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Multidomain Correlation-Based Multidimensional CSI Tensor Generation for Device-FreeWi-Fi Sensing

Computer Modeling in engineering & Sciences 2024年第2期138卷 1749-1767页

作者： Liufeng Du Shaoru Shang Linghua Zhang Chong Li JianingYang Xiyan Tian School of Mechanical and Electrical Engineering Henan Institute of Science and TechnologyXinxiang453003China School of Communications and Information Engineering Nanjing University of Posts and TelecommunicationsNanjing210003China School of Mechatronic Engineering and Automation Shanghai UniversityShanghai200444China

Due to the fine-grained communication scenarios characterization and stability,Wi-Fi channel state information(CSI)has been increasingly applied to indoor sensing tasks *** spatial variations are explicitlyreflected in CSI measurements,the representation differences caused by small contextual changes are easilysubmerged in the fluctuations of multipath effects,especially in device-free Wi-Fi *** existing datasolutions cannot fully exploit the temporal,spatial,and frequency information carried by CSI,which results ininsufficient sensing resolution for indoor scenario *** a result,the well-liked machine learning(ML)-based CSI sensing models still struggling with stable *** paper formulates a time-frequency matrixon the premise of demonstrating that the CSI has low-rank potential and then proposes a distributed factorizationalgorithm to effectively separate the stable structured information and context fluctuations in the CSI ***,a multidimensional tensor is generated by combining the time-frequency gradients of CSI,which containsrich and fine-grained real-time contextual *** evaluations and case studies highlight thesuperiority of the proposal.

关键词： Wi-Fi sensing device-free CSI low-rank matrix factorization

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Observer-based robust control for a class of sampled-data systems with model uncertainty and external disturbance

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Journal of Control and Decision 2023年第3期10卷 454-463页

作者： Junqi Yang Zechen Li Yantao Chen School of Engineering and Automation Henan Polytechnic UniversityJiaozuoPeople’s Republic of China Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment Henan Polytechnic UniversityJiaozuoPeople’s Republic of China

This paper studies the issue of observer-based feedback stabilisation for a class of linear sampleddatasystems with model uncertainty and external disturbance. First, for a sampled-data systemwith external disturbance, a sampled-data observer is designed to estimate the system ***, a robust H∞ controller based on the observer is developed. For a continuous samplinginterval, the gain matrices of both observer and controller change exponentially. Second,using the state coordinate transformations with an exponential rate, a unified dynamics is constructedby augmenting the state estimation error and the closed-loop system state as a newstate. Next, the sufficient conditions ensuring the asymptotical stability of the closed-loop systemare given by the Lyapunov–Krasovskii method and linear matrix inequality (LMI) ***, the effectiveness of the proposed method is verified by a helicopter model.

关键词： Sampled-data system observer linear matrix inequality robust controller

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Improved WAC Control Strategy for LCL Grid-Connected Inverters Considering Digital Control Delay 18th

Improved WAC Control Strategy for LCL Grid-Connected Inverte...

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18th Annual Conference of China Electrotechnical Society, ACCES 2023

作者： Yao, Guanyu Wang, Xinhuan School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo454003 China Henan International Joint Laboratory of Direct Drive and Control of Intelligent Equipment Jiaozuo454003 China

ISBN: (纸本)9789819714193

The traditional Weighted Average Current (WAC) control method loses its loop-order reduction characteristic due to control delay, resulting in significant instability risk for the system in weak grid conditions. This paper, based on the equivalent impedance model, analyzed that the main cause of system instability is the introduction of a positive feedback loop associated with grid impedance through the voltage feedforward channel, resulting in phase lag. To address this issue, the paper proposes the introduction of a Second-Order Generalized Integrator (SOGI) in the voltage feedforward channel to attenuate the impact of the positive feedback loop on the system, improve the phase margin of the equivalent output impedance in the medium to low frequency range, and enhance the system's adaptability to a wide range of grid impedance variations. Furthermore, in order to eliminate control errors in the indirect control of WAC and enhance the system's background harmonics suppression capability, the quasi-Proportional Resonant (QPR) controller is combined to improve the quality of grid-connected current. Finally, the effectiveness and feasibility of this improved WAC control strategy are verified through simulation in MATLAB/Simulink. © Beijing Paike Culture Commu. Co., Ltd. 2024.

关键词： Electric inverters

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Torque Performance Improving Strategy for DSEM Based on Online Self-Searching Six-State Advanced Angle Commutation

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IEEE Transactions on Power Electronics 2025年第7期40卷 9223-9233页

作者： Zhou, Xingwei Xu, Jingcheng Sun, Yang Niu, Shuangxia Zhou, Bo Zhang, Li Hohai University School of Electrical and Power Engineering Nanjing210098 China The Hong Kong Polytechnic University Department of Electrical Engineering Hong Kong Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing210016 China

Advanced angle commutation (AAC) is an effective and easy-implemented approach to improve the torque performance for doubly salient electromagnetic machine (DSEM), in which six-state advanced angle commutation (SSAAC) is widely used due to the balance in torque improvement and commutation algorithm complexity. This article proposes a torque improving strategy for DSEM based on online self-searching SSAAC. First, the commutation process is researched in detail, and the quantitative expressions of the optimal advanced angles α and β are obtained according to the ideal DSEM model and commutation process. Then, for easier-implemented online searching, the reference current is selected as the feedback, in the advanced angles commutation region, the effects of the dual advanced angles α and β on output torque are analyzed, respectively. Based on this, the dual coupled advanced angles optimization is simplified into two independent single advanced angle optimizations. Afterwards, the golden section strategy is put forward to search the optimal α and β, respectively, online. With no requirement of any system parameters, the output torque performance is desired to be enhanced in terms of torque current ratio as well as torque ripple. The experimental results on a 12/8-pole DSEM prototype validate the correctness and feasibility of the proposed strategies under multiple operating conditions. © 1986-2012 IEEE.

关键词： Torque Torque measurement Commutation Inductance Windings Rotors Optimization Power electronics Complexity theory Training

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Optimal Energy Management for Multistack Fuel Cell Vehicles Based on Hybrid Quantum Reinforcement Learning

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 8500-8511页

作者： Shi, Wenzhuo Sun, Xianzhuo Zhang, Zelong Chen, Junyu Du, Yuhua Ruan, Jiaqi Ding, Yibo Wang, Lei Huangfu, Yigeng Xu, Zhao Northwestern Polytechnical University School of Automation Xi’an710072 China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Research Institute of Smart Energy Hong Kong

This article proposes a driving condition recognition (DCR)-based hybrid quantum deep deterministic policy gradient (HQDDPG) method for energy management in multistack fuel cell vehicle hybrid power systems (MFCV HPSs) and its quantum simulation setup on digital signal processors (DSPs). Driving conditions are initially segmented into microtrips and clustered into three types. The DCR method, using a learning vector quantization neural network (LVQNN), is then developed, thus accurately and efficiently identifying driving condition types. Subsequently, quantum reinforcement learning (RL) is proposed to achieve optimal energy management of MFCV HPSs, i.e., power allocation among the multiple fuel cells to minimize the economic metrics based on the DCR results. Compared to classical large-scale neural networks, quantum RL reduces parameters by combining a parameterized quantum circuit (PQC) with a single-layer classical neural network. The PQC encodes and processes state information through quantum mechanics for enhanced computational expressiveness, while the classical neural network transforms the quantum measurement expectations into actionable outputs for energy management. The trained hybrid quantum circuits are implemented on DSPs through quantum simulations. The method is validated through controller hardware-in-the-loop (CHIL) experiments, demonstrating superior performance in optimizing economic metrics compared to conventional methods. © 2015 IEEE.

关键词： Reinforcement learning

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Event-triggered Adaptive Control of Switched Nonlinear Cyber-physical Systems

Event-triggered Adaptive Control of Switched Nonlinear Cyber...

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2024 China automation Congress, CAC 2024

作者： Yuan, Manman Qian, Wei School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo454003 China Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment Jiaozuo454003 China

ISBN: (纸本)9798350368604

The event-triggered control problem of switched nonlinear cyber-physical systems (CPSs) is investigated under average dwell time (ADT). A new dynamic gain is proposed, which can effectively compensate for the unknown growth rate and measurement sensitivity. Then, a switched observer integrated with a novel dynamic gain is designed and an event-triggered output feedback controller is developed, which can effectively mitigate the communication burden. Finally, it is proved that all the closed-loop signals are bounded and all system states converge to the origin. Accordingly, the effectiveness of the presented scheme is verified through the simulation of switched RLC circuit system. © 2024 IEEE.

关键词： Adaptive control systems

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Photovoltaic Power Prediction Based on K-Means++-BiLSTM-Transformer

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Progress in Electromagnetics Research C 2025年 154卷 191-201页

作者： Liang, Jianwei Yin, Liying Li, Sichao Zhu, Xiubin Liu, Zhangshen Xin, Yanli School of Electrical Engineering and Automation Jiangxi University of Science and Technology Jiangxi Ganzhou341000 China School of Automattion Guangdong Polytechnic Normal University Guangdong Guangzhou510665 China

The inherent volatility and uncertainty associated with photovoltaic (PV) power generation present significant challenges to maintaining grid stability. As the level of PV integration into the grid continues to rise, the importance of accurately predicting its power output becomes increasingly critical. This study presents a new PV power prediction model utilizing K-means++-Bidirectional Long Short-Term Memory (BiLSTM)-Transformer framework. Initially, the Pearson correlation coefficient is computed to determine the key factors influencing the prediction of PV power significantly. Following this, the K-means++ clustering algorithm is applied to analyze historical power data, categorizing it into three distinct groups corresponding to different weather conditions. Finally, the BiLSTM-Transformer architecture is employed to develop a power output prediction model tailored for the three weather scenarios. The prediction model is subsequently optimized using Bayesian methods to determine the optimal model configuration for each specific weather condition. Experimental findings demonstrate that the proposed K-means++-BiLSTM-Transformer similar day PV power prediction model exhibits superior accuracy, enhanced generalization, and increased robustness compared to alternative prediction models. © 2025, Electromagnetics Academy. All rights reserved.

关键词： K-means clustering

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Cooperative Guidance Law with Prescribed-Time Convergence for Maneuvering Target 1

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7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023

作者： Wu, Zihao Yu, Jianglong Wang, Zhikai Li, Qingdong School of Automation Science and Electrical Engineering Beihang University Beijing China School of Information Engineering Henan University of Science and Technology Henan Luoyang China

ISBN: (数字)9789819733408

ISBN: (纸本)9789819733392

To ensure that multiple missiles hit the maneuvering target at different line-of-sight (LOS) angles simultaneously, the impact time errors and LOS angle errors of all missiles need to be eliminated before the missile hits the target. Therefore, a prescribed-time cooperative guidance law is proposed, in which the convergence time of state error can be predefined in advance. Based on the two-direction coordination strategy and prescribed-time stability principle, the impact time is consistent in the LOS direction, and the LOS angle constraint is satisfied in the normal LOS direction. Then, the stability and prescribed-time convergence are analyzed. Finally, the effectiveness of the proposed method is verified by numerical simulation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Numerical methods

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Method of Enhancing Lubrication Performance of the Engine Based on Optimal Dimples of Partial Textures

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Journal of Bio- and Tribo-Corrosion 2023年第2期9卷 1-11页

作者： Wang, Yan Nguyen, Vanliem Wang, Xiangjie Xu, Shaoyong Li, Shiming College of Mechanical and Electrical Engineering Jiaozuo University Jiaozuo China School of Mechanical and Power Engineering Henan Polytechnic University Jiaozuo China School of Mechanical and Electrical Engineering Hubei Polytechnic University Huangshi China School of Mechanical and Electronic Engineering Suzhou University Suzhou China

A design of the partial texture (PT) using the spherical dimple (SD), circular-cylindrical dimple (CCD), conical dimple (CD), square-cylindrical dimple (SCD), and wedge-shaped dimple (WSD) on the crankpin bearing (CB) is proposed to ameliorate the CB’s lubrication. A model of the CB’s dynamic lubrication has been built for analyzing the influence of the geometrical dimensions and distribution densities of the PT on the CB’s lubrication efficiency under the different external loads of the CB at an engine speed of 2000 rpm. The optimal algorithm has been resorted to optimize PT’s parameters to enhance the CB’s lubrication efficiency. The increase of oil film pressure (p) and reduction of frictional force (Ff) of CB are the objectives of the study. Investigation indicates that the PT improves CB’s lubrication better than full textures (FT) designed all over the bearing surface. Also, with the SD using the distribution density of m = 4 and n = 6, the SD has an obvious effect in improving the CB’s lubrication compared to different structures and densities of the PT. Especially, with the geometric dimensions of the SD optimized by the genetic algorithm, the maximum p is increased by 7.98%, while the maximum Ff is reduced by 24.43% compared to the FT. Thus, the CB’s mixed lubrication region should be designed by the optimal SD with m = 4 and n = 6 to further improve the CB’s lubrication efficiency in engines. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Lubrication

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Ti6Al4V laser carburizing grinding surface generation considering carbide distribution

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Journal of Manufacturing Processes 2025年 145卷 454-466页

作者： Hong, Yuan Sun, Cong Zhang, He Li, Haoru Guo, Qiang Ma, Liang Zhao, Jibin School of Mechanical Engineering and Automation Northeastern University Shenyang110819 China National Institute of Intelligent Robotics Shenyang Co. Ltd Shenyang110015 China School of Mechanical and Electrical Engineering Changchun University of Science and Technology Changchun130022 China School of Mechanical and Power Engineering Henan Polytechnic University Jiaozuo454000 China School of Mechanical and Electrical Engineering Xinjiang Institute of Engineering Urumchi820023 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China

Laser carburizing grinding is a performance-accuracy synergistic manufacturing method with promising applications. However, the existing research on the surface generation mechanism of laser carburizing grinding is not comprehensive. The improvement of grinding surface shape accuracy by laser-assisted heat and carburizing alloying has not been fully explored. Therefore, the differences in dynamic thermal-force coupling states, microscopic phase compositions and surface roughness between laser carburizing grinding and traditional separate machining (laser alloying & grinding) are compared by experimental studies. In laser carburizing grinding, the continuous heating results in a continuous high temperature of the remelted layer (192.7 °C), making the grit removal process more stable. The tangential grinding forces are reduced by 15 % compared to traditional separate machining. SEM and XRD examinations revealed the presence of a diffusely distributed granular TiC phase within the remelted layer, which improves the grindability of the machined surface. Further, a grinding surface generation model is developed considering the microscopic TiC phase distribution, material flow and multiple grits trajectories. The granular TiC has a smaller critical undeformed chip thickness. When the content of TiC in the remelted layer exceeds 30 %, the rubbing and plowing of the grits are suppressed, and the surface grooves are reduced. The roughness Ra of the laser carburizing grinding surface is reduced by 15 % and 25 % compared to traditional separate machining and conventional grinding, respectively. This research has improved the surface generation mechanism of laser carburizing grinding and promoted the development of highly efficient and controllable machining-strengthening integration technology. The relevant conclusions are essential for guiding high-performance Ti6Al4V surface property-accuracy synergistic manufacturing. © 2025 The Society of Manufacturing Engineers

关键词： Carburizing

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