### Fuzzy Filter Design for Affine Systems with Sensor Faults:A Dynamic Event-Triggered Approach

CHENG Jun1, WU Yuyan1,2, WU Zhengguang3, LI Kezan4

1. 1. School of Mathematics and Statistics, Center for Applied Mathematics of Guangxi, Guangxi Normal University, Guilin 541006, China;
2. School of Information Science and Engineering, Chengdu University, Chengdu 610106, China;
3. Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China;
4. School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China
• Received:2021-03-14 Revised:2021-05-11 Online:2022-10-25 Published:2022-10-12
• Supported by:
This research was supported by the National Natural Science Foundation of China under Grant Nos.12161011,62173100,the National Natural Science Foundation of Guangxi Province under Grant Nos.2020GXNSFAA159049 and 2020GXNSFFA297003,the Guangxi Science and Technology Base and Specialized Talents under Grant No.Guike AD20159057,the Innovation Project of Guangxi Graduate Education under Grant No.YCSW2021103,and the Training Program for 1,000 Young and Middle-Aged Cadre Teachers in Universities of Guangxi Province

CHENG Jun, WU Yuyan, WU Zhengguang, LI Kezan. Fuzzy Filter Design for Affine Systems with Sensor Faults:A Dynamic Event-Triggered Approach[J]. Journal of Systems Science and Complexity, 2022, 35(5): 1761-1784.

This study addresses the issue of dynamic event-triggered-based filtering for fuzzy affine systems.To alleviate the utilization of constraint bandwidth resources and improve the efficiency of the signals exchange,a dynamic event-triggered protocol is forwarded to regulate the trigger instants with objective system states.Meanwhile,the nonhomogeneous Markov process is proposed to characterize the dynamic behaviors of sensor faults,where the time-varying transition probabilities belong to a convex polytope set.Finally,the validity and applicability of devised filter design methodology for fuzzy affine systems are displayed via two practical models.
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