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Average controllability of Cartesian Product Networks

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2025年

作者： Zhang, Qiang Huang, Junjie Liu, Bo Su, Housheng Chen, Alatancang Inner Mongolia Univ Sch Math Sci Hohhot 010021 Peoples R China Minzu Univ China Sch Informat Engn Key Lab Intelligent Anal & Secur Governance Ethn L Minist Educ Beijing 100081 Peoples R China Huazhong Univ Sci & Technol Educ Minist China Autonomous Intelligent Unmanned Syst Engn Res Ctr Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Image Proc & Intelligent Control Key Lab Educ Mini Wuhan 430074 Peoples R China

This article explores the average controllability of composite networks generated by factor networks via Cartesian product from energy control perspective, which can be characterized by the controllability Gramian-based metrics. The considered factors are directed weighted networks with diagonalizable / non-diagonalizbable Laplacian dynamics. It is shown that the average controllability of a composite network is determined by the spectral properties of its factors without calculating its own high-dimensional matrix, which reveals how the energy-related controllability of a Cartesian product network (CPN) can be derived from its factors' features. This will reduce the computational complexity and provide insights to study the energy control of other graph product networks.

关键词： controllability Eigenvalues and eigenfunctions Laplace equations Measurement Costs Topology Data centers Complex networks Vectors Social networking (online) Average controllability Cartesian product networks multi-agent networks

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Asynchronous-Based Bipartite Triggered control for Insecure Multi-Agent Systems

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2025年

作者： Zhang, Qingcao An, Qing Chen, Yin Su, Housheng Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Image Proc & Intelligent Control Key Lab Educ Minist China Wuhan Peoples R China Hanjiang Natl Lab Wuhan Peoples R China Wuchang Univ Technol Artificial Intelligence Sch Wuhan Peoples R China Univ Strathclyde Dept Elect & Elect Engn Glasgow Scotland

This paper investigates the problem of memory-event-driven bipartite tracking consensus of delayed linear multi-agent systems (MASs) within insecure cooperative and antagonistic interaction networks under scaling attacks. The study aims to address a more challenging and practical scenario of asynchronous communication. An effective approach of asynchronous memory-event-triggered control (METC) is proposed to overcome the security consensus problem of asynchronous scaling attacks on MASs with heterogeneous time-varying input delays, which may result in either communication tampering or communication interruption on the interactive edge between agents. Furthermore, a distributed memory-based delayed controller is designed to ensure exponential bipartite tracking consensus for the closed-loop control system. Additionally, the memory-based control gains under networked attacks are obtained using the Lyapunov functional method and Halanay inequality, and the upper bound for the allowable delay is established in the system stability analysis. Finally, the proposed control strategy and theoretical results are validated by simulation examples.

关键词： asynchronous memory-event-triggered control asynchronous scaling attacks exponential bipartite consensus heterogeneous delays multi-agent systems

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Global Asymptotic Synchronization of Coupled Neural Networks with Reaction Diffusions and Unbounded Time-varying Delays

Global Asymptotic Synchronization of Coupled Neural Networks...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Yun Xing Yin Sheng The Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

This article investigates global asymptotic synchronization of coupled neural networks with reaction diffusions and unbounded time-varying delays (RDUDCNNs). Through designing a centralized adaptive controller and corresponding updating laws of time-varying control gains, under two different upper bound of control gains, an asymptotic convergence lemma under unbounded time-varying delays and the Barbarat lemma are used to derive global asymptotic synchronization of RDUDCNNs, respectively. The effectiveness of the obtained conclusion is verified through a numerical simulation.

关键词： Upper bound Automation Neural networks Numerical simulation Delays Synchronization Convergence

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A Novel Dynamic Peer-to-Peer Carbon Right Sharing Scheme for Microgrid Clusters

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IEEE Transactions on Smart Grid 2025年

作者： Zhou, Wei Lai, Jingang Li, Xi Zeng, Zhigang School of Artificial Intelligence and Automation China Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Education Ministry of China Wuhan430074 China

In this paper, a novel four-level distributed game decision-making framework of dynamic peer-to-peer (P2P) carbon emission right (CER) sharing is proposed for microgrid clusters (MGCs), which consists of four phases: exploration, selection, equilibrium and correction. Firstly, in the exploration stage, the tradable information is published by microgrids (MGs) and an initial set of tradable options is constructed. Secondly, in the selection stage, bilateral transaction coefficients are calculated according to the deficit and surplus of CERs in the P2P carbon market, and then an optimal sharing matching scheme of CERs is designed to reduce invalid transactions. Thirdly, in the equilibrium stage, a P2P carbon right sharing strategy based on the Stackelberg game is proposed to realize the dynamic change in carbon prices and the flexible conversion of master-slave roles in P2P carbon trading, which can promote the popularity of carbon market. Fourthly, in the correction stage, a carbon emission right balancer (CERB) is developed to avoid the imbalance of CERs, and then a billing scheme including incentives and penalties is established to achieve the benefit redistribution after P2P carbon trading. In the end, numerical results illustrate the effectiveness of the proposed multi-layer game decision-making framework for P2P carbon right sharing among MGs. © 2010-2012 IEEE.

关键词： carbon emission right balancer Microgrid cluster peer-to-peer carbon trading Stackelberg game

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Protecting Multiple Types of Privacy Simultaneously in EEG-Based Brain-Computer Interfaces

Protecting Multiple Types of Privacy Simultaneously in EEG-B...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Lubin Meng Xue Jiang Tianwang Jia Dongrui Wu Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is the preferred input signal in non-invasive BCIs, due to its convenience and low cost. EEG-based BCIs have been successfully used in many applications, such as neurological rehabilitation, text input, games, and so on. However, EEG signals inherently carry rich personal information, necessitating privacy protection. This paper demonstrates that multiple types of private information (user identity, gender, and BCI-experience) can be easily inferred from EEG data, imposing a serious privacy threat to BCIs, To address this issue, we design perturbations to convert the original EEG data into privacy-protected EEG data, which conceal the private information while maintaining the primary BCI task performance. Experimental results demonstrated that the privacy-protected EEG data can significantly reduce the classification accuracy of user identity, gender and BCI-experience, but almost do not affect at all the classification accuracy of the primary BCI task, enabling user privacy protection in EEG-based BCIs.

关键词： Training Privacy Data privacy Accuracy Perturbation methods Machine learning Electroencephalography Brain-computer interfaces Protection Spectrogram

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Bearing-Only Motional Target-Surrounding control for Multiple Unmanned Surface Vessels

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2022年第4期69卷 3988-3997页

作者： Hu, Bin-Bin Zhang, Hai-Tao Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

This article proposes a distributed bearing-only controller for multiple unmanned surface vessels (USVs) to encircle and rotate evenly around a motional target with inter-USV topologies. The distributed control law consists of three terms, i.e., a bearing-only estimation term to approximate the target state, an upper-level surrounding term to fulfill the target-surrounding mission, and a single-vessel regulation term to track the upper-level signal. Significantly, technical conditions are derived to guarantee the asymptotical stability of the closed-loop system. Finally, experimental results on a real platform composed of three HUSTER-0.3 USVs and a target vessel are conducted to substantiate the effectiveness of the proposed controller.

关键词： Topology Vehicle dynamics Sensors Sensor arrays Protocols Velocity measurement Upper bound Bearing-only measurement collaborative control target surrounding unmanned surface vessel (USV)

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Adaptive Synchronization of Reaction-Diffusion Neural Networks With Nondifferentiable Delay via State Coupling and Spatial Coupling

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023年第10期34卷 7555-7566页

作者： Zhang, Hao Zeng, Zhigang Huazhong Agr Univ Coll Informat Wuhan 430070 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

In this article, master-slave synchronization of reaction-diffusion neural networks (RDNNs) with nondifferentiable delay is investigated via the adaptive control method. First, centralized and decentralized adaptive controllers with state coupling are designed, respectively, and a new analytical method by discussing the size of adaptive gain is proposed to prove the convergence of the adaptively controlled error system with general delay. Then, spatial coupling with adaptive gains depending on the diffusion information of the state is first proposed to achieve the master-slave synchronization of delayed RDNNs, while this coupling structure was regarded as a negative effect in most of the existing works. Finally, numerical examples are given to show the effectiveness of the proposed adaptive controllers. In comparison with the existing adaptive controllers, the proposed adaptive controllers in this article are still effective even if the network parameters are unknown and the delay is nonsmooth, and thus have a wider range of applications.

关键词： Synchronization Biological neural networks Couplings Delays Adaptive control Convergence Stochastic processes Adaptive synchronization nondifferentiable delay reaction-diffusion neural network (RDNN) spatial coupling

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RBP-Former: Joint Prediction of RNA-protein Binding Sites on Full-length RNA Transcripts for Multiple RBPs

RBP-Former: Joint Prediction of RNA-protein Binding Sites on...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Li, Yichong Liu, Xiaojian Cheng, Fan Pan, Xiaoyong Yang, Yang Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai200240 China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai200240 China

ISBN: (纸本)9798350386226

RNA-binding proteins (RBPs) are essential for gene expression, and the complex RNA-protein interaction mechanisms require analysis of global RNA information. Therefore, accurate prediction of RBP binding sites on full-length RNA transcripts is crucial for understanding these mechanisms and their roles in diseases. While machine learning methods can predict RBP binding to RNA fragments, extending this to full-length transcripts presents challenges due to sequence length and data imbalance. In this paper, we introduce RBP-Former, a binding site joint prediction model designed specifically for full-length RNA transcripts that can be used for multiple RBPs. This model processes information at both coarse and fine-grained levels to fully exploit sequence data and its interactions with multiple RBPs. We develop multi-level imbalance learning strategies, achieving favorable results on imbalanced data. Our method outperforms existing methods in predicting binding sites on full-length RNA transcripts for multiple RBPs, demonstrating its effectiveness in handling imbalanced label and sample distributions. © 2024 IEEE.

关键词： Binding sites

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Correlation-aware constrained many-objective service composition in crowdsourcing design

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ADVANCED ENGINEERING INFORMATICS 2025年 65卷

作者： Li, Gui Xiao, Renbin Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Inst Artificial Intelligence Wuhan 430074 Hubei Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

With the development of social productivity, crowdsourcing design, a new service-oriented innovative design model emerged. The optimal selection of service resources in crowdsourcing design has a great impact on the quality of task implementation and consumer satisfaction. Unlike the previous research, this paper models and solves the problem from the perspective of constrained many-objective optimization. Firstly, a constrained 6objective combination optimization model is constructed according to the characteristics of service resources in crowdsourcing design. Secondly, a variety of correlation categories and correlation forms of services are considered. It is not limited to the correlation between two services but rather correlations between any number of services. In order to improve search efficiency, a multi-objective service pruning (MOSP) method based on efficient non-dominated sorting (ENS) is used to reduce the decision space. The new constraint strategy handles complex constraints, and a correlation-aware local search strategy is proposed to deal with correlations between services. The results of comparison experiments prove the superiority of the proposed method in solving the constrained correlation-aware many-objective service composition problem.

关键词： Many-objective optimization Dynamic learning evolutionary algorithm Crowdsourcing design Service composition Constraint optimization

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Finite-time H∞ output synchronization for DCRDNNs with multiple delayed and adaptive output couplings

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NEURAL NETWORKS 2025年 184卷 107104页

作者： Qiu, Qian Chen, Yin Su, Housheng Henan Univ Sch Artificial Intelligence Zhengzhou 450046 Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Image Proc & Intelligent Control Key Lab Educ Minist China Wuhan 430074 Peoples R China Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XW Scotland

This work concentrates on solving the finite-time H infinity output synchronization (FTHOS) issue of directed coupled reaction-diffusion neural networks (DCRDNNs) with multiple delayed and adaptive output couplings in the presence of external disturbances. Based on the output information, an adaptive law to adjust output coupling weights and a controller are respectively developed to ensure that the DCRDNNs achieve FTHOS. Then, in the special case of no external disturbances, a corollary on the finite-time output synchronization (FTOS) of the DCRDNNs with multiple delayed and adaptive output couplings is provided. In addition, a novel adaptive scheme to update output coupling weights is devised to ensure H infinity output synchronization (HOS) in the DCRDNNs with multiple delayed output couplings. Finally, the relevant simulation graphs are provided to certify the validity of several synchronization criteria.

关键词： FTHOS FTOS HOS DCRDNNs Multiple delayed and adaptive output couplings

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