L
Linchuang Zhang
Researcher at Hohai University
Publications - 15
Citations - 641
Linchuang Zhang is an academic researcher from Hohai University. The author has contributed to research in topics: Fault detection and isolation & Quantization (signal processing). The author has an hindex of 5, co-authored 11 publications receiving 394 citations. Previous affiliations of Linchuang Zhang include Penn State College of Information Sciences and Technology & Bohai University.
Papers
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Journal ArticleDOI
Adaptive Event-Triggered Fault Detection Scheme for Semi-Markovian Jump Systems With Output Quantization
TL;DR: An adaptive event-triggered scheme for S-MJSs that is more effective than conventional event- triggered strategy for decreasing network transmission information is developed and a new adaptive law is designed that can dynamically adjust the event-Triggered threshold is designed.
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Containment Control of Semi-Markovian Multiagent Systems With Switching Topologies
TL;DR: Two kinds of classical control schemes are utilized to address the proposed synthesis problem of the containment control with respect to continuous-time semi- Markovian multiagent systems with semi-Markovian switching topologies.
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Fault Detection for Fuzzy Semi-Markov Jump Systems Based on Interval Type-2 Fuzzy Approach
TL;DR: This article studies the fault detection problem for continuous-time fuzzy semi-Markov jump systems (FSMJSs) by employing an interval type-2 (IT2) fuzzy approach and it can be guaranteed that the constructed fault detection model based on this filter and IT2 FSMJSs is stochastically stable with $H_{\infty }$ performance.
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Fault estimation for a class of nonlinear semi‐Markovian jump systems with partly unknown transition rates and output quantization
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Event-triggered fault detection for nonlinear semi-Markov jump systems based on double asynchronous filtering approach
TL;DR: In this article , a double asynchronous fault detection filter is designed to take the place of the traditional filter and tackle the fault detection problem for fuzzy semi-Markov jump systems, where the premise variables and the modes are usually mismatched for both the filter and the plant in actual network environment.