Q
Qinyuan Liu
Researcher at Tongji University
Publications - 40
Citations - 1467
Qinyuan Liu is an academic researcher from Tongji University. The author has contributed to research in topics: Wireless sensor network & Filter (signal processing). The author has an hindex of 14, co-authored 33 publications receiving 1101 citations. Previous affiliations of Qinyuan Liu include Tsinghua University.
Papers
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Journal ArticleDOI
Event-Based Recursive Distributed Filtering Over Wireless Sensor Networks
TL;DR: The distributed filtering problem is investigated for a class of discrete time-varying systems with an event-based communication mechanism, where a novel matrix simplification technique is developed to handle the challenges resulting from the sparseness of the sensor network topology and filter structure preserving issues.
Journal ArticleDOI
A survey of event-based strategies on control and estimation
TL;DR: This survey aims to summarize the results available in the literature on event-based strategies so as to promote the related research in this realm and point out some potential future research directions.
REVIEW A survey of event-based strategies on control and estimation
Qinyuan Liu,Zidong Wang,Xiao He +2 more
TL;DR: In this article, the authors summarize the results available in the literature on event-based strategies so as to promote the related research in this realm and highlight some potential future research directions.
Journal ArticleDOI
On Kalman-Consensus Filtering With Random Link Failures Over Sensor Networks
TL;DR: Sufficient conditions for the stochastic boundedness of the Kalman-consensus filter are established and it is shown that the filtering performance is directly influenced by the network connectivity and the collective observability.
Journal ArticleDOI
Event-Based $H_{\infty}$ Consensus Control of Multi-Agent Systems With Relative Output Feedback: The Finite-Horizon Case
TL;DR: The aim of the problem addressed is to co-design the time-varying controller and estimator parameters such that the controlled multi-agent systems achieve consensus with a disturbance attenuation level γ over a finite horizon.