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Recursive Filtering for Stochastic Systems With Filter-and-Forward Successive Relays

IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1202-1212页

作者： Hailong Tan Bo Shen Qi Li Hongjian Liu School of Mathematics-Physics and Finance Anhui Polytechnic UniversityWuhu 241000China Anhui Future Technology Research Institute Anhui Polytechnic UniversityWuhu 241000China College of Information Science and Technology Donghua UniversityShanghai 201620China Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China School of Information Science and Engineering Hangzhou Normal UniversityHangzhou 311121China

In this paper,the recursive Filtering problem is considered for stochastic systems over filter-and-forward successive relay(FFSR)networks.An FFSR is located between the sensor and the remote filter to forward the measurement.In the successive relay,two cooperative relay nodes are adopted to forward the signals alternatively,thereby existing switching characteristics and inter-relay interferences(IRI).Since the filter-and-forward scheme is employed,the signal received by the relay is retransmitted after it passes through a linear filter.The objective of the paper is to concurrently design optimal recursive filters for FFSR and stochastic systems against switching characteristics and IRI of relays.First,a uniform measurement model is proposed by analyzing the transmission mechanism of FFSR.Then,novel filter structures with switching parameters are constructed for both FFSR and stochastic systems.With the help of the inductive method,Filtering error covariances are presented in the form of coupled difference equations.Next,the desired filter gain matrices are further obtained by minimizing the trace of Filtering error covariances.Moreover,the stability performance of the Filtering algorithm is analyzed where the uniform bound is guaranteed on the Filtering error covariance.Finally,the effectiveness of the proposed Filtering method over FFSR is verified by a three-order resistance-inductance-capacitance circuit system.

关键词： Filtering successive stochastic

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Dynamic Event-Triggered Quadratic Nonfragile Filtering for Non-Gaussian Systems:Tackling Multiplicative Noises and Missing Measurements

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1127-1138页

作者： Shaoying Wang Zidong Wang Hongli Dong Yun Chen Guoping Lu College of Science Shandong University of AeronauticsBinzhou 256603China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590 Department of Computer Science Brunel University LondonUxbridge UB83PHUK Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318China School of Automation Hangzhou Dianzi UniversityHangzhou 310018China School of Electrical Engineering Nantong UniversityNantong 226019China

This paper focuses on the quadratic nonfragile Filtering problem for linear non-Gaussian systems under multiplicative noises,multiple missing measurements as well as the dynamic event-triggered transmission scheme.The multiple missing measurements are characterized through random variables that obey some given probability distributions,and thresholds of the dynamic event-triggered scheme can be adjusted dynamically via an auxiliary variable.Our attention is concentrated on designing a dynamic event-triggered quadratic nonfragile filter in the well-known minimum-variance sense.To this end,the original system is first augmented by stacking its state/measurement vectors together with second-order Kronecker powers,thus the original design issue is reformulated as that of the augmented system.Subsequently,we analyze statistical properties of augmented noises as well as high-order moments of certain random parameters.With the aid of two well-defined matrix difference equations,we not only obtain upper bounds on Filtering error covariances,but also minimize those bounds via carefully designing gain parameters.Finally,an example is presented to explain the effectiveness of this newly established quadratic Filtering algorithm.

关键词： Filtering quadratic bounds

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Experimental distillation of tripartite quantum steering with an optimal local Filtering operation

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Photonics Research 2024年第3期12卷 552-562页

作者： QIAN-XI ZHANG XIAO-XU FANG HE LU School of Physics State Key Laboratory of Crystal MaterialsShandong UniversityJinan 250100China Shenzhen Research Institute of Shandong University Shenzhen 518057China

Multipartite Einstein-Podolsky-Rosen(EPR)steering admits multipartite entanglement in the presence of uncharacterized verifiers,enabling practical applications in semi-device-independent protocols.Such applications generally require stronger steerability,while the unavoidable noise weakens steerability and consequently degrades the performance of quantum information processing.Here,we propose the local Filtering operation that can maximally distill genuine tripartite EPR steering from N copies of three-qubit generalized Greenberger-Horne-Zeilinger states,in the context of two semi-device-independent scenarios.The optimal Filtering operation is determined by the maximization of assemblage fidelity.Analytical and numerical results indicate the advantage of the proposed Filtering operation when N is finite and the steerability of initial assemblages is weak.Experimentally,a proof-of-principle demonstration of two-copy distillation is realized with the optical system.The advantage of the optimal local Filtering operation is confirmed by the distilled assemblage in terms of higher assemblage fidelity with perfectly genuine tripartite steerable assemblages,as well as the greater violation of the inequality to witness genuine tripartite steerable assemblages.Our results benefit the distillation of multipartite EPR steering in practice,where the number of copies of initial assemblages is generally finite.

关键词： Filtering distillation optimal

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Bayesian Filtering for High-Dimensional State-Space Models With State Partition and Error Compensation

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1239-1249页

作者： Ke Li Shunyi Zhao Biao Huang Fei Liu Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Institute of AutomationJiangnan UniversityWuxi 214122China Department of Chemical and Materials Engineering University of AlbertaEdmonton AB T6G 2G6Canada

In the era of exponential growth of data availability,the architecture of systems has a trend toward high dimensionality,and directly exploiting holistic information for state inference is not always computationally affordable.This paper proposes a novel Bayesian Filtering algorithm that considers algorithmic computational cost and estimation accuracy for high-dimensional linear systems.The high-dimensional state vector is divided into several blocks to save computation resources by avoiding the calculation of error covariance with immense dimensions.After that,two sequential states are estimated simultaneously by introducing an auxiliary variable in the new probability space,mitigating the performance degradation caused by state segmentation.Moreover,the computational cost and error covariance of the proposed algorithm are analyzed analytically to show its distinct features compared with several existing methods.Simulation results illustrate that the proposed Bayesian Filtering can maintain a higher estimation accuracy with reasonable computational cost when applied to high-dimensional linear systems.

关键词： Filtering estimation error

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Secure control and Filtering for industrial metaverse

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Frontiers of Information Technology & Electronic Engineering 2024年第2期25卷 179-181页

作者： Qing-Long HAN Derui DING Xiaohua GE School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia Department of Control Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China

Metaverse can be regarded as a socialized and virtualized cyberspace parallel yet interactive to the real world.Benefiting from the rapid development of cloud computing and digital twins,metaverse is transforming traditional control and Filtering para‐digms of industrial automation systems into cyberphysical social systems.Under this scenario,future industrial automation systems could be an integration of real-world ones and virtual twins combined with great computational power within a certain temporal and spatial range.

关键词： interactive Filtering Secure

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Encoding-Decoding-Based Recursive Filtering for Fractional-Order Systems

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 1103-1106页

作者： Bo Jiang Hongli Dong Yuxuan Shen Shujuan Mu Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318 Sanya Offshore Oil&Gas Research Institue Sanya 572025China IEEE

Dear editor,This letter focuses on the encoding-decoding-based recursive Filtering problem for a class of fractional-order systems.For the purpose of protecting security of the wireless communication network,a dynamic-quantization-based encoding-decoding mechanism is introduced to encrypt the transmitted measurement.Specifically,the measurement outputs are first encoded by the encoder into codewords which are then transmitted over the wireless communication network.After received by the decoder,the codewords are decoded and then sent to the filter.In light of the mathematical properties of truncated Gaussian distribution,the variance of the encoding-decoding-induced error between the decoded measurement and the real measurement is derived.An upper bound on the Filtering error covariance is first obtained based on the variance of the encoding-decoding-induced error.Then,the minimal upper bound is derived by choosing proper filter gain.Finally,the efficiency and superiority of the proposed algorithm are verified through a simulation example.

关键词： decoder Filtering error

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Distributed Dimensionality Reduction Filtering for CPSs Under DoS Attacks

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 1080-1082页

作者： Xiaoyuan Zheng Hao Zhang Xindi Yang Huaicheng Yan School of Artificial Intelligence and Data Science Hebei University of TechnologyTianjin 300401China Department of Control Science and Engineering Tongji UniversityShanghai 200092China Key Laboratory of Smart Manufacturing in Energy Chemcical Process of Ministry of Education East China University of Science and TechnologyShanghai 200237 School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China

Dear Editor,This letter concerns about the distributed dimensionally reduction Filtering for a class of cyber physical systems with denial of service(DoS)attacks.Considering each sensor exchanging measurements with ne... 详细信息

关键词： DoS service Filtering

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Recursive Filtering for Nonlinear Systems With Self-Interferences Over Full-Duplex Relay Networks

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IEEE/CAA Journal of Automatica Sinica 2022年第11期9卷 2037-2040页

作者： Hailong Tan Bo Shen Qi Li Wei Qian the School of Mathematics-Physics and Finance Anhui Polytechnic UniversityWuhu 241000 the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 241000China IEEE the College of Information Science and Technology Donghua UniversityShanghai 201620 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the School of Information Science and Engineering Hangzhou Normal UniversityHangzhou 311121China the School of Electrical Engineering and Automation Henan Polytechnic UniversityJiaozuo 454000China

Dear Editor,In this paper,a recursive Filtering problem(RRP)is addressed for nonlinear systems over full-duplex relay(FDR)networks.A FDR is adopted to forward measurements of the sensor to the filter.Because of concurrently transmitting and receiving,the FDR is interfered by the signals from itself,thereby exhibiting self-interference(SI).

关键词： thereby Nonlinear Filtering

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Self-adaptive label Filtering learning for unsupervised domain adaptation

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Frontiers of Computer Science 2023年第1期17卷 225-227页

作者： Qing TIAN Heyang SUN Shun PENG Tinghuai MA School of Computer and Software Nanjing University of Information Science and TechnologyNanjing 210044China Engineering Research Center of Digital Forensics Ministry of EducationNanjing University of Information Science and TechnologyNanjing 210044China

1 Introduction As an emerging machine learning paradigm,unsupervised domain adaptation(UDA)aims to train an effective model for unlabeled target domain by leveraging knowledge from related but distribution-inconsistent source domain.Most of the existing UDA methods[2]align class-wise distributions resorting to target domain pseudo-labels,for which hard labels may be misguided by misclassifications while soft labels are confusing with trivial noises so that both of them tend to cause frustrating performance.To overcome such drawbacks,as shown in Fig.1,we propose to achieve UDA by performing self-adaptive label Filtering learning(SALFL)from both the statistical and the geometrical perspectives,which filters out the misclassified pseudo-labels to reduce negative transfer.Specifically,the proposed SALFL firstly predicts labels for the target domain instances by graph-based random walking and then filters out those noise labels by self-adaptive learning strategy.

关键词： Filtering resort overcome

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Distributed H∞ Filtering of nonlinear systems with random topology by an event-triggered protocol

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Science China(Information Sciences) 2021年第10期64卷 206-220页

作者： Yun CHEN Mengze ZHU Renquan LU Anke XUE Key Lab for IoT and Information Fusion Technology of Zhejiang Hangzhou Dianzi University School of Automation Guangdong University of Technology

Applying an event-triggered protocol, this paper proposes a distributed Hfilter design for nonlinear perturbed systems under fading measurements with random topology. Nonlinearities in this system obey the one-sided Lipschitz constraint, which embraces the conventional Lipschitz condition as a special case.The sensor network allows random variations of the interconnection strengths between adjacent nodes, and the connection coefficient is determined as the product of a constant and a stochastic variable with a known probabilistic feature. To reduce the unnecessary data transmission and efficiently use the limited bandwidth,the transmissions are orchestrated by an event-triggered regulating strategy. A stochastic bounded real lemma is established for the resulting error dynamics. Based on the presented matrix decomposition, which removes the direct coupling between the statistical information of interconnection strengths and the filter gain, the distributed Hfilter gain can be explicitly expressed and easily solved. The usefulness of the theoretical method is demonstrated in a simulation study.

关键词： sensor network distributed H ∞ Filtering one-sided Lipschitz condition event-triggered protocol random topology

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