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第43届中国控制会议

作者： Shengbin Wu Jing Na Yingbo Huang Faxiang Zhang Xinkai Chen Faculty of Mechanical and Electrical Engineering Kunming University of Science and Technology Yunnan Key Laboratory of Intelligent Control and Application Department of Electronic and Information Systems Shibaura Institute of Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

An adaptive parameter estimation method that ensures fixed-time convergence is proposed for micro-nano positioning system driven by magnetostrictive actuator(i.e., magnetostrictive actuated positioning system). Firstly, the hysteresis nonlinearity of the magnetostrictive actuated positioning system is characterized using the generalized Prandtl–Ishlinskii(GPI) ***, the low-pass filter is introduced to design the adaptive estimation law driven by the estimation error, by which the unmeasured intermediate hysteresis variable can be avoided, and the estimation error converges to zero within a fixed time. Specifically,a modified error variable is designed to deal with the influence of the regression vector, thereby improving convergence performance and simplifying parameter adjustment. Finally, the effectiveness of the presented method is verified by simulation and experimental outcomes.

关键词： Adaptive parameter estimation Fixed-time convergence Magnetostrictive actuator Micro/nano positioning system

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A Planar, Wideband and Compact Hadamard Matrix for 2-D Switched Beam Antenna Array

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IEEE Antennas and Wireless Propagation Letters 2025年

作者： Pan, Yufei Xu, Zizhen Yang, Ye Dai, Xin Yang, Wanjun Zheng, Shaoyong School of Electronics and Communication Engineering Guangzhou University Guangzhou China City University of Hong Kong Department of Electrical Engineering Hong Kong Sun Yat-sen University Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems School of Electronics and Information Technology Guangzhou510006 China

This letter proposes a wideband two-dimensional (2-D) switched beam antenna array with single/dual/quad-lobed switched beams for direction of arrival (DOA) estimation. A planar and compact 4-order Hadamard matrix (HM) without any intersection structure works as its feeding network. The HM provides four groups of output signals with equal amplitudes and coded 0° /180° phase differences between adjacent outputs. It adopts four universal building blocks arranged planarly, each of them is realized by a 3-dB wideband quadrature coupler cascading with a 90 8 phase shifter. For demonstration, a HM prototype operating at 2.4 GHz is designed, fabricated, and measured. Its overall circuit size is 0.67 × 1.34 λg 2 and bandwidth is larger than 47.6%. Finally, a wideband 2-D switched beam antenna array is constructed by the proposed HM and magnetoelectric dipole antenna array. The 2-D single/dual/quadlobed switched beams verify its effectiveness. © 2002-2011 IEEE.

关键词： Hadamard matrices

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Performance-Aware control of Modular Batteries For Fast Frequency Response

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IEEE Transactions on Sustainable Energy 2025年

作者： He, Yutong Ruan, Guangchun Zhong, Haiwang Tsinghua University State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Beijing100084 China Massachusetts Institute of Technology Lab for Information and Decision Systems CambridgeMA02139 United States

Modular batteries can be aggregated to deliver frequency regulation services for power grids. Although utilizing the idle capacity of battery modules is financially attractive, it remains challenging to consider the heterogeneous module-level characteristics such as dynamic operational efficiencies and battery degradation. In addition, real-time decision making within seconds is required to enable fast frequency response. In order to address these issues, this paper proposes a performance-aware scheduling approach for battery modules to deliver fast frequency response (FFR) support. In particular, the conduction loss and switching loss of battery packs as well as converters are captured within a mix-integer quadratic constrained program (MIQCP). The cycle-based aging model identifies the aging cost of battery modules during frequent cycling by introducing the aging subgradient calculation and linearization. Case studies based on real-world battery data show that the proposed scheduling approach can effectively reduce power loss cost by nearly 28%-57% and battery aging cost by 4%-15% compared to conventional methods, which can also enhance the SoC balance. © 2010-2012 IEEE.

关键词： Battery management systems

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Self-powered temperature-changing system driven by wind energy

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Microsystems & Nanoengineering 2024年第5期10卷 171-180页

作者： Jiayu Li Boxun Liu Mingyang Li Yahui Li Wangyang Ding Guanlin Liu Jun Luo Nan Chen Lingyu Wan Wenjuan Wei Center on Nanoenergy Research Institute of Science and Technology for Carbon Peak&NeutralityGuangxi UniversityNanning 530004China State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures School of Physical Science&TechnologyGuangxi UniversityNanning 530004China Department of Chemistry and the Tsinghua Center for Frontier Polymer Research Tsinghua UniversityBeijing 100084PR China State Key Laboratory of Pollution Control and Resource Reuse School of the EnvironmentNanjing UniversityNanjing 210023China Department of Micro/Nano Electronics School of Electronic Information and Electrical EngineeringShanghai Jjao Tong UniversityShanghai 200240PR China State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures MOE Key Laboratory of New Processing Technology for Nonferrous Metals and Materialsand School of ResourcesEnvironment and MaterialsGuangxi UniversityNanning 530004China

Research on outdoor,mobile,and self-powered temperature-control devices has always been highly *** devices can reduce energy consumption for cooling and heating,and they have broad market *** this basis,a rotary disc-shaped triboelectric nanogenerator(TENG)with a maximum open-circuit voltage of 6913 V,a maximum short-circuit current of 85μA,and a maximum transferred charge of 1.3μC was *** synthesized a ferroelectric ceramic composed of 0.15PbTiO_(3)-0.85PbSc_(o.5)Ta_(o.5)O_(3)(0.15PT-0.85PST),which exhibited excellent electrothermal effects at room *** quenching,the electrothermal effect(A Tmax)and energy harvesting properties of the device were 1.574 K and 0.542 J/cm3,***,for the frst time,we proposed a self-powered temperature quantification control system with a rotary disc-shaped *** device effectively harnessed wind and water energy,in addition to other types of *** system consisted of energy collecting cups,a rotating disc-shaped FEP-rabbit fur TENG,a circuit management module,and a ferroelectric ceramic chip *** the circuit management module,the system converted external wind energy into a high-voltage electric field at the two ends of the 0.15PT-0.85PST ceramic chip to fully stimulate the electrothermal *** a speed of 200 rpm,the temperature change in the insulated cup within 276 s was 0.49 K,and the volume of the insulated cup was 300 times greater than that of the 0.15PT-0.85PST ceramic *** with the results reported in previous work,the cooling and heating times were both reduced by 31%,and the temperature changes for both cooling and heating increased by 81%.Moreover,the heating and cooling temperatures of the device optimized on this basis were increased to 1.19K and 0.93 K,*** great improvement in the temperature variation performance confrmed the great potential of the device for *** research could serve as a reference for reduci

关键词： ceramic shaped ferroelectric

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Deep Learning control for Autonomous Robot

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Computers, Materials & Continua 2022年第8期72卷 2811-2824页

作者： Rihem Farkh Saad Alhuwaimel Sultan Alzahrani Khaled Al Jaloud Mohammad Tabrez Quasim College of Engineering Muzahimiyah BranchKing Saud UniversityRiyadh11451Saudi Arabia Laboratory for Analysis Conception and Control of SystemsLR-11-ES20Department of Electrical Engineering National Engineering School of TunisTunis El Manar University1002Tunisia King Abdulaziz City for Science and Technology Saudi Arabia College of Computing and Information Technology University of BishaBisha67714Saudi Arabia

Several applications of machine learning and artificial intelligence,have acquired importance and come to the fore as a result of recent advances and improvements in these *** cars are one such *** is expected to have a significant and revolutionary influence on *** with smart cities,new infrastructure and urban planning with sophisticated cyber-security are some of the current ramifications of self-driving *** autonomous automobile,often known as selfdriving systems or driverless vehicles,is a vehicle that can perceive its surroundings and navigate predetermined routes without human *** are on the verge of evolving into autonomous robots,thanks to significant breakthroughs in artificial intelligence and related technologies,and this will have a wide range of socio-economic ***,in order for these automobiles to become a reality,they must be endowed with the perception and cognition necessary to deal with high-pressure real-life events and make proper judgments and take appropriate *** majority of self-driving car technologies are based on computer systems that automate vehicle control *** forward-collision warning and antilock brakes to lane-keeping and adaptive drive control,to fully automated driving,these technological components have a wide range of capabilities.A self-driving car combines a wide range of sensors,actuators,and *** researches on computer vision and deep learning are used to control autonomous driving *** self-driving automobiles,lane-keeping is *** study presents a deep learning approach to obtain the proper steering angle to maintain the robot in the *** propose an advanced control for a selfdriving robot by using two controllers *** neural networks(CNNs)are employed,to predict the car’and a proportionalintegral-derivative(PID)controller is designed for speed and steering *** stu

关键词： Autonomous car cascade PID control deep learning convolutional neural network differential drive system raspberry PI road lane detector

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Actively tunable dual-broadband graphene-based terahertz metamaterial absorber

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Chinese Physics B 2021年第12期30卷 495-502页

作者： Dan Hu Tian-Hua Meng Hong-Yan Wang Mai-Xia Fu School of Physics and Electrical Engineering Anyang Normal UniversityAnyang 455000China Department of Physics and Electronics Science Shanxi Datong UniversityDatong 037009China School of Education Information Technology and Communication Anyang Normal UniversityAnyang 455000China College of Information Science and Engineering Henan University of TechnologyKey Laboratory of Grain Information Processing and ControlMinistry of EducationZhengzhou 450001China

A tunable metamaterial absorber(MA)with dual-broadband and high absorption properties at terahertz(THz)frequencies is designed in this *** MA consists of a periodic array of flower-like monolayer graphene patterns at top,a SiO_(2)dielectric spacer in middle,and a gold ground plane at the *** simulation results demonstrate that the designed MA has two wide absorption bands with an absorption of over 90%in frequency ranges of 0.68 THz-1.63 THz and 3.34 THz-4.08 THz,and the corresponding relative bandwidths reach 82.3%and 20%,*** peak absorptivity of the absorber can be dynamically controlled from less than 10%to nearly 100%by adjusting the graphene chemical potential from 0 eV to 0.9 ***,the designed absorber is polarization-insensitive and has good robustness to incident *** a high-performance MA has broad application prospects in THz imaging,modulating,filtering,etc.

关键词： metamaterial graphene absorber terahertz

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Analyzing Behavior Data of Students in the Classroom with Association Rule Mining

Analyzing Behavior Data of Students in the Classroom with As...

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Chinese Automation Congress (CAC)

作者： Qingbo Zeng Zhezhuang Xu Song Zheng Chi Liu Qinqin Chai Ying Zhang Education Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing College of Electrical Engineering and Automation Fuzhou University Fuzhou China

Students behavior in the classroom has a close relation with the academic performance of students. With the widespread use of mobile phones, the students are easily distracted by mobile phones during the class. Therefore, analyzing the students behavior in the classroom becomes important to improve the quality of teaching. However, the existing methods for analyzing students behavior in the classroom, such as facial recognition, has low efficiency with large amounts of irrelevant data. And it also raises concerns about privacy and ethical issues. To solve this problem, in this paper, a novel mobile software called EasyClass has been developed to collect and quantify students behaviors. Based on the data collected by EasyClass, we propose to utilize user profiling to study students behavior in the classroom. The clustering algorithm is firstly employed to classify the data and generate semantically tags which describe students behavior in the classroom. Then a sequence and association rule analysis method is used to analyze the behavior tags and generated association rules. The results enable educators and non-expert users to gain a deeper understanding of students behavior in the classroom, and further improve the quality of the classroom teaching.

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Short-Term Traffic Flow Prediction of Highway Tunnels Based on SSA and Improved TSK Fuzzy System

Short-Term Traffic Flow Prediction of Highway Tunnels Based ...

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Chinese Automation Congress (CAC)

作者： Zhijing Huang Kang Chen Zhezhuang Xu Qinbo Zeng Zhibin Xu Education Department of Fujian Province Key Laboratory of Industrial Automation Control Technology and Information Processing College of Electrical Engineering and Automation Fuzhou University Fuzhou China

Aiming at the problem that the traffic flow has an low prediction accuracy due to varying randomness and high nonlinearity, an improved TSK fuzzy neural network prediction model by singular spectrum analysis is ***, the original traffic flow time series can be decomposed into several subseries by singular spectrum analysis (SSA). Then, the Takagi-Sugeno-Kang (TSK) fuzzy system was trained using simulated annealing genetic algorithm (SAGA) and minibatch gradient descent method (MBGD) combined with three techniques (RDA) of regularization, DropRule and *** prediction model of TSK fuzzy neural network is established to predict each subseries independently, and the forecasted traffic flow is obtained by superimposing the prediction results of each subseries. Finally, the traffic flow dataset of expressway tunnels in a city is used to verify the effectiveness of the model. Experimental results can show high traffic flow prediction accuracy of the model, and the model can accurately predict multiple different highway tunnels.

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Breakdown of effective-medium theory by a photonic spin Hall effect

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Science China(Physics,Mechanics & Astronomy) 2023年第11期66卷 145-154页

作者： Shuaijie Yuan Xinxing Zhou Yu Chen Yuhan Zhong Lijuan Sheng Hao Hu Hongsheng Chen Ido Kaminer Xiao Lin Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Synergetic Innovation Center for Quantum Effects and ApplicationsSchool of Physics and ElectronicsHunan Normal UniversityChangsha410081China International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Engineering Technology Research Center for 2D Material Information Function Devices and Systems of Guangdong ProvinceInstitute of Microscale OptoelectronicsShenzhen UniversityShenzhen518060China Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and InstrumentationZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiang UniversityHangzhou310027China International Joint Innovation Center Electromagnetics Academy at Zhejiang UniversityZhejiang UniversityHaining314400China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore639798Singapore Key Laboratory of Radar Imaging and Microwave Photonics Ministry of EducationCollege of Electronic and Information EngineeringNanjing University of Aeronautics and AstronauticsNanjing211106China Key Laboratory of Advanced Micro/Nano Electronic Devices&Smart Systems of Zhejiang Jinhua Institute of Zhejiang UniversityZhejiang UniversityJinhua321099China Shaoxing Institute of Zhejiang University Zhejiang UniversityShaoxing312000China Department of Electrical Engineering Technion-Israel Institute of TechnologyHaifa32000Israel

Effective-medium theory pertains to the theoretical modelling of homogenization,which aims to replace an inhomogeneous structure of subwavelength-scale constituents with a homogeneous effective *** effective-medium theory is fundamental to various realms,including electromagnetics and material science,since it can largely decrease the complexity in the exploration of light-matter interactions by providing simple acceptable ***,the effective-medium theory is thought to be applicable to any all-dielectric system with deep-subwavelength constituents,under the condition that the effective medium does not have a critical angle,at which the total internal reflection *** we reveal a fundamental breakdown of the effective-medium theory that can be applied in very general conditions:showing it for deep-subwavelength all-dielectric multilayers even without a critical *** finding relies on an exotic photonic spin Hall effect,which is shown to be ultrasensitive to the stacking order of deep-subwavelength dielectric layers,since the spin-orbit interaction of light is dependent on slight phase accumulations during the wave *** results indicate that the photonic spin Hall effect could provide a promising and powerful tool for measuring structural defects for all-dielectric systems even in the extreme nanometer scale.

关键词： photonic spin Hall effect effective-medium theory spin-orbit interaction of light

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Surface Defect Detection of Wooden Boards Based on Multi-Modal Fusion

Surface Defect Detection of Wooden Boards Based on Multi-Mod...

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Chinese Automation Congress (CAC)

作者： Hongchuan Zhang Song Zheng Yuhang Zhu Ye Lin Zhijie Ai Zhezhuang Xu Education Department of Fujian Province College of Electrical Engineering and Automation Fuzhou University and Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou China

Automated wood defect detection is of great significance for improving wood utilization. However, the stains on the wood surface resemble defect features and it is difficult to distinguish the appearance of wane from defect-free regions. Relying solely on machine vision for extracting surface features of wood makes it difficult to achieve accurate defect detection. To address these challenges, we propose MMDNet, a multimodal detection network that combines point cloud and image data. By adaptively fusing point cloud and image features at multiple stages, the network effectively highlights wood surface defect regions. Additionally, we introduce an Atrous Spatial Pyramid Pooling (ASPP) module into the network, which expands the network's receptive field and enables a comprehensive perception of the defects. Furthermore, we employ a deep supervision strategy to encourage the network to learn discriminative feature representations, enhancing the model's ability to differentiate defect regions. Experimental results validate the effectiveness of our method in detecting defects that are similar to the background and reducing interference from stains.

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