On Kalman-Consensus Filtering With Random Link Failures Over Sensor Networks

Liu, Qinyuan; Wang, Zidong; He, Xiao; Zhou, Donghua

doi:10.1109/tac.2017.2774601

Cited by 151 publications

(55 citation statements)

References 30 publications

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“…Unlike a single sensor in a traditional system, a sensor node in WSNs can collaborate with other sensors in a given topology based on information measured by itself and output information of adjacent sensors. Therefore, some initiatives have been taken to address the problems of distributed filtering based on WSNs in recent years, see [11][12][13][14][15][16][17][18][19][20]. For example, in [12], the filtering problem of nonlinear stochastic systems affected by sensor saturation in unstable communication channels has been solved.…”

Section: Introductionmentioning

confidence: 99%

Distributed Robust Filtering for Wireless Sensor Networks with Markov Switching Topologies and Deception Attacks

Zhu

Liu

Wen

et al. 2020

Sensors

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This paper is concerned with the distributed full- and reduced-order l 2 - l ∞ state estimation issue for a class of discrete time-invariant systems subjected to both randomly occurring switching topologies and deception attacks over wireless sensor networks. Firstly, a switching topology model is proposed which uses homogeneous Markov chain to reflect the change of filtering networks communication modes. Then, the sector-bound deception attacks among the communication channels are taken into consideration, which could better characterize the filtering network communication security. Additionally, a random variable obeying the Bernoulli distribution is used to describe the phenomenon of the randomly occurring deception attacks. Furthermore, through an adjustable parameter E, we can obtain full- and reduced-order l 2 - l ∞ state estimator over sensor networks, respectively. Sufficient conditions are established for the solvability of the addressed switching topology-dependent distributed filtering design in terms of certain convex optimization problem. The purpose of solving the problem is to design a distributed full- and reduced-order filter such that, in the presence of deception attacks, stochastic external interference and switching topologies, the resulting filtering dynamic system is exponentially mean-square stable with prescribed l 2 - l ∞ performance index. Finally, a simulation example is provided to show the effectiveness and flexibility of the designed approach.

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Section: Introductionmentioning

confidence: 99%

Distributed Robust Filtering for Wireless Sensor Networks with Markov Switching Topologies and Deception Attacks

Zhu

Liu

Wen

et al. 2020

Sensors

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“…However, the gain perturbation of the filter is inevitable in practice, such as the error in analog-to-digital conversion and the finite word length of computer, At the same time, the parameter estimation is based on the assumption that the signal of the sensors is accurate. However, in practical applications, the sensors may fail due to electromagnetic interference or poor working environment, which will result in inaccurate filtering results or even an accident [20][21][22]. A robust H∞ filter is designed for a class of Markovian jump neural networks with random sensor failure in [23], but in the literature, the gain of sensor failure is only   0,1 , which does not match the actual situation.…”

Section: Introductionmentioning

confidence: 99%

Non-Fragile Robust H∞ Filtering of Takagi-Sugeno Fuzzy Networked Control Systems with Sensor Failures

Wang

Xie

Zhou

et al. 2019

Sensors

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The fault-tolerant robust non-fragile H∞ filtering problem for networked control systems with sensor failures is studied in this paper. The Takagi-Sugeno fuzzy model which can appropriate any nonlinear systems is employed. Based on the model, a filter which can maintain stability and H∞ performance level under the influence of gain perturbation of the filter and sensor failures is designed. Moreover, the gain matrix of sensor failures is converted into a dynamic interval to expand the range of allowed failures. And the sufficient condition for the existence of the desired filter is derived in terms of linear matrix inequalities (LMIs) solutions. Finally a simulation example is given to illustrate the effectiveness of the proposed method.

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“…For example, data collision might happen if a big amount of information is transmitted via a shared communication network. 14,[31][32][33][34][35][36] To overcome such an obstacle, some communication protocols, which include, but are not limited to, the Round-Robin (RR) protocol, 31,32,[37][38][39] the Try-Once-Discard (TOD) protocol, 15,39 and the stochastic communication protocol (SCP), 35,36,40,41 have been fortunately developed in recent years. Since the RR protocol is a well-known static protocol, which deals well with the network congestion problem without extra scheduling cost, it is naturally adopted in this paper to improve the efficiency of the data transmission.…”

Section: Introductionmentioning

confidence: 99%

Robust model predictive control for polytopic uncertain systems with state saturation nonlinearities under Round‐Robin protocol

Wang

Song

Wei

et al. 2019

Intl J Robust & Nonlinear

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Summary This paper is concerned with the robust model predictive control (RMPC) problem for polytopic uncertain systems with state saturation nonlinearities under the Round‐Robin (RR) protocol. With respect to the practical application, one of the most commonly encountered obstacles that stem from the physical limitation of system components, ie, state saturation, is adequately taken into consideration. In order to reduce the network transmission burden and improve the utilization of the network from the controller nodes to the actuator node, a so‐called RR protocol is employed to orchestrate the data transmission order. At each transmission instant, only one controller node that obtains the priority is accessible to the shared communication network. Our aim of the underlying problem is to design a set of controllers in the framework of RMPC such that the closed‐loop system is asymptotically stable. By taking the influence of the RR protocol and the state saturation precisely into account, some sufficient criteria are established in terms of the token‐dependent Lyapunov‐like approach. Then, an online optimization problem subjected to some matrix inequality constraints is provided, and the desired controllers can be obtained by solving the certain upper bound of the objective addressed. Finally, a distillation process example is provided to illustrate the effectiveness of the proposed RMPC approach.

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On Kalman-Consensus Filtering With Random Link Failures Over Sensor Networks

Cited by 151 publications

References 30 publications

Distributed Robust Filtering for Wireless Sensor Networks with Markov Switching Topologies and Deception Attacks

Distributed Robust Filtering for Wireless Sensor Networks with Markov Switching Topologies and Deception Attacks

Non-Fragile Robust H∞ Filtering of Takagi-Sugeno Fuzzy Networked Control Systems with Sensor Failures

Robust model predictive control for polytopic uncertain systems with state saturation nonlinearities under Round‐Robin protocol

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