rely on the networks to transmit production data in real time,which plays an important role in ensuring the smooth operation of oilfields.As the oilfield networks continue growing,the problems of energy saving and safety during information transmission have become increasingly prominent.In order to ensure the sustainable development of China's petroleum industry,energy saving and security have become the basic requirements for the smart oilfield construction.How to ensure the accuracy of production data under the energy-saving wireless transmission mechanism,and how to ensure the reliability of production data in the case of network being attacked are extremely challenging issues.In this thesis,the recursive filtering method is used as the key technology to study the above problems.The corresponding filters are designed by using Lyapunov theory,stochastic analysis techniques,and so on,which achieve the purpose of ensuring the accuracy and reliability of production data on the premise of energy saving and security wireless transmission.To be specific,the main research contents of the thesis are as follows.First,an energy-saving transmission mechanism based on duty cycle is considered.A novel filter is designed for two classes of linear time-varying systems,which solves the problem that the filtering accuracy is affected by the significant reduction of measurement transmission under the duty cycle transmission mechanism(DCTM).To be specific,the mathematical model of the DCTM is first created.Then,a recursive filtering scheme combined with the collaborative prediction(CP)is proposed.Furthermore,the recursive filtering problems for a class of linear discrete-time systems and a class of time-varying systems with uncertainty are discussed,and the boundedness of filtering error covariance matrix and its upper bound are analyzed respectively.The proposed filtering method attains the goal of improving the filtering performance during ensuring the energy-saving effect.Second,a recursive filtering algorithm is designed for a class of complex networks(CNs)with random coupling strengths(RCSs)under event-triggered transmission mechanism(ETTM),which solves the problem of filtering performance affected by data congestion due to limited network bandwidth.Under the comprehensive framework of ETTM,state saturations and RCSs,a recursive filtering algorithm based on each node and its adjacency information is first developed for such complex networks.Then,the mean square exponential boundedness(MSEB)of the error dynamic system is analyzed and the corresponding parameterized conditions are obtained.It is realized that the developed filtering scheme ensures the efficient data transmission and improves system filtering performance under the premise of energy saving.Third,a security filtering algorithm is proposed for a class of CNs with uncertain coupling strengths subject to deception attacks(DAs),which addresses the problem of serious degradation of filter performance.Specifically,the state saturated CNs under DAs and uncertain coupling strengths are taken into account,and the recursive filtering algorithm relying on local information is put forward.Subsequently,a sufficient condition to guarantee the MSEB of the error dynamic system is presented.The designed filtering scheme promotes the filtering performance for this class of CNs under DAs.Next,under the unified framework of energy saving and security,a novel filtering scheme is developed for a class of nonlinear time-varying systems,which addresses the problem of filtering performance deterioration when the system is under DAs and DCTM.More specifically,the scenarios that the amount of measurement data received is reduced heavily and the system is subjected to DAs are taken into account.A recursive filtering algorithm based on CP is proposed.Then,an upper bound of the filter error covariance matrix is derived and the boundedness of the upper bound is analyzed.The proposed filtering method improves the filtering effects of nonlinear time-varying systems under the complex scene,and achieves the objective of ensuring filtering performance on the premise of energy saving and safety.Finally,the discrete-time state space expression of the natural gas pipeline flow system is deduced,and the time-varying uncertain model of the system is constructed.The abovementioned theoretical results on energy saving and security are applied to the time-varying uncertain model.The simulation results show that the filter algorithm designed can effectively estimate the pressure and the flow rate inside the pipeline on the premise of ensuring energy saving and security.The research results of this thesis provide some new theoretical guidance for ensuring the green and safe operation of oilfield.