Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms

作     者：Ying SUN Miaomiao FU Jingyang MAO Guoliang WEI Ying SUN;Miaomiao FU;Jingyang MAO;Guoliang WEI

作者机构：Business SchoolUniversity of Shanghai for Science and TechnologyShanghai200093China Shanghai Caoyang Vocational SchoolShanghai200333China School of Electrical and Electronic EngineeringShanghai Institute of TechnologyShanghai201418China School of Intelligent Emergency ManagementUniversity of Shanghai for Science and TechnologyShanghai200093China 

出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)

年 卷 期：2024年第25卷第2期

页      面：250-259页

核心收录：

学科分类：0711[理学-系统科学] 0808[工学-电气工程] 07[理学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Project supported by the National Natural Science Foundation of China(Nos.62203306 and 61933007) the Shanghai Pujiang Program,China(No.22PJ1412600) the China Postdoctoral Science Foundation(No.2021M702195)。 

主　　题：Cyber-physical systems Multi-rate Joint recursive filtering Adaptive event-triggered mechanisms Unknown inputs 

摘      要：Cyber-physical systems(CPSs)take on the characteristics of both multiple rates of information collection and processing and the dependency on information exchanges.The purpose of this paper is to develop a joint recursive filtering scheme that estimates both unknown inputs and system states for multi-rate CPSs with unknown inputs.In cyberspace,the information transmission between the local joint filter and the sensors is governed by an adaptive event-triggered strategy.Furthermore,the desired parameters of joint filters are determined by a set of algebraic matrix equations in a recursive way,and a sufficient condition verifying the boundedness of filtering error covariance is found by resorting to some algebraic operation.A state fusion estimation scheme that uses local state estimation is proposed based on the covariance intersection(CI)based fusion conception.Lastly,an illustrative example demonstrates the effectiveness of the proposed adaptive event-triggered recursive filtering algorithm.