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IEEE International Conference on control Science and systems Engineering (CCSSE)

作者： Jianhui Tang Pan Zhang Jundong Wu Yawu Wang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Magnetically-controlled soft microrobots have great application prospects because of small size, flexible motion and wireless control. In this paper, a magnetically-controlled soft microrobot is designed and fabricated. In order to achieve its path-following control, two open-loop control strategies and a closed-loop one are developed. Especially, for the closed-loop control strategy, we present the image processing method and the pure pursuit algorithm, where the former is used to obtain the position and posture of the microrobot required for the latter. Finally, the developed open-loop and closed-loop control strategies are verified by carrying out the experiments. These methods are promising in numerous applications because of the ease of implementation.

关键词： Wireless communication Fabrication Magnetic resonance imaging Image processing Process control systems engineering and theory control systems

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Surface Defect Detection of Sanitary Ceramic Product Utilizing High-resolution Image on Two Different Scales

Surface Defect Detection of Sanitary Ceramic Product Utilizi...

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Chinese control and Decision Conference, CCDC

作者： Xing-Ao Wang Jianqi An Yisheng Mei Xin Chen Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9781665478977

Surface defect detection of sanitary ceramic products is an important part of the production process. The deep learning method is the mainstream research direction in the field of defect detection. Since there are many small defects on the surface of sanitary ceramic products, it is an effective means to use a high-resolution camera to obtain images. The detection speed of high-resolution pictures and the interference of background are the difficult problems in detection. Therefore, this paper designs a two-scale detection framework to detect and locate defects of sanitary ceramics utilizing high-resolution images. The two-scale detection framework speeds up the detection of high-resolution images and weakens the interference of the background by dividing the defect detection task into two parts, a workpiece region recognition task on large scale and a defect detection task on small scale. The experiments show that the two-scale detection method has a better detection speed and accuracy rate compared with the single-scale method, which proves the superiority of the proposed method.

关键词： Deep learning Image recognition Ceramic products Interference Production Cameras Ceramics

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Distributed Coverage control of Multi-Agent systems in Uncertain Environments using Heat Transfer Equations

arXiv

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arXiv 2022年

作者： Zheng, Yinan Zhai, Chao The School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

This paper addresses the coverage control problem of multi-agent system in the uncertain environment. With the aid of Voronoi partition, a distributed coverage control formulation of multi-agent system is proposed to complete the workload in the uncertain environments. Driven by the gradient of thermal field, each agent is able to move around for clearing the workload on its own subregion. Theoretical analysis is conducted to ensure the completion of workload in finite time. Finally, numerical simulations are carried out to demonstrate the effectiveness and advantages of the proposed coverage control approach as compared to other existing approaches. © 2022, CC BY.

关键词： Multi agent systems

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Reconstruction of spectral reflectance based on fusion convolution neural network 9

Reconstruction of spectral reflectance based on fusion convo...

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9th International Conference on Computing and Pattern Recognition, ICCPR 2020

作者： Zhang, Lijun Wang, Xiangguo Zhang, Jingjing Qiao, Jinlong Li, Penghui School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China

ISBN: (纸本)9781450387835

An improved method for spectral reflectance reconstruction from the RGB response of the digital camera is proposed by deep convolution neural network. The proposed method learns a fusion mapping theory that represents the basic characteristics of spectral reflectance, including spectral nonlinear mapping and spatial similarity. The deep residual network greatly deepens the network structure and improves the performance of the model, enabling the recovery network to make full use of the sample structure information to accurately recover the spectral reflectance. The performance of the method is compared with several existing methods in the cases of the same experimental data set. Experimental results show that the proposed method has the best accuracy in estimating spectral reflectance and colorimetric values in most cases in comparison with existing methods. © 2020 ACM.

关键词： Deep neural networks

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Containment control for Multi-Agent systems under Directed Interaction Topologies with Time-Varying Delays

Containment Control for Multi-Agent Systems under Directed I...

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International Conference on control, automation and systems ( ICCAS)

作者： Xiaojie Peng Yong He School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

This paper is concerned with the containment control problem for multi-agent systems(MASs) with time-varying delays. for the purpose of obtaining less conservative containment control criterion, an augmented Lyapunov-Krasovskii functional(LKF) considering more delay information is constructed firstly. Then by employing the Wirtinger-based integral inequality(WBII) and the extended reciprocally convex matrix inequality(ERCMI) to estimate the derivative of LKF, the delay-dependent term ignored in previous works is reconsidered. Moreover, a delay-product-type(DPT) functional based on the Jensen inequality is established to further reduce the conservatism of the outcomes. As a result, two new criteria are derived to ensure the containment consensus on the communication directed graph, the upper bound of maximum delays and feedback gains. Finally, two numerical simulations are employed to demonstrate the superiority of the theoretical results.

关键词： Upper bound control systems Numerical simulation Delays Topology Linear matrix inequalities Time-varying systems

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Image Super-Resolution of Residual-Dense Connected Networks in Unmanned Deep-Sea Exploration Equipment

Image Super-Resolution of Residual-Dense Connected Networks ...

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Chinese control Conference (CCC)

作者： Jiajun Chu Weihua Cao Chao Gan Yulong Yang School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China

Deep-sea unmanned exploration equipment is an important tool for exploring and developing the resources in the ocean, and it can survey the deep-sea environment more visually with the help of visual images. However, the complex and variable environment and the low resolution of the underwater lens lead to the poor resolution of the images acquired by the equipment. In this paper, we propose a residual-dense connected method applied to unmanned deep-sea exploration equipment to improve it's image resolution. The method uses dense connections within the residual structure to improve the model detail information acquisition to ensure accuracy and model stability of model. Secondly, through the study of the model performance, a high precision residual-dense connected model with less computational effort is designed. Finally, the model is trained and tested using environmental images in deep-sea conditions, and it is demonstrated that the method can be applied to deep-sea unmanned exploration equipment for fast, accurate, and stable image super-resolution processing.

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Group Consensus of Multi-agent systems with Additive Noises and Multiplicative Noises

Group Consensus of Multi-agent Systems with Additive Noises ...

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Chinese automation Congress (CAC)

作者： Haoxiang Qin Chuanjian Li Xiaofeng Zong School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

In this paper, we study the group consensus problem of multi-agent systems with additive noises and multiplicative noises. The multi-agent systems are composed of two sub networks affected by additive noises and multiplicative noises, respectively. A consensus protocol is designed to guarantee the group consensus. Based on this protocol, the mean square weak consensus condition and mean square strong consensus condition are obtained by algebraic graph theory and stochastic stability theory. Finally, the numerical simulations show the effectiveness of the group consensus protocol in this paper.

关键词： Additive noise Differential equations Numerical simulation Stability analysis Consensus protocol Thermal stability Numerical stability

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control Strategy of Electrolytic Capacitor-Less Multi-port Converter for Suppressing the Influences of Low-Frequency DC-Link Current Ripple

Control Strategy of Electrolytic Capacitor-Less Multi-port C...

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Smart Power & Internet Energy systems (SPIES), International Conference on

作者： Zihong Zhang Zhijian Fang Yuangeng Xia Hanlin Dong Haojiang Yue School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Multi-port Converter (MPC) gets growing applications due to its advantages of flexible control mode, high power density, bidirectional power delivery capability, etc. However, the inherent instantaneous power difference between each port will generate significant low frequency dc-link current ripple, which degrades the operational stability of the system. To suppress the influence, the mechanism of dc-link current ripple is analyzed. And then, a compound control strategy based on the repetitive controller (RC) plus a PR controller is adopted according to the ripple characteristics for the electrolytic Capacitor-Less Multi-port Converter. The developed current control strategy in this paper can achieve a minimum steady-state error while maintaining a relatively fast transient response. Finally, to validate the proposed strategy, a simulation is also built and tested. The simulation results validate the theoretical analysis.

关键词： Transient response Power system measurements Simulation Power system dynamics Power system stability Frequency conversion Stability analysis

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Emotion Recognition via Environmental Context and Human Body

Emotion Recognition via Environmental Context and Human Body

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Industrial Cyber-Physical systems (ICPS)

作者： Cheng-Shan Jiang Zhen-Tao Liu School of Automation China University of Geosciences Wuhan P. R. China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan P. R. China

To promote the humanized interactive experience of the intelligent device and system, emotional intelligence has become a popular research field in the human-machine interaction. The previous research on emotion recognition based on computer vision has mostly been carried out by analysing facial expression or body posture, and psychological studies show that scene context also contributes some important information on emotion recognition. In addition, most context-aware emotion recognition studies focus on exploring the relevance analysis of environmental semantics, but the influence of feature encoder on semantic information embedding has not been fully discussed. In this paper, we proposed a Global Semantic Feature Enhancement-Dual Stream Densely Connected Network (GSFE-DSDCN) to enhance global semantic information learning from the perspectives of dimension and spatial. Densely connected pattern is introduced to concatenate the shallow and deep layers output, which fuses the semantic information of low-dimensional geometric features and high-dimensional abstract context features together. The Global Multi-Scale Feature Recalibration (GMSFR) module expands the receptive field in spatial, which effectively improves the global semantic features extraction capability of feature encoder. We evaluate the proposed method on the EMOTIC data set, and experimental results are shown to be competitive with the state-of-the-art algorithms.

关键词： Human computer interaction Emotion recognition Computer vision Fuses Biological system modeling Semantics Psychology

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Safe Reinforcement Learning for Social Motor Coordination in Two Dimensional Space 26

Safe Reinforcement Learning for Social Motor Coordination in...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Yang, Fan Huang, Yuening Zhai, Chao Zhang, Hehong China University of Geosciences School of Automation Wuhan Campus China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Rice University George R. Brown School of Engineering and Computing HoustonTX United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (纸本)9798331521950

This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints. © 2025 IEEE.

关键词： Reinforcement learning

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