NDLI: Distributed robust filtering with hybrid consensus strategy for sensor networks

Content Provider	IET Digital Library
Author	Rastgar, Fatemeh Rahmani, Mehdi
Abstract	The problem of distributed state estimation for time-varying uncertain systems over a sensor network within the robust Kalman filtering framework is studied. It is assumed that the parameters of the underlying model are subjected to stochastic uncertainties. At the first step, the authors present a particular form of the Kalman filter named information form of a robust Kalman filter. Then, using a consensus scheme that guarantees an agreement in estimation among nodes, they propose a new consensus-based robust filtering approach. The consensus methodology is a hybrid method that is a combination of consensus on information (CI) and consensus on measurement (CM). To this end, before proposing the hybrid consensus filtering algorithm, distributed robust filtering based on CI and CM have been presented. Next, they show that the estimation error in the proposed consensus algorithm is exponentially mean square bounded using a Lyapunov function. Finally, they provide two illustrative examples to show the robust performance and effectiveness of the proposed consensus filtering algorithms.
Starting Page	37
Ending Page	46
Page Count	10
ISSN	20436386
Volume Number	10
e-ISSN	20436394
Issue Number	Issue 1, Feb (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-wss/10/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-wss.2019.0093
Journal	IET Wireless Sensor Systems
Publisher Date	2019-10-02
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Consensus Algorithm Consensus Filtering Algorithm Consensus Methodology Consensus on Information Consensus Scheme Consensus-based Robust Filtering Approach Distributed Robust Filtering Distributed State Estimation Estimation Theory Exponentially Mean Square Bounded Filtering Theory Hybrid Consensus Filtering Algorithm Hybrid Consensus Strategy Hybrid Method Kalman Filter Lyapunov Function Lyapunov Method Robust Control Robust Kalman Filtering Framework Robust Performance Sensor Network Signal Processing Theory Stability in Control Theory State Estimation Statistics Stochastic Linearised SCUC Time Varying System Time-varying Uncertain System Uncertain System
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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