Event-triggered fault detection for continuous-time networked polynomial-fuzzy-model-based systems

Dan Ye and Xiehuan Li

Applied Mathematics and Computation, 2020, vol. 366, issue C

Abstract: The paper deals with the event-triggered fault detection filter design problem for continuous-time networked polynomial-fuzzy-model-based (PFMB) systems. Unlike some existing results, a novel polynomial event-triggered mechanism (PETM) is introduced to reduce the network resource occupancy. Moreover, the resultant event-triggered conditions are checked only at each sampling instant. A polynomial fault detection filter (PFDF), whose membership functions (MFs) and fuzzy rules are different from the considered PFMB systems, is designed to ensure the augmented PFMB fault detection system is asymptotically stable with H∞ performance. The communication delay in communication network transmission is also considered. By adopting an appropriate Lyapunov–Krasovskii (L-K) functional, the sum of square (SOS)-based design conditions are less conservative and time-delay dependent. Two examples are used to demonstrate the effectiveness of the proposed method.

Keywords: Continuous polynomial fuzzy model; Fault detection; Polynomial event-triggered mechanism; Sum of squares; Mismatched premise membership functions (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:366:y:2020:i:c:s0096300319307210

DOI: 10.1016/j.amc.2019.124729

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