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Data-driven cooperative output regulation of multi-agent systems under distributed denial of service attacks

Science China(Information Sciences) 2023年第9期66卷 5-20页

作者： Weinan GAO Zhong-Ping JIANG State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Department of Electrical and Computer Engineering Tandon School of Engineering New York University

This paper addresses an optimal, cooperative output regulation problem for multi-agent systems with distributed denial of service attacks and unknown system dynamics. Unlike existing studies, the proposed solution is essentially a learning-based control strategy such that one can obtain a distributed control policy with internal models through online data and analyze the resilience of closed-loop systems, both without the precise knowledge of system dynamics in the state-space model. The efficiency of the proposed methodology is validated using computer simulations.

关键词： cooperative output regulation adaptive dynamic programming learning-based control multi-agent systems cybersecurity

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Microgrids with day-ahead energy forecasting for efficient energy management in smart grids: hybrid CS-RERNN

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Australian Journal of electrical and Electronics engineering 2024年第3期21卷 213-227页

作者： Shirley, C.P. Pattar, Jagannath Kavitha Rani, P. Saini, Sumit Ranga, Jarabala Elangovan, D. Venkatakrishna Reddy, Ch. Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India Department of Mechanical Engineering Madanapalle Institute of Technology & Science Madanapalle India Department of M.Tech Computer Science and Engineering Sri Krishna College of Engineering and Technology Coimbatore India Department of Electrical Engineering School of Engineering & Technology Central University of Haryana Mahendergarh India Detartment of Electrical and Electronics Engineering Ramachandra College of Engineering Eluru India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Electrical and Electronics Engineering Chaitanya Bharathi institute of technology Hyderabad India

By integrating smart grid technology with home energy management systems, households can monitor and optimise their energy consumption. This allows for more efficient use of energy resources, reducing waste and lowering energy bills. In this manuscript, a hybrid approach is proposed for smart grid home energy management with microgrids and day-ahead energy forecasts. The proposed control approach combines the Circle Search (CS) algorithm and Recalling-Enhanced Recurrent Neural Network (RERNN). Commonly it is named as CS-RERNN technique. The novelty of this paper is to optimise energy consumption and production within microgrids, thereby contributing to the overall efficiency of the smart grid system. The proposed method is used to reduce the electricity cost, peak-to-average ratio (PAR), and maximising consumer comfort. Energy management is performed based on the CS algorithm. A smart home connected to the external power grid (PG) is managed by the proposed method. Here, load demand is predicted by using RERNN. By then, the performance of the proposed method is implemented in MATLAB platform. The proposed method shows a high efficiency of 96%, and 22 $ of low electricity bill cost compared with other existing methods such as Particle swarm optimisation (PSO), Cuckoo search algorithm (CSA, and Border collie Optimisation (BCO). ©, Engineers Australia.

关键词： Energy utilization

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Effect of pulsed current cathodic protection on pipeline steel API 5L X65 corrosion mitigation: An investigation and machine learning-assisted modeling

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Corrosion Communications 2023年第4期12卷 29-45页

作者： Hosein Eslamian Mehdi Javidi Mohammad Reza Zamani Mohammad Mahdi Dana Eghbal Mansoori Department of Materials Science and Engineering School of Engineering Shiraz University School of Metallurgy and Materials Engineering College of Engineering University of Tehran Computer Science Eng.and IT Dept. School of Electrical and Computer Engineering Shiraz University

Pulsed current cathodic protection(PCCP) could be more effective than direct current cathodic protection(DCCP)for mitigating corrosion in buried structures in the oil and gas industries if appropriate pulsed parameters are chosen. The purpose of this research is to present the corrosion prevention mechanism of the PCCP technique by taking into account the effects of duty cycle as well as frequency, modeling the relationships between pulse parameters(frequency and duty cycle) and system outputs(corrosion rate, protective current and pipe-to-soil potential) and finally identifying the most effective protection conditions over a wide range of frequency(2–10 kHz) and duty cycle(25%-75%). For this, pipe-to-soil potential, pH, current and power consumption, corrosion rate, surface deposits and investigation of pitting corrosion were taken into account. To model the input-output relationship in the PCCP method, a data-driven machine learning approach was used by training an artificial neural network(ANN). The results revealed that the PCCP system could yield the best protection conditions at 10 kHz frequency and 50% duty cycle, resulting in the longest protection length with the lowest corrosion rate at a consumption current 0.3 time that of the DCCP method. In the frequency range of 6–10 kHz and duty cycles of 50%-75%, SEM images indicated a uniform distribution of calcite deposits and no pits on cathode surface.

关键词： Pulsed current cathodic protection Duty cycle Frequency Artificial neural network API X65 pipeline steel

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Advancements in Remote Sensing Image Dehazing: Introducing URA-Net with Multi-Scale Dense Feature Fusion Clusters and Gated Jump Connection

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computer Modeling in engineering & Sciences 2024年第9期140卷 2397-2424页

作者： Hongchi Liu Xing Deng Haijian Shao School of Computer Jiangsu University of Science and TechnologyZhenjiang212003China Department of Electrical and Computer Engineering University of NevadaLas Vegas89119USA

The degradation of optical remote sensing images due to atmospheric haze poses a significant obstacle,profoundly impeding their effective utilization across various *** methodologies have emerged as pivotal components of image preprocessing,fostering an improvement in the quality of remote sensing *** enhancement renders remote sensing data more indispensable,thereby enhancing the accuracy of target *** defogging techniques based on simplistic atmospheric degradation models have proven inadequate for mitigating non-uniform haze within remotely sensed *** response to this challenge,a novel UNet Residual Attention Network(URA-Net)is *** paradigmatic approach materializes as an end-to-end convolutional neural network distinguished by its utilization of multi-scale dense feature fusion clusters and gated jump *** essence of our methodology lies in local feature fusion within dense residual clusters,enabling the extraction of pertinent features from both preceding and current local data,depending on contextual *** intelligently orchestrated gated structures facilitate the propagation of these features to the decoder,resulting in superior outcomes in haze *** validation through a plethora of experiments substantiates the efficacy of URA-Net,demonstrating its superior performance compared to existing methods when applied to established datasets for remote sensing image *** the RICE-1 dataset,URA-Net achieves a Peak Signal-to-Noise Ratio(PSNR)of 29.07 dB,surpassing the Dark Channel Prior(DCP)by 11.17 dB,the All-in-One Network for Dehazing(AOD)by 7.82 dB,the Optimal Transmission Map and Adaptive Atmospheric Light For Dehazing(OTM-AAL)by 5.37 dB,the Unsupervised Single Image Dehazing(USID)by 8.0 dB,and the Superpixel-based Remote Sensing Image Dehazing(SRD)by 8.5 *** noteworthy,on the SateHaze1k dataset,URA-Net attains preeminence in overall performance,yieldi

关键词： Remote sensing image image dehazing deep learning feature fusion

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An artificial systems,computational experiments and parallel execution-based surface electromyogram-driven anti-disturbance zeroing neurodynamic strategy for upper limb human-robot interaction control

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CAAI Transactions on Intelligence Technology 2024年第2期9卷 511-525页

作者： Yongbai Liu Keping Liu Gang Wang Jiliang Zhang Yao Chou Zhongbo Sun Department of Mechanical Engineering Changchun University of TechnologyChangchunChina Department of Control Engineering Changchun University of TechnologyChangchunChina School of Electrical and Information Engineering Jilin Engineering Normal UniversityChangchunChina College of Information Science and Engineering Northeastern UniversityShenyangChina Department of Electrical and Computer Engineering Brigham Young UniversityProvoUtahUSA

In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be ***,the efficacy and robustness of the HRI control algorithm in the presence of unknown external disturbances deserve to be *** deal with these urgent issues,in this study,artificial systems,computational experiments and a parallel execution intelligent control framework are constructed for the HRI *** upper limb-robotic exoskeleton system is re-modelled as an artificial *** on surface electromyogram-based subject's active motion intention in the practical system,a non-convex function activated anti-disturbance zeroing neurodynamic(NC-ADZND)controller is devised in the artificial system for parallel interaction and HRI control with the practical ***,the linear activation function-based zeroing neurodynamic(LAF-ZND)controller and proportionalderivative(posterior deltoid(PD))controller are presented and *** results substantiate the global convergence and robustness of the proposed controller in the presence of different external *** addition,the simulation results verify that the NC-ADZND controller is better than the LAF-ZND and the PD controllers in respect of convergence order and anti-disturbance characteristics.

关键词： neural network pattern recognition robotics signal processing

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A survey on cross-user federated recommendation

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Science China(Information Sciences) 2025年第4期68卷 7-32页

作者： Enyue YANG Yudi XIONG Wei YUAN Weike PAN Qiang YANG Zhong MING College of Computer Science and Software Engineering Shenzhen University School of Electrical Engineering and Computer Science The University of Queensland WeBank AI Lab WeBank Department of Computer Science and Engineering Hong Kong University of Science and Technology College of Big Data and Internet Shenzhen Technology University Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)

Recommender systems are effective in mitigating information overload, yet the centralized storage of user data raises significant privacy concerns. Cross-user federated recommendation(CUFR) provides a promising distributed paradigm to address these concerns by enabling privacy-preserving recommendations directly on user devices. In this survey, we review and categorize current progress in CUFR, focusing on four key aspects: privacy, security, accuracy, and efficiency. Firstly,we conduct an in-depth privacy analysis, discuss various cases of privacy leakage, and then review recent methods for privacy protection. Secondly, we analyze security concerns and review recent methods for untargeted and targeted *** untargeted attack methods, we categorize them into data poisoning attack methods and parameter poisoning attack methods. For targeted attack methods, we categorize them into user-based methods and item-based methods. Thirdly,we provide an overview of the federated variants of some representative methods, and then review the recent methods for improving accuracy from two categories: data heterogeneity and high-order information. Fourthly, we review recent methods for improving training efficiency from two categories: client sampling and model compression. Finally, we conclude this survey and explore some potential future research topics in CUFR.

关键词： cross-user federated recommendation federated recommendation federated learning recommender systems user privacy

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Competitive Incentive Mechanism for Multi-Agents in Demand Response via a Hierarchical Game Considering Joint Uncertainties

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IEEE Transactions on Smart Grid 2025年第4期16卷 2913-2925页

作者： Jiang, Tingyu Ju, Ping Lin, Zhenjia Wu, Qiuwei Lin, Zhenhong Chung, C.Y. College of Energy and Electrical Engineering Hohai University Nanjing China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Hong Kong China Tsinghua Shenzhen International Graduate School Tsinghua-Berkeley Shenzhen Institute Shenzhen China School of Future Technology South China University of Technology Guangzhou China Department of Electrical Engineering The Hong Kong Polytechnic University Hong Kong China

The emergence of load aggregators (LAs) has significantly elevated the trading position of residential users in demand response (DR). Effective incentive designs can greatly enhance the responsiveness of residential users. However, a key but often overlooked issue in practical implementation is strengthening the connection between pricing and actual responses to ensure the executability of DR scheduling results. To address this issue, this paper presents a competitive incentive mechanism for multi-agents in DR through a hierarchical game that considers joint uncertainties, and examines the rationality and interactive behaviors of different agents to ensure the efficient implementation of scheduling. The agents are the independent system operator (ISO), LAs, and residential users. First, the rationality levels of the various agents are analyzed, and corresponding utility functions are developed to target each agent specifically. Then, the interactive relationships among the various agents are examined, and a bi-level game model that incorporates a "pricing-response" approach is developed to enhance the feasibility of scheduling results, utilizing both Stackelberg and evolutionary game theories. Finally, uncertain factors are introduced, and the correlations between them are analyzed using copula theory, which results in model refinements that improve accuracy and pertinence. Simulations verify the effectiveness and economic efficiency of the proposed competitive incentive mechanism in terms of achieving a win-win situation for all agents. © 2010-2012 IEEE.

关键词： Competition

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Energy-efficient joint UAV secure communication and 3D trajectory optimization assisted by reconfigurable intelligent surfaces in the presence of eavesdroppers

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Defence Technology（防务技术） 2024年第1期31卷 537-543页

作者： Huang Hailong Mohsen Eskandari Andrey V.Savkin Wei Ni The Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina School of Electrical Engineering and Telecommunications University of New South WalesSydney2052Australia Data61 CSIROAustralia

We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple *** friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the *** formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given *** present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the *** effectiveness of the proposed method is validated via computer simulations.

关键词： Unmanned aerial systems(UASs) Unmanned aerial vehicle(UAV) Communication security Eaves-dropping Reconfigurable intelligent surfaces(RIS) Autonomous navigation and placement Path planning Model predictive control

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String Stability of Vehicle Platoon with Packet Loss in NR-V2X

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Chinese Journal of Electronics 2025年第2期34卷 683-697页

作者： Ning Ruirui Lin Siyu Wang Xi Zhang Xiaokang Feng Weiyang Zhang Ning School of Electronic and Information Engineering Beijing Jiaotong University Beijing 100044 China Department of Electrical and Computer Engineering University of Windsor Windsor ON N9B 3P4 Canada

The vehicle platoon refers to the dynamic formation of a group of vehicles to drive with a certain spacing between vehicles, which is an important enhanced application scenario of cellular vehicle-to-everything (C-V2X). Through the C-V2X technology, the real-time interaction of vehicle motion status information and driving strategy of the vehicle platoon can be realized. In addition, benefit from vehicle-to-vehicle (V2V) communication, vehicle platoon can reduce the headway and expand the road capacity. However, in the process of vehicle-to-everything communication, packet loss is inevitable, which affect the stable operation of vehicle platoon and make it a challenge to the design of efficient vehicle platoon strategy. In response to the above challenge, this paper proposes an analytical framework that investigates the influence of the packet loss in new radio vehicle-to-everything (NR-V2X) mode 2 on the string stability of the vehicle platoon. Firstly, the packet loss in NR-V2X mode 2 is analyzed, and an analytical model is presented to depict the relationship between the packet delivery probability and the intra-platoon spacing with the aid of stochastic geometry. Then, the influence of packet loss in NR-V2X mode 2 on the string stability of the vehicle platoon is depicted, and the time headway boundary value under the condition of ensuring the string stability is deduced when the number of connected predecessors varies. Theoretical analysis and simulation verification of the proposed model are carried out. Design insights are given for efficient platoon strategy by increasing the number of connected predecessors and improving packet delivery probability to achieve short time headway and thus high road capacity.

关键词： New radio vehicle-to-everything (NR-V2X) Platoon String stability Stochastic geometry

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A Soft-Switching Type-3 Fuzzy Control for electrically Driven Nonholonomic Robots

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IEEE Access 2025年 13卷 99234-99251页

作者： Yuan, Xinhong Fekih, Afef Taghizadeh, Abouzar Zhang, Chunwei Mohammadzadeh, Ardashir Zhejiang Polytechnic University of Mechanical and Electrical Engineering School of Automation Hangzhou China University of Louisiana at Lafayette Department of Electrical and Computer Engineering Lafayette LA United States Shenyang University of Technology Multidisciplinary Center for Infrastructure Engineering Shenyang China Sakarya University Faculty of Engineering Department of Electrical and Electronics Engineering Sakarya Turkey

The wheeled mobile robots (WMRs) are used in extensive fields because of their simple structure and high efficiency. Due to the different applications of WMRs in different problems, the control problem of WMRs is challenging. Various frictions and disturbances complicate the dynamics of MRs. To cope with these problems, various control systems have been developed. But, in most of the existing methods, just the structural uncertainties are considered, and non-structural uncertainties such as disturbance and un-modeled dynamics are neglected. Although in some studies, the sliding mode controller (SMC) and its combination with different methods have been presented, however, in most of these controllers, to ensure stability, some coefficients are conservatively set with large values, and as a result, large control signals are generated. These signals are often not within the acceptable range, and their practical implementation is difficult. In this paper, an adaptive controller is designed that is robust under structural/un-structural uncertainties and unknown dynamics. In the designed controller, the coefficients and bounds of uncertainties are adjusted using an adaptive type-3 (T3) fuzzy system (FS). Based on back-stepping kinematic control, new adaptation laws, sufficient conditions for stability, and control signals are derived. Adaptive T3-FS is designed to create a soft-switching mechanism. New learning rules of T3-FS are derived to adjust the upper/lower bounds of structural and un-structural/uncertainties. The stability is mathematically analyzed and proved under uncertainties. Several simulations are given to prove the effectiveness. © 2013 IEEE.

关键词： adaptive control kinematic control Mobile robot sliding mode control type-3 fuzzy

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