Robust Consensus Nonlinear Information Filter for Distributed Sensor Networks With Measurement Outliers

Dong, Peng; Jing, Zhongliang; Leung, Henry; Shen, Kai; Li, Minzhe

doi:10.1109/tcyb.2018.2850368

Cited by 43 publications

(18 citation statements)

References 42 publications

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“…Recently, various alternative schemes are developed to overcome the deficiency of above fusion approach in communication and computation. For instance, in the framework of consensus, alternating direction methods of multipliers combined with variational Bayesian algorithms are proposed to carry out the fusion in [51], [52] for systems with non-gaussian noises or gaussian noises with unknown covariance. Additionally, discussing the Cramér-Rao lower bound can realize the efficient sensor selection [53], and adopting the structure of information filter can obtain a compact form of filtering algorithm [52].…”

Section: Filter Structurementioning

confidence: 99%

A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems

Ding

Han

Wang

et al. 2019

IEEE Trans. Ind. Inf.

406

124

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Industrial cyber-physical systems (CPSs) are largescale, geographically dispersed and life-critical systems, in which lots of sensors and actuators are embedded and networked together to facilitate real-time monitoring and closed-loop control. Their intrinsic features in geographic space and resources put forward to urgent requirements of reliability and scalability for designed filtering or control schemes. This paper presents a review of the state-of-the-art of distributed filtering and control of industrial CPSs described by differential dynamics models. Special attention is paid to sensor networks, manipulators and power systems. For real-time monitoring, some typical Kalmanbased distributed algorithms are summarized and their performances on calculation burden, communication burden as well as scalability are discussed in depth. Then, the characteristics of non-Kalman cases are further disclosed in light of constructed filter structures. Furthermore, the latest development is surveyed for distributed cooperative control of mobile manipulators and distributed model predictive control in industrial automation systems. By resorting to droop characteristics, representative distributed control strategies classified by controller structures are systematically summarized for power systems with the requirements of power sharing, and voltage and frequency regulation. In addition, distributed security control of industrial CPSs is reviewed when cyber-attacks are taken into consideration. Finally, some challenges are raised to guide the future research. Index Terms-Industrial cyber-physical systems; distributed filtering; distributed control; power schedule; droop characteristics. I. INDUSTRIAL CYBER-PHYSICAL SYSTEMS A cyber-physical system (CPS), a fast-growing research area, is a highly integrated system of physical components involving sensors, actuators and various equipments, as well as cyber possessing ubiquitous computation and efficient communication. From the engineering point of view, CPSs are considered as the most promising industrial systems including transportation networks, energy systems, water/gas distribution networks, and unmanned factories. For example, multiple industrial robots with an inertial navigation device or various sensors are programmed for the movement along a programmed trajectory to cooperatively complete production tasks [1], [2]. The main advantage of these systems is that the tight

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Section: Filter Structurementioning

confidence: 99%

A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems

Ding

Han

Wang

et al. 2019

IEEE Trans. Ind. Inf.

406

124

View full text Add to dashboard Cite

show abstract

“…A linear distributed consensus filter with CI strategy to handle measurement outliers is proposed in [25], where the measurement noise of each sensor node is modeled by the multivariate Student-t distribution and variational Bayesian (VB) method [26], [27] is used to approximate the joint posterior density. Then it is extended to nonlinear cases in [28] where hybrid consensus strategy [9], [11] is used. However, these methods can only handle the scenarios with heavy-tailed measurement noise and wellbehaved process noise.…”

Section: Measurement Vectormentioning

confidence: 99%

Distributed Consensus Student-t Filter for Sensor Networks With Heavy-Tailed Process and Measurement Noises

Wang¹,

Dong

Shen

et al. 2020

IEEE Access

Self Cite

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In the estimation of distributed sensor networks, process noise and measurement noise may have outliers which have heavy-tailed characteristics. To solve this problem, this paper proposes a distributed consensus estimating method for sensor networks based on Student-t distribution. In the state space model, both process noise and measurement noise are modeled as Student-t distributions with heavytailed characteristics. First, for the assumption that the process noise and measurement noise have the same degree of freedom parameters, an exact distributed consensus Student-t filtering algorithm is derived. In practical applications, this assumption is often not true, and due to the increasing degrees of freedom, the method will quickly converge to the traditional distributed consensus Kalman filter. Therefore, it is necessary to relax the assumption of the same degree of freedom and keep the degree of freedom unchanged within a certain range. Based on this, an approximate distributed consensus Student-t filter algorithm is proposed. Simulation results verify the effectiveness of the proposed algorithm.

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“…This choice will produce satisfactory performance even a small L is provided. 38 In addition, π i , j is also a crucial parameter for the convergence rate of consensus algorithms. A poor choice may lead to consensus on local information with more iterations, which is not always practical in real-time applications.…”

Section: Distributed Srcqif-hcmentioning

confidence: 99%

Distributed hybrid consensus–based square-root cubature quadrature information filter and its application to maneuvering target tracking

Liu

Dong

et al. 2019

International Journal of Distributed Sensor Networks

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To handle nonlinear filtering problems with networked sensors in a distributed manner, a novel distributed hybrid consensus–based square-root cubature quadrature information filter is proposed. The proposed hybrid consensus–based square-root cubature quadrature information filter exploits fifth-order spherical simplex-radial quadrature rule to tackle system nonlinearities and incorporates a novel measurement update strategy into the hybrid consensus filtering framework, which takes the predicted measurement error into account and hence produces more accurate estimates. In addition, the proposed hybrid consensus–based square-root cubature quadrature information filter inherits the complementary positive features of both consensus on information and consensus on measurements methods and avoids sensitive matrix operations such as square-root decompositions and inversion of covariances, which is beneficial for numerical stability. Stability analysis with respect to consensus, convergence, and consistency for the proposed hybrid consensus–based square-root cubature quadrature information filter is also developed. The effectiveness of the proposed hybrid consensus–based square-root cubature quadrature information filter is validated through a maneuvering target tracking scenario. The simulation results show that the proposed hybrid consensus–based square-root cubature quadrature information filter outperforms the existing algorithms at the expense of a slight increase in computational cost.

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Robust Consensus Nonlinear Information Filter for Distributed Sensor Networks With Measurement Outliers

Cited by 43 publications

References 42 publications

A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems

A Survey on Model-Based Distributed Control and Filtering for Industrial Cyber-Physical Systems

Distributed Consensus Student-t Filter for Sensor Networks With Heavy-Tailed Process and Measurement Noises

Distributed hybrid consensus–based square-root cubature quadrature information filter and its application to maneuvering target tracking

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