Event-based fusion estimation for multi-rate systems subject to sensor degradations |
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| Institution: | 1. School of Information Science and Technology, Donghua University, Shanghai 201620, China;2. Engineering Research Center of Digitalized Textile and Fashion Technology, Ministry of Education, Shanghai 201620, China;1. School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China;2. Department of Informatics, School of Natural and Mathematical Science, King’s College London, London WC2R 2LS, UK;1. School of Electrical Engineering and Automation, Changshu Institute of Technology, Changshu, Jiangsu 215500, PR China;2. College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, PR China;1. School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;2. School of Automation, Beijing Institute of Technology, Beijing 100081, China;3. School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100192, China |
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| Abstract: | This paper is concerned with the event-based fusion estimation problem for a class of multi-rate systems (MRSs) subject to sensor degradations. The MRSs under consideration include several sensor nodes with different sampling rates. To facilitate the filter design, the MRSs are transformed into a single-rate system (SRS) by using an augmentation approach. A set of random variables obeying known probability distributions are used to characterize the phenomenon of the sensor degradations. For the purpose of saving the limited communication resources, the event-triggering mechanism (ETM) is adopted to regulate the transmission frequency of the measurements. For the addressed MRSs, we aim to design a set of event-based local filters for each sensor node such that the upper bound of each local filtering error covariance (FEC) is guaranteed and minimized by designing the filter parameter appropriately. Subsequently, the local estimates are fused with the aid of covariance intersection (CI) fusion approach. Finally, a numerical experiment is exploited to demonstrate the usefulness of the developed fusion estimation algorithm. |
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