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distributed filtering based on Cauchy-kernel-based maximum correntropy subject to randomly occurring cyber-attacks

AUTOMATICA 2022年 135卷 110004-110004页

作者： Song, Haifang Ding, Derui Dong, Hongli Yi, Xiaojian Univ Shanghai Sci & Technol Dept Control Sci & Engn Shanghai 200093 Peoples R China Swinburne Univ Technol Sch Sci Comp & Engn Technol Melbourne Vic 3122 Australia Northeast Petr Univ Heilongjiang Prov Key Lab Networking & Intelligen Daqing 163318 Peoples R China Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China

This paper is concerned with the distributed filtering issue under the Cauchy-kernel-based maximum correntropy for large-scale systems subject to randomly occurring cyber-attacks in non-Gaussian environments. The considered cyber-attacks are hybrid and consist of both denial-of-service attacks and deception attacks. The weighted Cauchy kernel-based maximum correntropy criterion instead of the traditional minimum variance is put forward to evaluate the filtering performance against non-Gaussian noises as well as cyber-attacks. Based on the matrix decomposition and the fixed-point iterative update rules, the desired filter gain related with a set of Riccati-type equations is obtained to achieve the optimal filtering performance. Then, an improved version only dependent on the local information and neighboring one-step prediction is developed to realize the distributed implementation. Furthermore, the convergence of the developed fixed-point iterative algorithm is addressed via the famous Banach fixed-point theorem. Finally, a standard IEEE 39-bus power system is utilized to show the merit of the proposed distributed filtering algorithm in the presence of cyber-attacks and non-Gaussian noises. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： distributed filtering Maximum correntropy Fixed-point iteration Cyber-attacks Non-Gaussian noises

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Multi-Rate Asynchronous distributed filtering Under Randomized Gossip Strategy 22

Multi-Rate Asynchronous Distributed Filtering Under Randomiz...

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22nd International Conference on Information Fusion (FUSION)

作者： Shao, Teng Duan, Zhangsheng Hanebeck, Uwe D. Xi An Jiao Tong Univ Ctr Informat Engn Sci Res Xian 710049 Shaanxi Peoples R China Karlsruhe Inst Technol KIT Inst Anthropomat & Robot Intelligent Sensor Actuator Syst Lab ISAS Karlsruhe Germany

ISBN: (纸本)9780996452786

In this paper, we consider the extension of synchronous distributed filtering under randomizedgossip strategy to multi-rate asynchronous sensor network. To deal with asynchronous measurements due to multi-rate sampling, two processing schemes are proposed, i.e., a batch one and a sequential one. In batch processing, the common fusion period is chosen as the least common multiple of the sampling periods of all sensors. Each measurement of a sensor is propagated to the nearest common fusion time and saved locally. At the common fusion time, multiple propagated measurements of a sensor are compressed to a single measurement and then exchanged with its neighbors. Whereas in sequential processing, the common fusion period is chosen as the greatest common divisor of the sampling periods of all sensors to sequentially process each measurement once it is received. Depending on whether a real measurement is available locally, three exchanging strategies are developed. It is found that unlike in the traditional distributed fusion with a common fusion center, the batch and sequential processing schemes are not equivalent. Pros and cons of these two schemes are analyzed. Numerical experimental results further verify the effectiveness of the proposed schemes.

关键词： Multi-rate sampling asynchronous fusion distributed filtering sensor network batch processing sequential processing randomized gossip

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distributed filtering for A Class of Nonlinear Systems with Limited Communication Capacity

Distributed Filtering for A Class of Nonlinear Systems with ...

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第三十一届中国控制会议

作者： DONG Hongli~1,WANG Zidong~(2,3),LIANG Jinling~4,HE Xiao~2 1.College of Electrical and Information Engineering,Northeast Petroleum University,Daqing 163318,China 2.Department of Automation,Tsinghua University,Beijing 100084,China 3.Department of Information Systems and Computing,Brunei University,Uxbridge,Middlesex,UB8 3PH,United Kingdom 4.Department of Mathematics,Southeast University,Nanjing 210096,China

This paper is concerned with the distributed Hfiltering problem for a class of nonlinear systems with randomly occurring sensor saturations（ROSS） and successive packet dropouts in sensor networks.A sufficient condition is established for the desired distributed filter to ensure that the filtering dynamics is exponentially mean-square stable and the prescribed Hperformance constraint is *** solution of the distributed filter gains is characterized by solving an auxiliary convex optimization ***,a simulation example is provided to show the effectiveness of the proposed filtering scheme.

关键词： distributed filtering Randomly occurring sensor saturations Sensor networks Successive packet dropouts.

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distributed filtering for a Class of Saturated Nonlinear Systems with Measurement Outliers

Distributed Filtering for a Class of Saturated Nonlinear Sys...

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第40届中国控制会议

作者： Jiaxing Li Jun Hu Zhihui Wu Jinpeng Huang Zhipeng Cao Department of Mathematics Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and Technology

This paper addresses a distributed filtering problem for saturated systems over sensor network with measurement outliers, where the multiplicative noises are used to characterize the internal behaviors of system model. A χ detection is first constructed in the distributed filter to detect and remove the outliers existing in the measurement outputs caused by some external environment disturbances or malicious attacks. Moreover, the innovation sequence is applied to design filter as a compensation term. The objective of this paper is to find a locally optimal distributed filter such that, for both the measurement outliers and multiplicative noises, an upper bound of filtering error covariance is given and then a proper filter gain is derived to minimize the obtained upper bound matrix with the help of the matrix analysis theory and the probability knowledge. Finally, a numerical experiment is proposed to verify the validity of the designed distributed filtering algorithm.

关键词： distributed filtering Sensor network Measurement outliers Multiplicative noises State-saturated systems

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distributed filtering Basing Consensus for the Local Strongly Coupled Systems

Distributed Filtering Basing Consensus for the Local Strongl...

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World Congress on Intelligent Control and Automation

作者： Yunze Cai Hua O. Wang Xiaoming Xu Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Mechanical Engineering Boston University Department of Automation Shanghai Jiao Tong University and the University of Shanghai for Science and Technology

ISBN: (纸本)9781467313971

The interactions between subsystems are important for large-scale systems. We introduce a local strongly coupled system which coupled by random communication between subsystems. Due to the intermittent communication, it is difficult to apply the standard Kalman or robust filter to design procedures to such systems. In this paper, we addressed the distributed robust filter design method for this kind of system based on the consensus idea. The main result is a sufficient condition which guarantees a suboptimal level of disagreement of estimates in a coupled network of estimators. The condition is formulated in terms of feasibility of biaffine matrix inequalities (BMIs). The generic algorithm is used to treat the bilinear relation between filter parameters and the interconnection gains. The proposed approach is applied to the problem of formation-based robust synchronization. The numerical simulations show the effectiveness of the proposed filtering method.

关键词： distributed filtering Local Strongly Coupled Systems Consensus Estimation

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Nonlinear distributed filtering subject to censoring measurements under dynamic event-triggered communication mechanism: The state-saturated case

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2022年 114卷

作者： Li, Jiaxing Hu, Jun Liu, Hongjian Yu, Hui Wu, Zhihui Harbin Univ Sci & Technol Dept Math Harbin 150080 Peoples R China Harbin Univ Sci & Technol Sch Automat Harbin 150080 Peoples R China Anhui Polytechn Univ Sch Math & Phys Wuhu 241000 Peoples R China

This paper studies the nonlinear distributed filtering problem for a class of discrete state-saturated systems with censoring measurements and multiplicative noises under the dynamic event-triggered communication mechanism (DETCM). The censoring measurements, which are characterized by the Tobit type I model, unavoidably arise in the measurement signals resulted from the sudden changes of circumstances or the repairs of components. Meanwhile, for the sake of reducing the communication cost and improving the data transmission efficiency, the DETCM is used to determine when the sensor has an opportunity to transmit the information to its adjacent nodes according to the fixed communication topology. The main purpose of the paper is to design a novel distributed filter under the DETCM for the underlying sensor networks, where a particular upper bound of the filtering error covariance is obtained by means of the mathematical induction approach and the matrix theory. Then, the proposed upper bound can be minimized via designing the suitable filter gain. Further, the boundedness of filtering error dynamics is proved based on some pre-set conditions. Finally, illustrative simulation experiments are provided to illustrate the effectiveness of the presented distributed filtering algorithm. (C) 2022 Elsevier B.V. All rights reserved.

关键词： distributed filtering Censoring measurements Dynamic event-triggered communication mechanism State-saturated systems Boundedness analysis

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The design of distributed filtering based on lattice rule

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SIGNAL PROCESSING 2023年第1期213卷

作者： Li, Shihang Zhang, Zhiheng Liu, Peng Cui, Jianfeng North Univ China Taiyuan Peoples R China North Automat Control Technol Inst Taiyuan 030000 Peoples R China

For the problem of multiple micro-target tracking and positioning, the high-dynamic and communication coupling are two cases in actual motion. The dynamic evolution and measurement among them are depicted by a nonlinear system. This paper proposes a new distributed lattice Kalman filter (DLKF) to cope with the two cases simultaneously. The prediction is based on the Cranley-Patterson shift and Korobov lattice rule to generate the low-difference sample points. The update stage is based on the weighted average consistency to fusion its innovation and the information of its neighbor. The stability of this distributed filter is proved by constructing the upper and lower bound of the Lyapunov functional. The finite steps consensus iteration strategies for the update fusion are also investigated. To evaluate the efficiency of the DLKF, it is compared with unscented Kalman filtering and its distributed form. The simulation results show that DLKF uses significantly fewer sampling points than other quasi-Monte Carlo (QMC) filters while maintaining the estimation accuracy. The computational complexity is significantly lower, which is the key factor for application to multiple micro-targets.

关键词： distributed filtering Lattice rule Information fusion

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Consensus-based distributed filtering with fusion step analysis

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AUTOMATICA 2022年 142卷

作者： Qian, Jiachen Duan, Peihu Duan, Zhisheng Chen, Guanrong Shi, Ling Peking Univ Coll Engn Dept Mech & Engn Sci State Key Lab Turbulence & Complex Syst Beijing 100871 Peoples R China Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Kowloon Clear Water Bay Hong Kong Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China

For consensus on measurement-based distributed filtering (CMDF), through infinite consensus fusion operations during each sampling interval, each node in the sensor network can achieve optimal filtering performance with centralized filtering. However, due to the limited communication resources in physical systems, the number of fusion steps cannot be infinite. To deal with this issue, the present paper analyzes the performance of CMDF with finite consensus fusion operations. First, by introducing a modified discrete-time algebraic Riccati equation and several novel techniques, the convergence of the estimation error covariance matrix of each sensor is guaranteed under a collective observability condition. In particular, the steady-state covariance matrix can be simplified as the solution to a discrete-time Lyapunov equation. Moreover, the performance degradation induced by reduced fusion frequency is obtained in closed form, which establishes an analytical relation between the performance of the CMDF with finite fusion steps and that of centralized filtering. Meanwhile, it provides a trade-off between the filtering performance and the communication cost. Furthermore, it is shown that the steady-state estimation error covariance matrix exponentially converges to the centralized optimal steady-state covariance matrix with fusion operations tending to infinity during each sampling interval. Finally, the theoretical results are verified with illustrative numerical experiments. (C) 2022 Elsevier Ltd. All rights reserved.

关键词： distributed filtering Consensus Information fusion Algebraic Riccati equation

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Optimal distributed filtering for nonlinear saturated systems with random access protocol and missing measurements: The uncertain probabilities case

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APPLIED MATHEMATICS AND COMPUTATION 2022年 418卷 126844-126844页

作者： Hu, Jun Li, Jiaxing Kao, Yonggui Chen, Dongyan Harbin Univ Sci & Technol Dept Math Harbin 150080 Peoples R China Harbin Univ Sci & Technol Sch Automat Harbin 150080 Peoples R China Harbin Univ Sci & Technol Heilongjiang Prov Key Lab Optimizat Control & Int Harbin 150080 Peoples R China Harbin Inst Technol Dept Math Weihai 264209 Peoples R China

The saturated-constrained distributed filtering problem is discussed for a class of discrete nonlinear systems with random access protocol (RAP) and missing measurements (MMs) under uncertain missing probabilities (UMPs ). In order to prevent data congestions, the RAP is adopted to regulate the information transmission, where only one sensor is sched-uled to have the communication right and transmit the information at each time step through a shared network. In addition, the phenomenon of MMs is considered, in which the UMPs are characterized by means of the nominal means and error bounds. The main purpose of this paper is to design a distributed filter under saturation constraint such that, for both RAP and MMs under UMPs, there exists an upper bound (UB) matrix of filtering error covariance and the corresponding distributed filter gain is constructed to minimize the trace of the received UB matrix by resorting to the matrix simplifying technique. Be-sides, the filtering algorithm performances are discussed regarding the boundedness and monotonicity of the presented distributed filtering scheme from the mathematical perspec-tive. Finally, some comparisons are provided to illustrate the validity of the proposed time-varying distributed filtering algorithm.(c) 2021 Elsevier Inc. All rights reserved.

关键词： State-saturated stochastic systems distributed filtering Missing measurements Uncertain missing probabilities Random access protocol

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Event-triggered distributed filtering for a class of uncertain parameter systems over dynamic switching topologies networks subject to missing measurements

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DIGITAL SIGNAL PROCESSING 2022年第0期126卷 103474-103474页

作者： Xu, Ping Wu, Huaiyu Zheng, Xiujuan Wuhan Univ Sci & Technol Inst Robot & Intelligent Syst Wuhan 430081 Peoples R China Engn Res Ctr Met Automat & Measurement Te Minist Educ Wuhan 430081 Peoples R China

In this paper, the event-triggered distributed filtering (ETDF) problem is discussed for a class of uncertain parameter systems over dynamic switching topologies networks subject to missing measurements. The event-triggered communication mechanism is introduced to improve energy utilization of sensor network. The randomness phenomena of dynamic switching typologies and missing measurements are characterized by two sets of random variables satisfying Bernoulli distribution. By taking the influence of the parameter uncertainty of the system and the stochastic disturbance of the corresponding estimator gain into account, a novel optimal ETDF is constructed with a linear consistency strategy. Moreover, the estimator gain is obtained by minimizing the upper bound of the estimation error covariance. Finally, an illustrative simulation is provided to illustrate the effectiveness of the proposed algorithm.(C) 2022 Elsevier Inc. All rights reserved.

关键词： distributed filtering Event-triggered communication mechanism Dynamic switching topologies Missing measurements Linear consistency

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