Intermittent fault detection for delayed stochastic systems over sensor networks |
| |
| Institution: | 1. School of Automation and Information Engineering, Xi’an University of Technology, China;2. Autonomous Systems and Intelligent Control International Joint Research Center, Xi’an Technological University, China;3. State Key Laboratory of Astronautic Dynamics, China;1. School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China;2. School of Mechanical and Electrical Engineering, Suzhou University of Science and Technology, Suzhou 215000, China;3. School of Science, Huzhou University, Huzhou 313000, China;4. School of Electrical Engineering and Automation, Qufu Normal University, Rizhao 276826, China;1. College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, PR China;2. Faculty of Information Technology, Beijing University of Technology, Beijing 100124, PR China;1. Institute of Complexity Science, Shandong Key Laboratory of Industrial Control Technology, Qingdao University, Qingdao 266071, China;2. Institute of Artificial Intelligence and Future Networks, Beijing Normal University, BNU-HKBU United International College, Zhuhai 519087, China;1. School of Automation, Beijing Institute of Technology, Beijing 100081, China;2. Key Lab of Intelligent Control and Decision of Complex Systems, Beijing 100081, China;3. Beijing Institute of Technology Chongqing Innovation Center, Chongqing 401120, China |
| |
| Abstract: | This paper is concerned with the intermittent fault (IF) detection problem for a class of linear discrete-time stochastic systems over sensor networks with constant time delay. By utilizing the lifting method, the distributed decoupled observers are proposed based on the output information of neighbor nodes and the node itself. In order to detect the appearing time and disappearing time of the IF, the truncated residuals are designed by introducing a sliding-time window. Furthermore, the IF detection and location thresholds are determined based on the hypothesis testing technique and the detectability of the IF is analyzed in the framework of stochastic analysis. Finally, a simulation example is presented to illustrate the effectiveness of the derived results. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
