H
Huaicheng Yan
Researcher at East China University of Science and Technology
Publications - 316
Citations - 6933
Huaicheng Yan is an academic researcher from East China University of Science and Technology. The author has contributed to research in topics: Computer science & Control theory (sociology). The author has an hindex of 35, co-authored 166 publications receiving 4128 citations. Previous affiliations of Huaicheng Yan include China University of Geosciences (Wuhan) & East China Jiaotong University.
Papers
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Event-Based Distributed $H_{\infty }$ Filtering Networks of 2-DOF Quarter-Car Suspension Systems
TL;DR: In order to reduce network traffic load and save communication resources, a novel periodic event-triggered sampling scheme is proposed, under which data are transmitted only when the proposed triggering condition is violated.
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Codesign of Event-Triggered and Distributed $H_{\infty }$ Filtering for Active Semi-Vehicle Suspension Systems
TL;DR: A codesign algorithm is provided to obtain the distributed distributed filtering for a cloud-aided active semi-vehicle suspension system with some unreliable characteristics, such as communication time-delay and limited bandwidth, which are solved by the delay-distribution dependent method and event-triggered scheme, respectively.
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$H_{\infty }$ Fault Detection for Networked Mechanical Spring-Mass Systems With Incomplete Information
TL;DR: The purpose of this paper is to design an FD filter such that the FD dynamic system is exponentially stable in the mean square and the error between the fault signal and the residual signal is controlled to the minimum.
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Distributed $H_\infty$ State Estimation for a Class of Filtering Networks With Time-Varying Switching Topologies and Packet Losses
TL;DR: Some novel sufficient conditions are obtained for ensuring the exponential stability in mean square and the switching topology-dependent filters are derived such that an optimal disturbance rejection attenuation level can be guaranteed for the estimation disagreement of the filtering network.
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Adaptive Consensus-Based Distributed Target Tracking With Dynamic Cluster in Sensor Networks
TL;DR: A novel distributed consensus-based adaptive Kalman estimation is developed to track a linear moving target over a filtering network with dynamic cluster and data fusion to estimate the states of the target more precisely.