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2024 International Convention on Rehabilitation engineering and Assistive Technology and World Rehabilitation Robot Convention, i-CREATE and WRRC 2024

作者： Lai, Jianwei Song, Aiguo Zhang, Wenbin Lu, Ye Wang, Jiajin Li, Ye School of Instrument Science and Engineering Southeast University State Key Laboratory of Digital Medical Engineering Jiangsu Key Laboratory of Remote Measurement and Control Nanjing210096 China College of Computer Science and Software Engineering Hohai University Nanjing210024 China

ISBN: (纸本)9798350355123

Soft robots offer promising solutions for rehabilitation due to their inherent attributes such as suppleness, lightweight construction, and safety features. However, prevalent soft actuators face limitations in output force and bending angle, impeding their effective application in rehabilitation. This paper proposes a novel design approach employing a two-layer lattice structure actuator, comprising flexion, guiding, and extension layers. This innovative design facilitates supple and efficient bi-directional rehabilitation training for fingers and wrists. Experimental results demonstrate the efficacy of the proposed dual-layer lattice structure actuator. At an air pressure of 150 kPa, it achieves an end force of 14.88 N, marking a remarkable 906% increase compared to its single-layer counterpart. Additionally, the dual-layer structure exhibits a minimum bending radius of 2.77 cm under 60 kPa, representing a 38.5% reduction relative to the single-layer actuator. Leveraging these actuators, a hand and wrist rehabilitation robot was developed and subjected to a clinical trial involving two healthy subjects. The trial outcomes reveal significant improvements in finger grasping ability and wrist range of motion with the assistance of the rehabilitation robot. These results underscore the practical usability and effectiveness of the soft hand and wrist rehabilitation robot, thereby holding promise for enhancing patient rehabilitation outcomes. © 2024 IEEE.

关键词： Patient rehabilitation

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Time-scheduled observer design for switched linear systems with unknown inputs

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Science China(Information Sciences) 2022年第7期65卷 265-266页

作者： Shuang SHI Zhongyang FEI Xudong ZHAO College of Automation Engineering Nanjing University of Aeronautics and Astronautics Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology

Dear editor, Since uncertain disturbance, actuator faults and unmodeled dynamics can all be viewed as unknown inputs in various practical systems, the issue of unknown input observer design is of great significance. Meanwhile, switched systems have attracted extensive attention, which are prevailingly motivated by superior capabilities in modeling numerous practical systems possessing switching characteristics. Recently, the state observation for switched systems with unknown inputs has attracted considerable attention [1–5].

关键词： switched linear systems unknown inputs admissible edge-dependent average dwell-time multiple discontinuous Lyapunov-like functions observer design

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A control Method for Coal Slime Water Thickening Process in Coal Preparation Plants Based on BP-TSFNN

A Control Method for Coal Slime Water Thickening Process in ...

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2024 China Automation Congress, CAC 2024

作者： Fu, Shangluo Zhou, Fan Zhao, Jun Wang, Wei Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education China School of Control Science and Engineering Dalian University of Technology Dalian China School of Information Science and Engineering Dalian Polytechnic University Dalian China

ISBN: (纸本)9798350368604

Aiming at the complex mechanism of coal slime water thickening process in coal preparation plant, which has the characteristics of multivariable and strong nonlinearity leading to the difficulty of realizing the intelligent optimization control, a model predictive control method based on back propagation neural network (BPNN) and Takagi-Sugeno fuzzy neural network (TSFNN) cascade (BP-TSFNN-MPC) is proposed. Further, in order to realize the intelligent optimization control of the thickening process, the BP-TSFNN-MPC controller is constructed, and the gradient descent optimization algorithm is used to solve the optimization problem. In the experimental part, the effectiveness of the model and control method is verified by combining the production data of the slime water concentration process and the simulation model of the thickener. The results show that the BP-TSFNN model has high prediction accuracy for the concentration process and BP-TSFNN-MPC has good control performance. © 2024 IEEE.

关键词： Model predictive control

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High-precision tracking control of parallel robots using the superhelix algorithm

High-precision tracking control of parallel robots using the...

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2024 China Automation Congress, CAC 2024

作者： Jiang, Haowei Li, Ruchao Quan, Lidi Li, Bing Xu, Xiaoyu Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems School of Engineering Huzhou University Huzhou313000 China School of Engineering Huzhou University Huzhou313000 China

ISBN: (纸本)9798350368604

The increasing demand for precision in industrial automation has amplified the importance of accurate control in parallel robots, particularly given their high nonlinearity, complex coupling, and sensitivity to environmental disturbances. This paper presents a trajectory tracking control strategy leveraging a super-helix algorithm and an adaptive integral terminal sliding mode controller, specifically designed to address the challenges posed by inertial forces, frequent acceleration shifts, and external perturbations in high-speed Delta parallel robots. By deriving a comprehensive dynamics model and integrating the convergence law with sliding mode and super-helix techniques, the proposed method significantly enhances system robustness and dynamic responsiveness. Simulation results demonstrate that, compared to traditional approaches, this method markedly improves trajectory tracking precision, disturbance resistance, and vibration suppression, enhancing system performance by up to 98.65%. This controller not only ensures high tracking accuracy but also holds considerable promise for practical industrial applications. © 2024 IEEE.

关键词： Sliding mode control

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Combined effect of zinc and cadmium ions on nitrification performance during the biological nitrogen removal of simulated livestock breeding wastewater

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Environmental Science and Pollution Research 2024年第28期31卷 41155-41166页

作者： Wang, Zhanpeng Huang, Jian Zhang, Hua Luo, Tao He, Chunhua Department of Municipal Engineering School of Environmental and Energy Engineering Anhui Jianzhu University Hefei230601 China Anhui Provincial Key Laboratory of Environmental Pollution Control and Resource Reuse Anhui Jianzhu University Hefei230009 China Anhui Research Academy of Ecological Civilization Hefei230601 China Joint Laboratory of Anhui Province for Pollution Control and Resource Utilization in Industrial Parks Hefei230041 China

Zinc and cadmium ions are usually found in livestock breeding wastewater, and the mixed ions will have an impact on the biological nitrogen removal. Nitrification performance plays an important role in biological nitrogen removal. In order to investigate the combined effect of zinc and cadmium ions on nitrification performance and to reveal the interactions between zinc and cadmium ions, three concentration ratios of zinc and cadmium ions, as well as 18 different concentration gradients were designed with the direct equipartition ray and the dilution factor method. The effect of pollutants on the nitrification performance of biological nitrogen removal was analyzed by the nonlinear regression equation, and the concentration-addition model was conducted to probe into the relationship between the mixed pollutants and the nitrification performance. The results showed that the effect on nitrification performance increased significantly with the increase of reaction duration and pollutant concentration, which indicated that the effects are concentration-dependent and time-dependent. The concentration-addition model suggested that the interactions between zinc and cadmium ions with different concentration ratios were mainly antagonistic, and as the percentage of cadmium ions in the mixtures increased, the antagonism between the mixtures became stronger. This study will provide a relevant theoretical basis for the regulation of the ratios and concentrations of heavy metal ions during the biological treatment of livestock breeding wastewater. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Wastewater treatment

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Modelling of blast furnace ironmaking process based on digital twin

Digital Twins and Applications

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Digital Twins and Applications 2024年第2期1卷 161-168页

作者： Yonghong Xu Chunjie Yang Zhe Liu State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhouChina

The blast furnace ironmaking process is a crucial step in the steel *** modelling the blast furnaces is significant in ensuring smooth operation and accelerating the digitalisation transformation of blast *** authors focus on the mechanism modelling of the blast furnace operation process,using a digital twin model development platform to simulate the main reaction processes inside the blast *** on-site production conditions,Si,Mn and Ti contents of molten iron and the corresponding indicators for model accuracy are *** Si,Mn,and Ti content,the Root Mean Square Error values are 0.0678,0.0108 and 0.0093 for dataset 1,while 0.0933,0.0120 and 0.0111 for dataset 2,respectively,indicating that the model has a small simulation error and high *** comparing the simulation results with accurate laboratory results,the model is validated to have satisfactory simulation reliability and compensates for the existing shortcomings in the blast furnace mechanism modelling field.

关键词： blast furnace ironmaking process digital twin mechanism modelling quality index

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Generating Adversarial Patterns in Facial Recognition with Visual Camouflage

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Journal of Shanghai Jiaotong University (Science) 2024年 1-12页

作者： Bao, Qirui Mei, Haiyang Wei, Huilin Lü, Zheng Wang, Yuxin Yang, Xin Key Laboratory of Social Computing and Cognitive Intelligence of Ministry of Education School of Control Science and EngineeringSchool of Computer Science and Technology Dalian University of Technology Liaoning Dalian116024 China Systems Engineering Institute Academy of Military Sciences Beijing100141 China

Deep neural networks, especially face recognition models, have been shown to be vulnerable to adversarial examples. However, existing attack methods for face recognition systems either cannot attack black-box models, are not universal, have cumbersome deployment processes, or lack camouflage and are easily detected by the human eye. In this paper, we propose an adversarial pattern generation method for face recognition and achieve universal black-box attacks by pasting the pattern on the frame of goggles. To achieve visual camouflage, we use a generative adversarial network (GAN). The scale of the generative network of GAN is increased to balance the performance conflict between concealment and adversarial behavior, the perceptual loss function based on VGG19 is used to constrain the color style and enhance GAN’s learning ability, and the fine-grained meta-learning adversarial attack strategy is used to carry out black-box attacks. Sufficient visualization results demonstrate that compared with existing methods, the proposed method can generate samples with camouflage and adversarial characteristics. Meanwhile, extensive quantitative experiments show that the generated samples have a high attack success rate against black-box models. © 2023, Shanghai Jiao Tong University.

关键词： Face recognition

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Diminishing ether-oxygen content of electrolytes enables temperature-immune lithium metal batteries

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Science China Chemistry 2023年第9期66卷 2700-2710页

作者： Tao Liu Jingnan Feng Zhe Shi Huajun Li Weina Zhao Minglei Mao Xiangzhen Zhu Yong-Sheng Hu Hong Li Xuejie Huang Liquan Chen Liumin Suo Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsChinese Academy of SciencesBeijing 100190China Qingdao Industrial Energy Storage Research Institute Qingdao Institute of Bioenergy and Bioprocess TechnologyChinese Academy of SciencesQingdao 266101China Department of Nuclear Science and Engineering and Department of Materials Science and Engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control Guangdong Key Laboratory of Environmental Catalysis and Health Risk ControlSchool of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China

The reversibility of lithium(Li) metal anodes is highly susceptible to temperature,owing to the aggravated side reactions at high temperatures and serious Li dendrite growth at low *** it is extremely challenging to simultaneously realize the high Li reversibility in both low and high temperature ***,an oxygen-free solvent(n-hexane,HEX) assisted with the hexyl methyl ether and 1 mol L^(-1)lithium bis(fluorosulfonyl)imide is proposed to constitute an electrolyte for temperatureimmune lithium metal *** demonstrates that the HEX not only greatly suppresses the solvent reduction even at high temperatures but also weaken the Li~+-solvent interaction for the facile Li-ion desolvation,leading to high Li Coulombic efficiencies(99.59% at 25℃,99.30%at 60℃ and 98.75% at -30℃) and the dendrite-free Li plating from -30℃ to 60℃.Benefitting from the low density and temperature-immune properties of our electrolyte,the sulfurized polyacrylonitrile(3.8mAh cm^(-2))||Li(60 μm) pouch-cells deliver 278 Wh kg^(-1)energy density and maintain the stable performance over 50 cycles,and retain 248 and 320 Wh kg^(-1) energy density at -30℃ and 60℃,*** work provides a new perspective on the electrolyte design for wide-temperature Li metal batteries.

关键词： wide temperature range oxygen-free solvent dendrite-free Li plating high Coulombic efficiencies lithium metal batteries

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Fixed- Time Adaptive Neural Pitch Angle control for Variable-Speed Wind Turbines 13

Fixed- Time Adaptive Neural Pitch Angle Control for Variable...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Xie, Shuzong Yang, Qinmin Li, Qingyi Wang, Shaodong Yang, Jun College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Zhejiang Provincial Energy Group Company Ltd. Jiaxing314000 China

ISBN: (纸本)9798350361674

This paper mainly focuses on the challenging problem of fixed-time adaptive neural pitch angle control for variable-speed wind turbines. Firstly, a switching continuous fixed-time sliding mode variable is adopted to avoid the singularity problem. Then, an adaptive sigmoid function neural network is introduced to approximate the unknown nonlinear function of wind tur-bines. On this basis, a fixed-time adaptive neural pitch angle controller is systematically developed, such that the tracking error can converge to a small neighborhood of the origin in fixed-time, thereby improving the power generation efficiency of wind turbines. Finally, the fixed-time stability of the whole closed-loop system is analyzed with rigorous theoretical proof, and the effectiveness of the proposed scheme is verified through a 1.5-MW three-blade wind turbine in Matlab/Simulink. © 2024 IEEE.

关键词： Windmill

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Attentive Neighborhood Feature Augmentation for Semi-supervised Learning

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Intelligent Automation & Soft Computing 2023年第8期37卷 1753-1771页

作者： Qi Liu Jing Li Xianmin Wang Wenpeng Zhao School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou510002China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang UniversityFuzhou350121China

Recent state-of-the-art semi-supervised learning(SSL)methods usually use data augmentations as core *** methods,however,are limited to simple transformations such as the augmentations under the instance’s naive representations or the augmentations under the instance’s semantic *** tackle this problem,we offer a unique insight into data augmentations and propose a novel data-augmentation-based semi-supervised learning method,called Attentive Neighborhood Feature Aug-mentation(ANFA).The motivation of our method lies in the observation that the relationship between the given feature and its neighborhood may contribute to constructing more reliable transformations for the data,and further facilitating the classifier to distinguish the ambiguous features from the low-dense ***,we first project the labeled and unlabeled data points into an embedding space and then construct a neighbor graph that serves as a similarity measure based on the similar representations in the embedding ***,we employ an attention mechanism to transform the target features into augmented ones based on the neighbor ***,we formulate a novel semi-supervised loss by encouraging the predictions of the interpolations of augmented features to be consistent with the corresponding interpolations of the predictions of the target *** carried out exper-iments on SVHN and CIFAR-10 benchmark datasets and the experimental results demonstrate that our method outperforms the state-of-the-art methods when the number of labeled examples is limited.

关键词： Semi-supervised learning attention mechanism feature augmentation consistency regularization

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