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13th IEEE International Conference on CYBER Technology in Automation, control, and Intelligent systems, CYBER 2023

作者： Zeng, Sheng Sun, Xiao Chen, Kang Huang, Weibing Chen, Yi Chen, Dan Xu, Zhezhuang College of Electrical Engineering and Automation Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou University Education Department of Fujian Province Fuzhou350000 China Evomotion Co. Ltd. Guangdong Shenzhen518000 China

ISBN: (纸本)9798350315196

High cost of environmental interaction and low data efficiency limit the development of reinforcement learning in robotic grasping. This paper proposes an end-to-end robotic grasping method based on offline reinforcement learning via sequence modeling. It considers the most recent n-step history to assist the agent in making decisions, where a predictive model learns to directly predict actions from raw image inputs. The experimental results show that our method can achieve higher grasping success rate with less training data than traditional reinforcement learning algorithms in offline setting. © 2023 IEEE.

关键词： Reinforcement learning

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Pattern Analysis and Placement Optimization of the Four-horn Monopulse for Terahertz Communication

Pattern Analysis and Placement Optimization of the Four-horn...

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2023 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2023

作者： Lu, Yong-Han Zhu, Zhong-Bo Ma, Jing Shi, Bin Zhang, Yu-Ting Peng, Lin Guilin University of Electronic Technology Key Laboratory of Microwave and Optical Wave Application Technology Guangxi Guilin541004 China National Key Laboratory of Science and Technology on Space Microwave Xi'an710100 China Beijing Simulation Center Science and Technology on Special System Simulation Laboratory Beijing100854 China School of Optoelectronic Engineering Guangxi Key Laboratory of Optoelectronic Information Processing Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9798350358971

The mobile node communication in terahertz monopulse system requires narrow beam to align with the mobile target precisely. In this paper, the radiation pattern of four-horn monopulse antenna is analyzed by use of the geometric optics (GO) and aperture field integration method (AFIM), and an efficient placement optimization to reduce the beamwidth of four-horn monopulse is presented. The optimization combines the genetic algorithm (GA) with GO-AFIM. The GA is employed to seek the optimal positions of the four horns, and the GO and AFIM are introduced into the fitness function of GA to evaluate the individual fitness. The optimization result has narrowed the beamwidth and enhanced gain of radiation pattern. Compared with the simulation in full wave software, the proposed method costs less time in pattern analysis and performs more efficiently in placement optimization. © 2023 IEEE.

关键词： aperture field integration method (AFIM) geometric optics (GO) placement optimization terahertz monopulse

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Predicting the State of Crane Spreader for Steel Bar Delivery Based on Machine Learning 13

Predicting the State of Crane Spreader for Steel Bar Deliver...

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13th IEEE International Conference on CYBER Technology in Automation, control, and Intelligent systems, CYBER 2023

作者： Liu, Zibin Xu, Zhezhuang Chen, Jian Cui, Chen Chen, Boyu Zhang, Qingdong College of Electrical Engineering and Automation Key Laboratory of Industrial Automation Control Technology and Information Processing Education Fuzhou University Department of Fujian Province Fuzhou350000 China Sansteel Minguang Co. Ltd Fujian Sanming353000 China

ISBN: (纸本)9798350315196

Deducing the twisting pattern of spreader is very important for crane operators in steel warehouse, since crane spreaders have to be rotated repeatedly at steel bar transport sites. To improve the efficiency of the steel bar delivery, the state prediction for crane spreaders is necessary. In order to fulfill this requirement, the HTSK-LN-ReLU model prediction method based on Optuna optimization is applied in this paper. We deploy the IMU on the spreader surface, and then obtain the state data during the operation of the crane spreader by wireless transmission. The data are first denoised through fourier filtering, and then the Optuna framework is used to optimize the HTSK-LN-ReLU model's hyperparameters. The evaluation index of mean square error is used for model evaluation, and finally the optimal hyperparameter combination of the model is selected from 200 comparison experiments. Experimental results demonstrate superior performance of the HTSK-LN-ReLU model in predicting the state of crane spreader for steel bar delivery. © 2023 IEEE.

关键词： Forecasting

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Metric Learning with Distillation for Overcoming Catastrophic Forgetting 16th

Metric Learning with Distillation for Overcoming Catastrop...

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16th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2021

作者： Yu, Piaoyao He, Juanjuan Min, Qilang Zhu, Qi College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China

ISBN: (纸本)9789811912528

In incremental learning, reducing catastrophic forgetting always adds additional weights to the classification layer when a new task comes. Moreover, it focuses on prediction accuracy, ignores mislabeling differences, and causes the learned features to be scattered. This paper removes the softmax and integrates depth metric learning to compute image embeddings, which doesn’t need to add extra weights or additional space for new classes. The distances of the data mapped in the old and new task spaces are calculated separately. Then, the distillation of depth metric learning is used to make the two distances as similar as possible to improve the performance of the old knowledge. The experimental results on Cifar10 and Tiny-ImageNet show that the proposed method can effectively alleviate catastrophic forgetting and enhance the effectiveness of incremental learning. © 2022, Springer Nature Singapore Pte Ltd.

关键词： Distillation

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An Enhanced Particle Swarm Algorithm Based on Fitness Landscape information

An Enhanced Particle Swarm Algorithm Based on Fitness Landsc...

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Congress on Evolutionary Computation

作者： Zhenya Diao Fei Yu Jian Guan Meitong Liu Key Lab of Intelligent Optimization and Information Processing School of Physics and Information Engineering Minnan Normal University Zhangzhou China Key Laboratory of Light Field Manipulation and System Integration Applications in Fujian Province Key Lab of Intelligent Optimization and Information Processing School of Physics and Information Engineering Minnan Normal University Zhangzhou China

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

In the original Particle Swarm Optimization (PSO), the selection of parameters significantly impacts the search capability of PSO. The paper introduces an innovative algorithm called Fitness Landscape-based PSO (FLPSO) to address the impact of parameter selection on the search capability of PSO. The algorithm focuses on acquiring fitness landscape information and analyzing the population state to intelligently select appropriate parameters in each generation. FLPSO defines four primary states: exploration, exploitation, convergence, and escaping state. In the convergence state, an elite learning strategy is incorporated to help the algorithm escape potential local optima by targeting the global best particle. To validate the efficacy of FLPSO, the paper conducted experiments on 30 different characteristic test functions from CEC2017. FLPSO was compared with six existing algorithms: PSO, PSO-TVAC, APSO, AWPSO, RPSO and ASRPPSO. The experimental results showed significant improvements in FLPSO, providing promising evidence for its effectiveness.

关键词： Sociology Particle swarm optimization Statistics Convergence

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In-plane shear failure behavior and mechanical properties of SiC/SiC Composites 3

In-plane shear failure behavior and mechanical properties of...

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2024 3rd International Conference on Applied Mechanics and Advanced Materials, ICAMAM 2024

作者： Li, Tianshan Yu, Guoqiang Zhou, Shihao Zheng, Zhikang Gao, Xiguang Song, Yingdong Key Laboratory of Aero-Engine Thermal Environment and Structure Ministry of Industry and Information Technology College of Energy and Power Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China Jiangsu Province Key Laboratory of Aerospace Power System College of Energy and Power Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and Astronautics Nanjing210016 China

Fiber-reinforced ceramic matrix composites, especially SiC/SiC composites, have the characteristics of lightweight, high strength, high-temperature resistance, etc., which are ideal structural candidates for aerospace vehicle components, in-plane shear performance is one of the important indicators to characterize the mechanical properties of materials and component assessment, this paper designs and processes the in-plane shear test pieces and test devices and methods to study the shear mechanical behavior under the mechanical properties and failure behavior of SiC/SiC ceramic-based fiber bundle composites are studied under shear mechanical behavior. The results show that matrix cracking and fiber fracture are the main failure modes, and there are two obvious phases in the specimen shear force-displacement curves, and fiber fracture is the main cause of strain in the specimen. © Published under licence by IOP Publishing Ltd.

关键词： Ceramic matrix composites

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Image Dehazing Network Based on Multi-scale Feature Extraction 4th

Image Dehazing Network Based on Multi-scale Feature Extracti...

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4th International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2021

作者： Feng, Ting Zhang, Fuquan Yu, Zhaochai Li, Zuoyong Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China

ISBN: (纸本)9789811640384

To remove image haze and make haze image scene clear, we proposed an image dehazing network based on multi-scale feature extraction (MSFNet) in this paper. The MSFNet first directly performs feature extraction on hazy images with three different resolutions to obtain fine feature maps and concatenates them with the rough feature maps extracted in the downsampling process for fusing and obtaining richer image information. Then, the fused feature maps are put into a network module composed of ResNeXt building blocks for network learning. Next, the feature maps extracted by upsampling are sequentially concatenated with the feature maps learned by the ResNeXt module for obtaining the residual image. Finally, the learned residual image is added to the input hazy image to obtain the image dehazing result. The experimental results on the SOTS dataset show that the MSFNet improves effectiveness of image dehazing. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feature extraction

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Lead-free perovskite Cs_(2)AgBiBr_(6)photodetector detecting NIR light driven by titanium nitride plasmonic hot holes

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Photonics Research 2024年第3期12卷 522-533页

作者： ZIJIAN LIU YUYING XI WENBO ZENG TING JI WENYAN WANG SITONG GUO LINLIN SHI RONG WEN YANXIA CUI GUOHUI LI College of Physics College of Electronic Information and Optical EngineeringKey Laboratory of Advanced Transducers and Intelligent Control System of Ministry of EducationTaiyuan University of TechnologyTaiyuan 030024China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030032China

Lead-free perovskite Cs_(2)AgBiBr_(6)manifests great potential in developing high-performance,environmentally friendly,solution-processable photodetectors(PDs).However,due to the relatively large energy bandgap,the spectrum responses of Cs_(2)AgBiBr_(6)PDs are limited to the ultraviolet and visible region with wavelengths shorter than 560 *** this work,a broadband Cs_(2)AgBiBr_(6)PD covering the ultraviolet,visible,and near infrared(NIR)range is demonstrated by incorporating titanium nitride(TiN)nanoparticles that are prepared with the assistance of self-assembled polystyrene sphere *** addition,an atomically thick Al2O3layer is introduced at the interface between the Cs_(2)AgBiBr_(6)film and TiN nanoparticles to alleviate the dark current deterioration caused by nanoparticle *** a result,beyond the spectrum range where Cs_(2)AgBiBr_(6)absorbs light,the external quantum efficiency(EQE)of the TiN nanoparticle incorporated Cs_(2)AgBiBr_(6)PD is enhanced significantly compared with that of the control,displaying enhancement factors as high as 2000 over a broadband NIR wavelength *** demonstrated enhancement in EQE arises from the photocurrent contribution of plasmonic hot holes injected from TiN nanoparticles into Cs_(2)AgBiBr_(6).This work promotes the development of broadband solution-processable perovskite PDs,providing a promising strategy for realizing photodetection in the NIR region.

关键词： perovskite titanium ultraviolet

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Modulating surface cation vacancies of nickel-cobalt oxides as efficient catalysts for lithium-oxygen batteries

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Journal of Materials Science & Technology 2023年第8期139卷 147-155页

作者： Yuan Yang Linna Dai Jianwei Qiu Zhibiao Hu Peng Wang Yongtao Zhao Huanhuan Guo Pengchao Si Rui Song Center for Robotics School of Control Science and EngineeringShandong UniversityJinan 250061China Research Center for Carbon Nanomaterials Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials(Ministry of Education)School of Materials Science and EngineeringShandong UniversityJinan 250061China School of Mechanical Electrical and Information EngineeringShandong UniversityWeihai 264209China College of Chemistry and Chemical Engineering Xingtai UniversityXingtai 054001China

Rechargeable lithium-oxygen batteries(LOBs)have received incremental attention owing to their high energy density and applicability to mobile devices and electric ***,the lack of robust,low-cost,and environmentally benign bifunctional catalysts is a major impediment to the commercial *** introduction of vacancies is one of the effective strategies to enhance the performance of cathode catalysts for lithium-oxygen batteries,but the preparation is *** this work,needle-like microsphere cathode catalysts of nickel-cobalt oxide containing cationic vacancies are constructed by controlling the annealing *** is demonstrated that the presence of cationic vacancies can modulate the electronic structure of the catalyst,reduce the energy barrier for the oxygen electrode re-action,meanwhile enhance the bifunctional catalytic ***,the nickel-cobalt oxide-based LOB with cationic vacancies exhibits large specific capacity(12,205 mAh g^(-1)at 200 mA g^(-1))and good *** work provides worthwhile insight into the formation and catalytic enhancement mech-anism of transition metal oxide catalysts with cationic vacancies,and to some extent,the creation of efficient and low-cost oxygen electrocatalysts for LOBs.

关键词： Li-O_(2)batteries Metal oxides Cation vacancies Catalytic kinetic

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Adaptive Neural Consensus Tracking control for Nonlinear Multiagent systems with Dead Zone and Sensor Faults 42

Adaptive Neural Consensus Tracking Control for Nonlinear Mul...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Chengjie Chen, Ci Liu, Zhi Li, Zhenni Guangdong University of Technology Guangzhou510006 China Guangdong Key Laboratory of IoT Information Technology Guangzhou510006 China 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangzhou510006 China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou510006 China Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing Ministry of Education Guangzhou510006 China

ISBN: (纸本)9789887581543

In this paper, an adaptive neural tracking control design is investigated for uncertain multiagent systems (MASs) with actuator dead zone and sensor faults. The adaptive control technique based on neural networks is employed to handle the uncertainty in the systems, which, however, results in a bounded tracking error from most existing works. To achieve the asymptotic tracking performance, we proposed a direct adaptive strategy via the tuning function method. Technically, a Lyapunov function with a series of smooth functions is designed, which benefits proposing of an asymptotic controller. Then, under the framework of direct adaptive control, an inverse compensation scheme, as well as a fault-tolerant mechanism, are considered for disposing of the actuator dead zone and sensor failures. As a result, user-preset tracking performance is achieved and the system error in the MASs converges to a predefined range. An example in the simulation section illustrates the effectiveness of the proposed method. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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