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Segment-wise learning control for trajectory tracking of robot manipulators under iteration-dependent periods

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science China(information sciences) 2024年第3期67卷 155-166页

作者： Fan ZHANG Deyuan MENG Kaiquan CAI The Seventh Research division Beihang University School of Automation science and Electrical Engineering Beihang University School of Electronics and information Engineering Beihang University

This paper is concerned with the amplitude boundedness problem of adaptive iterative learning control(AILC) for robot manipulators operating with iteration-dependent periods. By introducing virtual memory slots for storing historical data, a practical AILC method is proposed to achieve the segmentwise learning. This method requires less memory storage for historical information of previous iterations,especially in comparison with that of the conventional AILC methods using point-wise learning *** is shown that not only the energy boundedness but also the amplitude boundedness of estimates and inputs of practical AILC can be guaranteed. Moreover, the practical AILC method can achieve the perfect tracking objective regardless of iteration-dependent periods when the robot manipulators have a persistent full learning property. In addition, a solution to the visual manipulator platform is provided and deployed based on Coppeliasim and Matlab, which helps to show the amplitude boundedness of learning results and the perfect tracking performances of the proposed practical AILC method for robot manipulators.

关键词： amplitude boundedness iteration-dependent period iterative learning control robot manipulator segment-wise virtual memory slot

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Method for triangular fuzzy multiple attribute decision making based on two-dimensional density operator method

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Journal of Systems Engineering and Electronics 2024年第1期35卷 178-185页

作者： LIN Youliang LI Wu LIU Gang HUANG Dong School of Economics and management Hunan Institute of Science and TechnologyYueyang 414000China Hunan Vocational College for Nationalities Yueyang 414000China School of information science and Engineering Hunan Institute of Science and TechnologyYueyang 414000China

Aiming at the triangular fuzzy(TF)multi-attribute decision making(MADM)problem with a preference for the distribution density of attribute(DDA),a decision making method with TF number two-dimensional density(TFTD)operator is proposed based on the density operator theory for the decision maker(DM).Firstly,a simple TF vector clustering method is proposed,which considers the feature of TF number and the geometric distance of ***,the least deviation sum of squares method is used in the program model to obtain the density weight ***,two TFTD operators are defined,and the MADM method based on the TFTD operator is ***,a numerical example is given to illustrate the superiority of this method,which can not only solve the TF MADM problem with a preference for the DDA but also help the DM make an overall comparison.

关键词： fuzzy decision making clustering density operator multi-attribute decision making(MADM)

QBIoT:A Quantum Blockchain Framework for IoT with an Improved Proof-of-Authority Consensus Algorithm and a Public-Key Quantum Signature

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Computers, Materials & Continua 2024年第7期80卷 1727-1751页

作者： Ang Liu Qing Zhang Shengwei Xu Huamin Feng Xiu-bo Chen Wen Liu Network and information management division Beijing Electronic Science and Technology InstituteBeijing100070China Department of Cyberspace Security Beijing Electronic Science and Technology InstituteBeijing100070China information Security Institute Beijing Electronic Science and Technology InstituteBeijing100070China General Office Beijing Electronic Science and Technology InstituteBeijing100070China information Security Center State Key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China

The Internet of Things(IoT)is a network system that connects physical devices through the Internet,allowing them to ***,IoT has become an integral part of our lives,offering convenience and smart ***,the growing number of IoT devices has brought about a corresponding increase in cybersecurity threats,such as device vulnerabilities,data privacy concerns,and network *** blockchain technology with IoT has proven to be a promising approach to enhance IoT ***,the emergence of quantum computing poses a significant challenge to the security of traditional classical cryptography used in blockchain,potentially exposing it to quantum *** support the growth of the IoT industry,mitigate quantum threats,and safeguard IoT data,this study proposes a robust blockchain solution for IoT that incorporates both classical and post-quantum security ***,we present the Quantum-Enhanced Blockchain Architecture for IoT(QBIoT)to ensure secure data sharing and integrity ***,we propose an improved Proof of Authority consensus algorithm called“Proof of Authority with Random Election”(PoARE),implemented within QBIoT for leader selection and new block ***,we develop a publickey quantum signature protocol for transaction verification in the ***,a comprehensive security analysis of QBIoT demonstrates its resilience against cyber threats from both classical and quantum *** summary,this research introduces an innovative quantum-enhanced blockchain solution to address quantum security concernswithin the realmof *** proposedQBIoT framework contributes to the ongoing development of quantum blockchain technology and offers valuable insights for future research on IoT security.

关键词： IoT quantum blockchain public-key quantum signature quantum hash function

Dynamic Analysis of Incentive Policy Impacts on Recycling of Retired Batteries for Electric Vehicles

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Journal of Systems science and information 2024年第4期12卷 491-514页

作者： Cuixia WANG Lang WEI School of information management Jiangxi University of Finance and Economics School of Economics and management Hunan College of Information

Electric Vehicles(EVs), as a low-carbon means of transportation, have promptly become popular worldwide in the past decade. Since the lifespan of batteries is limited, massive of Electric Vehicle Batteries(EVBs) are being retired, resulting in a rapid increase in the demand for the recycling of retired EVBs in recent years. However, due to high recycling costs and immature recycling technologies, EV manufacturers are facing significant challenges in recycling retired EVBs. China, as the country with the largest number of EV users in the world, is exploring effective incentive policies for the recycling of retired EVBs. In this context, we developed a system dynamics model to analyze the impact of incentive polices such as, recycling subsidies, technological progress, and carbon trading on the retired EVBs recycling. Results show that: 1) recycling subsidies can improve the recycling ratios quickly in the short term, and dynamic subsidies are more efficient than static subsidies; 2) the policy of technological advancement can reduce the recovery and cascade utilization cost, thus having a positive impact on battery recycling, but the policy effect has a time-delay; 3) the carbon trading policy is unable to promote efficient recycling due to the current low carbon prices; 4) dynamic subsidy and technological advancement policies complement each other, therefore, the combination of these two policies is the best way to promote the recycling of retired EVBs and reduce carbon emissions. It is hoped that this study will contribute to the ongoing debate on policies for the industrialization of retired EVBs recycling.

关键词： electric vehicles retired battery recycling policy impact system dynamics

An explorative study on document type assignment of review articles in Web of science,Scopus and journals’websites

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Journal of Data and information science 2024年第1期9卷 11-36页

作者： Manman Zhu Xinyue Lu Fuyou Chen Liying Yang Zhesi Shen National science Library Chinese Academy of SciencesBeijing 100190China Department of information Resource management School of Economics and ManagementUniversity of Chinese Academy of SciencesBeijing 100190China Institute of science and Technology information Jiangsu UniversityZhenjiang 212013China

Purpose:Accurately assigning the document type of review articles in citation index databases like Web of science(WoS)and Scopus is *** study aims to investigate the document type assignation of review articles in Web of science,Scopus and Publisher’s websites on a large ***/methodology/approach:27,616 papers from 160 journals from 10 review journal series indexed in SCI are *** document types of these papers labeled on journals’websites,and assigned by WoS and Scopus are retrieved and compared to determine the assigning accuracy and identify the possible reasons for wrongly *** the document type labeled on the website,we further differentiate them into explicit review and implicit review based on whether the website directly indicates it is a review or ***:Overall,WoS and Scopus performed similarly,with an average precision of about 99% and recall of about 80%.However,there were some differences between WoS and Scopus across different journal series and within the same journal *** assigning accuracy of WoS and Scopus for implicit reviews dropped significantly,especially for *** limitations:The document types we used as the gold standard were based on the journal websites’labeling which were not manually validated one by *** only studied the labeling performance for review articles published during 2017-2018 in review *** this conclusion can be extended to review articles published in non-review journals and most current situation is not very *** implications:This study provides a reference for the accuracy of document type assigning of review articles in WoS and Scopus,and the identified pattern for assigning implicit reviews may be helpful to better labeling on websites,WoS and ***/value:This study investigated the assigning accuracy of document type of reviews and identified the some patterns of wrong assignments.

关键词： Document type Web of science Scopus Review article

Magneto-optical Kerr Effect of Mono-layer NiX_(2)(X=Cl,Br,I):A Density Functional Theory Study

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Journal of Wuhan University of Technology(Materials science) 2024年第5期39卷 1121-1128页

作者： FAN Qingqian DU Chaochao School of Economics and management Shanghai Institute of TechnologyShanghai 200235China College of information science&Electronic Engineering Zhejiang UniversityHangzhou 310027China

The full-potential linearized augmented plane wave plus local orbital method is utilized for exploring the electronic,magnetic,and magneto-optical properties of the NiX_(2)(X=Cl,Br,and I)single *** first-principles calculation demonstrates that these compounds are ferromagnetic indirect semiconductors,and the energy band gaps of NiX_(2)for X=Cl,Br,and I are 3.888,3.134,and 2.157 eV,*** magnetic moments of Ni atoms in NiX_(2)monolayer are 1.656,1.588,1.449μB,and their magneto-crystalline anisotropy energies are 0.167,0.029,0.090 meV,*** on the macro-linear response theory,we systematically studied the influences of the external magnetic field and out-of-plane strain on the magneto-optical Kerr effect(MOKE)spectrum of the NiX_(2)single *** is found that,when the external magnetic field is perpendicular to the sample plane,the value of the Kerr rotation angle reaches the maximum,and the single-layer NiI_(2)material has a Kerr rotation angle of 1.89°at the photon energy of 1.986 ***,the Kerr rotation spectrum of NiCl_(2)and NiBr_(2)monolayers redshift as the out-of-plane strain increases,while NiI_(2)monolayer *** computation of the MOKE spectrum of NiX_(2)materials provides an opportunity for applications of 2D magnetic material ranging from sensing to data storing.

关键词： magneto-optical Kerr effect(MOKE) first-principles calculations external magnetic field out-of-plane strain

Secure state estimation for cyber-physical systems with unknown input sliding mode observer

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Control Theory and Technology 2024年第2期22卷 244-253页

作者： Panpan Zhang Yuwei Ren Yixian Fang Ang Liu School of information science and Engineering Shandong Normal UniversityJinan250358ShandongChina School of information Engineering Shandong Management UniversityJinan250357ShandongChina

In recent years, cyber attacks have posed great challenges to the development of cyber-physical systems. It is of great significance to study secure state estimation methods to ensure the safe and stable operation of the system. This paper proposes a secure state estimation for multi-input and multi-output continuous-time linear cyber-physical systems with sparse actuator and sensor attacks. First, for sparse sensor attacks, we propose an adaptive switching mechanism to mitigate the impact of sparse sensor attacks by filtering out their attack modes. Second, an unknown input sliding mode observer is designed to not only observe the system states, sensor attack signals, and measurement noise present in the system but also counteract the effects of sparse actuator attacks through an unknown input matrix. Finally, for the design of an unknown input sliding mode state observer, the feasibility of the observing system is demonstrated by means of Lyapunov functions. Additionally, simulation experiments are conducted to show the effectiveness of this method.

关键词： Sparse attacks Cyber-physical systems Unknown input sliding mode Secure state estimation Adaptive switching mechanism

Neural network equalization based on delta-sigma modulation

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Chinese Optics Letters 2024年第4期22卷 8-13页

作者：刘博任建新吴翔宇陈帅东毛雅亚赵利 Nanjing University of information science&Technology Nanjng 210044China Key Laboratory for information science of Electromagnetic Waves(MoE) Fudan UniversityShanghai 200433China

We propose a neural network equalization delta-sigma modulation(DSM)*** performing DSM on the multiorder quadrature amplitude modulation(QAM)orthogonal frequency division multiplexing(OFDM)signal at the transmitting end,neural network equalizer technology is used in the digital signal processing at receiving *** this technology to a 4.6 km W-band millimeter wave system,it is possible to achieve a 1 Gbaud 8192-QAM OFDM signal *** data rate reached 23.4 Gbit/s with the bit error rate at 3.8×10^(-2),lower than soft-decision forward-error correction threshold(4×10^(-2)).

关键词： multi-order quadrature amplitude modulation W-band delta-sigma modulation neural network equalization nonlinear compensation

A Review of NILM Applications with Machine Learning Approaches

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Computers, Materials & Continua 2024年第5期79卷 2971-2989页

作者： Maheesha Dhashantha Silva Qi Liu School of Electronic and information Engineering Nanjing University of Information Science and TechnologyNanjing210044China

In recent years,Non-Intrusive LoadMonitoring (NILM) has become an emerging approach that provides affordableenergy management solutions using aggregated load obtained from a single smart meter in the power ***, by integrating Machine Learning (ML), NILM can efficiently use electrical energy and offer less ofa burden for the energy monitoring process. However, conducted research works have limitations for real-timeimplementation due to the practical issues. This paper aims to identify the contribution of ML approaches todeveloping a reliable Energy management (EM) solution with NILM. Firstly, phases of the NILM are discussed,along with the research works that have been conducted in the domain. Secondly, the contribution of machinelearning approaches in three aspects is discussed: Supervised learning, unsupervised learning, and *** highlights the limitations in the applicability of ML approaches in the field. Then, the challenges in the realtimeimplementation are concerned with six use cases: Difficulty in recognizing multiple loads at a given time,cost of running the NILM system, lack of universal framework for appliance detection, anomaly detection andnew appliance identification, and complexity of the electricity loads and real-time demand side ***, options for selecting an approach for an efficientNILMframework are suggested. Finally, suggestionsare provided for future research directions.

关键词： Non-intrusive load monitoring transfer learning machine learning feature extraction