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Chinese automation Congress (CAC)

作者： Qingqing Yan Bei Dong Xin Li Yiwen Xiang Dapeng Luo Longsheng Wei School of Automation China University of Geosciences Wuhan China Key Laboratory of Geological Survey and Evaluation of Ministry of Education Wuhan China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Intelligent Technology co. Ltd of Chinese Construction Third Engineering Bureau Wuhan China School of Electronic Information and Mechanics China University of Geosciences Wuhan China

ISBN: (纸本)9781665426480

Deep learning-based no-reference image quality assessment (NR-IQA) algorithm requires massive training data and labels, but data scarcity usually exists in practical applications. Most of the previous metrics used pre-trained networks to solve this problem by fine-tuning on the target tasks. Unfortunately, the network trained on other tasks cannot be directly applied to IQA tasks and failed when encountering complex distortions. To reduce dependence on labeled data and improve generalization ability of unknown distortion types, a NR-IQA metric based on Meta-SGD is proposed, which can learn the quick adaptability of humans and obtain general meta-knowledge for distortion evaluation. Specifically, we collected a great many NR-IQA tasks with different distortion types to pre-train the model; then a meta-learning metric based on optimization, Meta-SGD, is proposed to acquire the meta-knowledge when evaluating images quality with various known distortions; finally, the obtained pre-trained meta-model can be directly applied to the new NR-IQA tasks only by fine-tuning a few images. Experiments on the TID2013 database demonstrate that the model after meta-learning obviously outperforms than some existing methods, and the average SRCC value for all types of distortion performance tests can reach 0.91.

关键词： Measurement Image quality Adaptation models automation Databases Training data Distortion

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An Universal control Strategy for Planar 2-DoF Underactuated Manipulator with One Passive Joint

An Universal Control Strategy for Planar 2-DoF Underactuated...

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第40届中国控制会议

作者： Zixin Huang Yaosheng Zhou Zhen Chen Wei Wang Lejun Wang School of Electrical and Information Engineering Wuhan Institute of Technology Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Innovation and Entrepreneurship Wuhan Institute of Technology School of Information and Safety Engineering Zhongnan University of Economics and Law

This paper presents an unified control strategy based on the trajectory planning and tracking control for the planar 2-Do F underactuated manipulator. The trajectory of the active link is composed of two parts. The first part trajectories are designed according to the initial and target angles of the active link. The second part trajectories are designed based on the constraints between the underactuated link and the active link. Meanwhile, the parameters of the trajectories are optimized by the differential evolution algorithm(DEA) to ensure all links eventually reach to their target values by tracking the designed trajectories. Then,the sliding mode variable structure controller are designed to make the active link track their trajectories. The effectiveness of such strategy is demonstrated through simulation results.

关键词： Planar 2-DoF underactuated manipulator Trajectory planning Tracking control Differential evolution algorithm

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Stability and Bifurcation control of Fractional BAM Neural Networks with Diffusion and Time Delays

Stability and Bifurcation control of Fractional BAM Neural N...

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Chinese control Conference (CCC)

作者： Feng Liu Wei Wang Gang Cai Feifan Zhou Hua O Wang Xiuqin Yang School of Automation China University of Geosciences Wuhan China Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Department of Mechanical Engineering Boston University Boston MA USA School of Education Minzu University of China Beijing China

Based on fractional calculus theory and reaction-diffusion equation theory, a fractional-order time-delay reaction-diffusion neural network with Neumann boundary conditions is investigated. By constructing the phase space basis based on the Laplace operator eigenvector, the system equation is linearized to obtain the characteristic equation. Then, the characteristic equation is analyzed, and the local stability of the system at the equilibrium point is discussed. And taking the time delay as the bifurcation parameter, the stability changes of the system at the equilibrium point and the generation conditions of the Hopf bifurcation are studied when the time delay changes. Moreover, a state feedback controller is designed to control the bifurcation of the system. Finally, the theoretical derivation is verified by numerical simulation.

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Explainable Deep Learning for Semg-Based Similar Gesture Recognition: A Shapley-Value-Based Solution

SSRN

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SSRN 2023年

作者： Wang, Feng Ao, Xiaohu Wu, Min Kawata, Seiichi She, Jinhua School of Automation China University of Geosciences Wuhan430074 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 School of Engineering Tokyo University of Technology Hachioji Tokyo192-0982 Japan

Surface electromyography (sEMG) based gesture recognition shows promise in enhancing human-robot interaction. However, accurately recognizing similar gestures is a challenging task, and the underlying mechanisms of gesture recognition are not well understood. To address these issues, we developed a new solution called the Shapley-value-based similar gesture recognition (SV-SGR) method. Our solution combines deep learning and game theory to achieve high recognition accuracy and interpretability. First, we devised a data preprocessing method that converts sEMG signals into sEMG color images, which can be more effectively utilized by deep learning techniques. Next, we established a deep-neural-network-based model for gesture recognition using the processed sEMG color images. Then, we designed a global explanation approach based on Shapley values to quantify the contribution of each channel to recognizing similar gestures. Finally, we carried out an explanation analysis, which provides feedback on the recognition model to enhance the precision of gesture recognition. Extensive comparisons and interpretable analyses have been conducted on real-world datasets, and the results demonstrate that the SV-SGR method outperforms other baselines under various experimental conditions. The interpretable analysis method based on Shapley values effectively enhances the performance of recognizing similar gestures and provides valuable insights into the decision-making process of recognition models. © 2023, The Authors. All rights reserved.

关键词： Gesture recognition

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Teleoperation System of the Internet-based Omnidirectional Mobile Robot with A Mounted Manipulator

Teleoperation System of the Internet-based Omnidirectional M...

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IEEE International Conference on Mechatronics and automation

作者： Dawei Wang Jianqiang Yi Dongbin Zhao Guosheng Yang Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy and Sciences Beijing China Institute of Advanced Control and Intelligent Information Processing College of Computer and Informaion Engineering Henan University Kaifeng China

A platform of the Internet-based teleoperation system with an omni-directional mobile robot which has a five DOFs robot arm is constructed. Remote control of the robot through the Internet is implemented. The system is featured as low-cost and user interface friendly: remote users can control the robot through the Internet just by a client program in a general computer. The client computer can receive the live video and environment information measured by sensors. With the help of the remote video and the local simulation, users can easily communicate with the robot. Different modules are proposed and the implementation method of the system is presented. Related experiments are conducted to test the validity of the proposed system.

关键词： Internet Mobile robots Manipulators Robot sensing systems Robot control User interfaces control systems Computer interfaces Computational modeling System testing

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Dynamic Analysis and control of Fractional Order Memristor Hopfield Neural Network

Dynamic Analysis and Control of Fractional Order Memristor H...

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Chinese control Conference (CCC)

作者： Feng Liu Gang Cai Feifan Zhou Wei Wang Hua Wang Xiuqin Yang School of Automation China University of Geosciences Wuhan China Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Department of Mechanical Engineering Boston University Boston MA USA School of Education Minzu University of China Beijing China

In this paper, a novel smooth magnetron is introduced to construct a fractional memristor Hopfield neural network (fractional order M-HNN). The local stability of equilibrium point are analyzed theoretically. Taking the memristor coupling strength coefficient and the fractional order as bifurcation parameters, the phase trajectory diagram, the bifurcation diagram of the system are drawn to analyze the influence on the dynamic behavior of the neural network. When the system parameters are fixed, the hyperchaos phenomenon of the fractional order M-HNN model is revealed. Finally, the PD controller is applied to the model to enhance the stability of the system.

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K-Means Clustering-based Kernel Canonical Correlation Analysis for Multimodal Emotion Recognition ⁎

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IFAC-PapersOnLine 2020年第2期53卷 10250-10254页

作者： Luefeng Chen Kuanlin Wang Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Department of Electrical and Computer Engineering University of Alberta Edmonton AB T6R 2G7 Canada Tokyo Institute of Technology Yokohama 226-8502 Japan

Emotion is an important part of human interaction. Emotional recognition can greatly promote human-centered interaction techniques. On this basis, multimodal feature fusion can effectively improve the emotion recognition rate. However, in the multimodal feature fusion at the feature level, most of the methods do not consider the intrinsic relationship between different modes. Only the fusion of analysis and transformation of the feature matrices of different modes does not make better use of modal differences to improve the recognition rate. This problem led us to propose feature fusion method based on K-Means clustering and kernel canonical correlation analysis (KCCA). Clustering makes the classification of features not classified by mode, but by the degree of influence on emotional labels, thus positively affecting the results of KCCA. The experimental results obtained on the Savee database show that the proposed K-Means based KCCA improves overall classification performance and produces higher recognition rate than that of the state of art methods, such as the Informed Segmentation and Labeling Approach.

关键词： Emotion Recognition K-Means Clustering Kernel Canonical Correlation Analysis Feature Fusion

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Interpretable analysis of feature importance and implicit correlation based on sEMG grayscale. images

Interpretable analysis of feature importance and implicit co...

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Industrial Cyber-Physical systems (ICPS)

作者： Xiaohu AO Feng Wang Juan Zhao Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan

for patients requiring upper limb rehabilitation, the hand rehabilitation robot assists the patient in completing movements within a certain training trajectory to achieve therapeutic results. There have been studies based on deep learning to convert surface electromyography (sEMG) signals into sEMG images for motion intention analysis. Although good recognition accuracy has been achieved, the working principle of neural networks and the processing of image features by the networks are not well explained. The interpretability of deep neural networks determines human confidence in neural network decisions. In this paper, we design a method based on feature importance and implicit correlation for hand motion intention recognition, experimentally explored that convolutional neural networks have implicit definitions for sEMG grayscale images of the same hand gesture action, and verified the effectiveness of the designed method.

关键词： Deep learning Analytical models Correlation Image recognition Neural networks Thumb Gray-scale

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The 110kV Live-Maintaining Robot control System Design for Substation Equipment in complex Working Conditions 42

The 110kV Live-Maintaining Robot Control System Design for S...

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42nd Chinese control Conference, CCC 2023

作者： Hu, Chenyu Chen, Xin Li, Chengyu Huang, Guangxian Zhou, Cheng Jian, Xu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Future Technology China University of Geosciences Wuhan430074 China State Grid Hubei Electric Power Co. Ltd. Xianning Power Supply Company Distribution Department Xianning437000 China State Grid Hubei Electric Power Co. Ltd Operations and Maintenance Department Xianning xian'An District Power Supply Company Xianning437000 China Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan430077 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

Live-maintaining work is essential for continuous power supply to the substation. To improve the safety and efficiency of live-maintaining work, this paper proposes an equipotential live-maintaining robot system suitable for 110kV voltage levels. Considering the narrow space, complex working conditions and strong electromagnetic interference in substations, binocular vision technology, manipulator trajectory planning algorithm based on time-energy optimization, high voltage electromagnetic shielding technology are utilized to develop the system, and the live-maintaining robot is successfully applied in actual substation. By accurately identifying and locating the joint bolts and insulator, the robot system can achieve equipotential live-disassemble, live-assemble the joint bolts within 18 minutes and live-clean insulator within 5 minutes, demonstrating its the effectiveness and practicability. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Electromagnetic pulse

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Analysis and circuit implementation of a new fourth-order multi-wing chaotic system based on memristors

Analysis and circuit implementation of a new fourth-order mu...

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Chinese automation Congress (CAC)

作者： Lei Jia Xiaowei Jiang Xianhe Zhang Ming Chi Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Geodetection Technology Ministry of Education School of Automation China University of Geosciences Wuhan P. R. China School of Electrical Engineering and Automation Hubei Normal University Huangshi P. R. China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan P. R. China

ISBN: (纸本)9781665426480

In this paper, a new fourth-orders memristor chaotic system is obtained by introducing a smooth memristor model as the feedback term based on the modified three-orders chaotic system. The system can generate double-wing, four-wing chaos or hyperchaos for different parameters and initial conditions. Through the analysis of Lyapunov exponent and other dynamics, we can see that the system has complex chaotic, hyperchaotic, and continuous chaotic. Other dynamical behaviors such as multi-stability and extreme multi-stability are found by comparing phase and bifurcation diagrams, and equilibrium point calculations. Finally, the chaotic behavior is successfully verified by circuit simulation.

关键词： Chaos automation Circuit simulation Buildings Memristors Bifurcation Encryption

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