Lijuan Zha;Yaping Guo;Jinliang Liu;Xiangpeng Xie;Engang Tian;Jinde Cao
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引用次数: 0
Abstract
In this article, a novel distributed fusion estimation approach is proposed for time-varying systems with unknown bounded noises subject to bandwidth-constrained networks and denial-of-service (DoS) attacks, where the round-robin scheduling protocol and the quantization scheme are, respectively, employed to ease the burden of networks. It is assumed that the network connecting sensors and local state estimators is vulnerable to DoS attacks. For resisting the impacts of DoS attacks, a compensation strategy is adopted. A new method has been developed to devise the local state estimators. The innovation signals from local estimators will be quantized first before entering the network. Gains of the local state estimators and the fusion weighting matrices are acquired by solving a linear matrix inequality. Finally, the effectiveness of the proposed methods is verified by a target tracking system.
期刊介绍:
The IEEE Transactions on Control of Network Systems is committed to the timely publication of high-impact papers at the intersection of control systems and network science. In particular, the journal addresses research on the analysis, design and implementation of networked control systems, as well as control over networks. Relevant work includes the full spectrum from basic research on control systems to the design of engineering solutions for automatic control of, and over, networks. The topics covered by this journal include: Coordinated control and estimation over networks, Control and computation over sensor networks, Control under communication constraints, Control and performance analysis issues that arise in the dynamics of networks used in application areas such as communications, computers, transportation, manufacturing, Web ranking and aggregation, social networks, biology, power systems, economics, Synchronization of activities across a controlled network, Stability analysis of controlled networks, Analysis of networks as hybrid dynamical systems.