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检索条件"机构=Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsWuhan"

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A Finite-Time Posture control Strategy for the Swarm Underactuated Robots 5th

A Finite-Time Posture Control Strategy for the Swarm Under...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Huang, Zixin Qin, Xiangyu Wei, Shaoqi Wang, Lejun Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan430205 China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan430200 China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789811939976

Under the background of industrial machinery automation. The swarm robots are required to cooperate to complete complex and accurate works in finite-time and create more relative residual value. Based on the inherent advantages of underactuated robot, the research of finite time posture control strategy has higher theoretical and practical value. Firstly, the dynamic model of a single Pendubot of planar swarm underactuated robots was built. However, the robots reach to the same objective from different initial states and keep being at the same posture, so it was necessary to plan a feasible trajectory. Then, the planned trajectory parameters are optimized to make the underactuated robots relized the objectives in finite time. Finally, an unified tracking controller is designed for the underactuated robots. Simulation results of the swarm underactuated robots demonstrated the effectiveness of the proposed control strategy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Robots

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Bearing Fault Diagnosis Under Variable Working Conditions Based on Domain Adaptation and Improved Depthwise Separable Convolution Network 26

Bearing Fault Diagnosis Under Variable Working Conditions Ba...

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26th International Conference on Industrial Technology, ICIT 2025

作者： Kuang, Zehui Mao, Fan Zhao, Xingyu Wan, Xiongbo School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Future Technology China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (纸本)9798331521950

Domain adaptation methods and appropriate feature extractors are usually applied to solve the problem that the variable working conditions of bearings affect the effectiveness of the fault diagnostic framework. However, the existing feature extractors are too complex to be deployed in real industries. In this paper, we propose a lightweight framework called improved depthwise separable convolution network (IDSCN) for the diagnosis of bearing faults in variable operating conditions. IDSCN is built on wavelet convolution and depthwise separable residual convolution (DSRC), where the wavelet convolution is used to extract frequency features from the source and target domains, and DSRC guarantees the performance of feature extraction with reduced parameters and computation. To minimise the distribution difference between the source and target domains, the local maximum mean difference is incorporated into the proposed framework. The performance of the proposed framework is validated on the Paderborn University dataset, involving a total of 6 transfer tasks. The experiment shows that the proposed framework achieves satisfactory results and outperforms other frameworks in bearing fault diagnosis. © 2025 IEEE.

关键词： Bearing fault diagnosis Depthwise separable residual convolution Domain adaptation Wavelet convolution

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High Precision Tracking control Method Based on Model-Following control and Equivalent-Input-Disturbance 3

High Precision Tracking Control Method Based on Model-Follow...

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3rd International Workshop on intelligent Systems, IWIS 2023

作者： Jiang, Ruoyu She, Jinhua 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 School of Engineering Tokyo University of Technology Tokyo192-0982 Japan

ISBN: (纸本)9798350305043

This paper presents a high-precision control method based on the model-following control (MFC) and equivalent-input-disturbance (EID) approaches. The MFC approach ensures that the output of the plant tracks the output of a desired nominal model. The EID estimates and eliminates an external disturbance. The combination of these two methods effectively achieves high-precision tracking. The validity of this method is demonstrated by a vibration-suppression example through simulations. © 2023 IEEE.

关键词： Equivalent-input-disturbance model-following control vibration suppression

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Skeleton-based Action Recognition Using Two-stream Graph Convolutional Network with Pose Refinement 41

Skeleton-based Action Recognition Using Two-stream Graph Con...

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第41届中国控制会议

作者： Biao Zheng Luefeng Chen Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Electrical and Computer Engineering University of Alberta Tokyo Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the development of science and technology,graph convolutional network has made great progress in improving the accuracy of action ***,there still exists some deficiencies in current ***,the human skeleton point coordinates entering into the network are barely refined,which may cause large ***,the second-order information(the length and direction of bones),which can reflect action characteristics discriminatively,is rarely *** solve the above issues,a two stream graph convolutional network with pose refinement for skeleton based action recognition is ***,we use an adaptive block to to help improve the *** test our method on Kinetics dataset and the experiment show it can get better results than some recent methods,which plays a positive role in future research.

关键词： Graph convolutional network Pose refinement Skeleton based action recognition Adaptive block

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A Test Suite and An Optimizer for Dietary Nutrition Optimization Problem: From Constrained Many-Objective Perspective

A Test Suite and An Optimizer for Dietary Nutrition Optimiza...

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2023 IEEE Congress on Evolutionary Computation, CEC 2023

作者： Ti, Yaqi Li, Changhe Yang, Shengxiang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350314588

With increasing people who suffer from diet-related diseases, providing suggestions for personal daily nutrient-dense intake is highly expected. However, current dietary nutrition models are less precise, and dietary nutrition optimizers usually fail to give satisfactory solutions. Therefore, we construct a constrained many-objective nutrition model with more precise nutrient assessments and a scalable constrained many-objective benchmark set. This test suite has great flexibility in evaluating algorithms' performance on high dimensional search and objective spaces with some feasible region fragments. We also propose a kd-tree based dynamic constrained many-objective evolutionary algorithm to search for customized food combinations according to personal daily consumption and intake preference. Experiments show that our algorithm has better diversity maintenance ability in high dimension space. © 2023 IEEE.

关键词： Nutrition

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A Multi-view Non-negative Matrix Factorization Single-cell Clustering Algorithm for Missing Data

A Multi-view Non-negative Matrix Factorization Single-cell C...

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2022 International Conference on Algorithms, Data Mining, and Information Technology, ADMIT 2022

作者： Yu, Ailian Zhu, Yuan School of Automation China University of Geosciences Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (数字)9781665454728

ISBN: (纸本)9781665454728

A significant study focus on the field of bioinformatics has been on how to quickly and accurately accomplish the cell clustering task using computational approaches for single-cell RNA sequencing (scRNA-seq) data. Technical issues with scRNA-seq data include missing values, high noise levels, and a large batch impact. While the single-cell data recovery method based on data filling can enhance data quality, it will subjectively alter the distribution of data. To address the above-mentioned issues, we propose a non-negative matrix factorization clustering algorithm (scMVNMF) based on multi-view data of scRNA-seq. Under the assumption of essentially unchanging original data distribution, it can not only identify the typical low-dimensional representation patterns of multi-view data but also produce final explicable clustering findings. The results of the experiments demonstrate that the suggested algorithm has some advantages over the filling approach in terms of clustering tasks and can maintain a certain level of stability when the quality of single-cell data varies. © 2022 IEEE.

关键词： Non-negative matrix factorization

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Dual-polarization Dual-mode Silicon 3dB Beam Splitter Based on Shallow Etched Multimode Interference Coupler

Dual-polarization Dual-mode Silicon 3dB Beam Splitter Based ...

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Optoelectronics Global Conference (OGC)

作者： Hong Ma Mengyuan Ye Jie Liu Duowei Zeng Yang Chen School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan China

In this paper, we propose a dual polarization dual mode 3dB beam splitter. By utilizing the shallow etched multimode interference (MMI) coupler, the proposed device can handle TE 0 , TE 1 , TM 0 and TM 1 modes simul...

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Reinforcement learning-enhanced dynamic multi-objective evolutionary algorithm for cooperative shovel scheduling in open-pit mining

Reinforcement learning-enhanced dynamic multi-objective evol...

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2024 China automation Congress, CAC 2024

作者： Zhang, Zihao Li, Changhe Yang, Shengxiang School of Automation China University of Geosciences 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 School of Artificial Intelligence Anhui University of Science & Technology Hefei232001 China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350368604

Aiming at the ore blending problem in the open-pit mining scenario, the optimization objective is to minimize the grade variance of the sliding window of the ore flow, and a cooperative shovel scheduling model for real-time ore blending is established. A reinforcement learning-enhanced dynamic multi- objective evolutionary algorithm is proposed, where a Q-learning operator selection mechanism is introduced to reuse the information from the previous environment for tracking the optimal solution in the dynamic environment. Experimental results show that the proposed method can effectively control the grade fluctuation of the ore flow and dynamically respond to external events, and can find a better solution in real time compared with the traditional operator selection algorithm. © 2024 IEEE.

关键词： Open pit mining

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Motion Analysis and Experiment of Sheet Small Magnetron Soft Robot 8

Motion Analysis and Experiment of Sheet Small Magnetron Soft...

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8th International Conference on control Science and Systems Engineering, ICCSSE 2022

作者： Ma, Haoyun Zhang, Pan Wu, Jundong Wang, Yawu School of Automation China University of Geosciences Hubei Wuhan430 074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Hubei Wuhan430074 China

ISBN: (纸本)9781665484138

In the past, most robots used rigid structures. With the development of intelligent materials, more and more soft materials began to be used in the manufacture of robots. Magnetic-driven soft robot is one of its important branches. Because of the flexibility of magnetoelastic composite robots and the harmlessness of magnetic field to human body, a magnetically-controlled soft robot has broad application prospects in medical fields such as disease diagnosis and treatment in human body. A small lamellate magnetic soft robot is designed in this paper with the advantages of small volume, light weight, high deformation, fast and simple manufacture. And it can be driven without wire under the control of the magnetic field formed by the three-dimensional Helmholtz coil. The robot can walk and crawl on the surface of magnetically-controlled. The motion characteristics of the magnetic soft robot such as crawling step length and bending height are analyzed. The data are collected through experiments to analyze the relationship between the control signal and the motion characteristics. © 2022 IEEE.

关键词： Motion analysis

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Research on Dynamic Labels in Network Pruning

Research on Dynamic Labels in Network Pruning

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Industrial Cyber-Physical Systems (ICPS)

作者： Lijun Zhang Yaomin Luo Shiqi Xie Xiucheng Wu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences Wuhan China

Convolutional neural network compression technology plays an extremely important role in model transplantation and deployment, especially in mobile and embedded hardware platforms with small memory and low computing power, compression technology is even more critical. Convolutional neural network channel pruning technology has developed rapidly in recent years, and a number of excellent pruning algorithms have emerged. The channel pruning technology has gradually developed from the earliest static pruning to dynamic pruning, which adopts different pruning schemes for different inputs. However, the current dynamic pruning scheme needs to introduce multiple modules to predict the mask to prune the feature maps, and some schemes also introduce multiple hyperparameters in the loss function to balance the model accuracy and pruning rate, which leads to The model has difficulty converging during training. We propose a dynamic pruning method, each convolution structure configures a simple prediction module, and generating dynamic labels through the input's norm and similarity to guide the prediction module training, which will not bring new parameters to the loss function. We conducted related experiments on multiple models on the Cifar10 datasets. The experiments on ResNet56 show that our scheme is 1.3% higher than the most advanced scheme in terms of compression rate under the premise of the same accuracy.

关键词： Training Convolution Heuristic algorithms Computational modeling Predictive models Cyber-physical systems Prediction algorithms

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