Journal ArticleDOI
Linear estimators for networked systems with one-step random delay and multiple packet dropouts based on prediction compensation
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TLDR
Compared with the estimators based on the compensation of using the latest measurement previously received in the existing literatures, the proposed estimators have higher estimation accuracy and smaller computational burden.Abstract:
This study is concerned with the linear estimation problem for networked systems with one-step random delay and multiple packet dropouts. At each moment, the estimator may receive one or two data packets or nothing. The predictor of sensor measurement at the current instant is used as a compensator if the current measurement does not arrive at the estimator. Based on the developed compensation model, the optimal linear estimators including filter, predictor and smoother are proposed by the innovation analysis approach. Compared with the estimators based on the compensation of using the latest measurement previously received in the existing literatures, the proposed estimators have higher estimation accuracy and smaller computational burden. Simulation results show the effectiveness of the proposed algorithms.read more
Citations
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Journal ArticleDOI
Multi-sensor distributed fusion estimation with applications in networked systems
TL;DR: The advances of DFE algorithms for networked systems are reviewed, including data quantization, random transmission delays, packet dropouts, fading measurements and communication disturbances, and some random phenomena induced by networks are discussed.
Journal ArticleDOI
Networked distributed fusion estimation under uncertain outputs with random transmission delays, packet losses and multi-packet processing
TL;DR: This paper investigates the distributed fusion estimation problem for networked systems whose multisensor measured outputs involve uncertainties modelled by random parameter matrices and finds that local least-squares linear estimators are obtained at the individual local processors, without requiring the signal evolution model.
Journal ArticleDOI
Fusion estimation for multi-sensor networked systems with packet loss compensation
TL;DR: Based on local estimators and cross-covariance matrices, distributed fusion estimators (DFEs) are presented by using the matrix-weighted fusion estimation algorithm in the LUMV sense and can obviously improve the estimation accuracy.
Journal ArticleDOI
Maximum correntropy delay Kalman filter for SINS/USBL integrated navigation.
TL;DR: In this paper, a filtering algorithm for strapdown inertial navigation system/ultra-short baseline (SINS/USBL) integrated navigation to deal with time-varying delay in underwater acoustic communication and cope with non-Gaussian noise induced by outliers and measurement noises is proposed.
Journal ArticleDOI
Partial-neurons-based state estimation for delayed neural networks with state-dependent noises under redundant channels
TL;DR: The main aim of the addressed problem is to design a state estimator to estimate the neurons’ state by use of a small fraction of the sensor measurements to improve the success rate of the data transmission from the sensor to the estimator.
References
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Journal ArticleDOI
Brief paper: Optimal linear estimation for systems with multiple packet dropouts
TL;DR: The optimal linear estimators including filter, predictor and smoother are developed via an innovation analysis approach based on a packet dropout model and computed recursively in terms of a Riccati difference equation of dimension equal to the order of the system state plus that of the measurement output.
Journal ArticleDOI
To Zero or to Hold Control Inputs With Lossy Links
TL;DR: None of the two simplest compensation strategies commonly found in the literature can be claimed superior to the other, even for simple scalar systems, since there are scenarios where one strategy performs better then the other and scenarios where the converse occurs.
Journal ArticleDOI
Robust filtering under randomly varying sensor delay with variance constraints
TL;DR: The filtering problem under consideration can effectively be solved if there are positive definite solutions to a couple of algebraic Riccati-like inequalities or linear matrix inequalities and the set of desired robust filters is characterized in terms of some free parameters.
Journal ArticleDOI
Optimal filtering with random sensor delay, multiple packet dropout and uncertain observations
TL;DR: The random sensor delay, multiple packet dropout or uncertainty in observation is transformed to a stochastic parameter in the system representation and a new formulation enables us to design an optimal filter for a system with multiple packets dropout in sensor data.
Journal ArticleDOI
Survey of recent progress in networked control systems
Keyou You,Lihua Xie +1 more
TL;DR: Various network conditions required for different control purposes, such as the minimum rate coding for stabilizability of linear systems in the presence of time-varying channel capacity, and the critical packet loss condition for stability of the Kalman filter are discussed.
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