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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Peng, Pai Liu, Qi Li, Bin Peng, Wei Wang, Xinjie Wang, Jinyuan Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China

ISBN: (纸本)9798350320831

Industrial robots are widely used in industrial production because of their high work efficiency and high flexibility, but their low tracking accuracy makes them unable to be applied on a large scale in high-precision manufacturing. Considering the modeling error of robot, the problem of low tracking accuracy should be solved by combining model-based methods and data-based methods. Thus, a model-data compound approach is proposed for compensating robot tracking error. This method comprehensively considers two error compensation methods of model-driven and data-driven, which constructed the input matrix by using the model-based information and the data-based information. The former includes the desired position, velocity, acceleration, torque and friction torque;and the latter includes the actual torque. For the purpose of predicting the correlation between the joint error and the historical joint motion state, the historical information of the joint motion is also added in the input matrix for improving the error prediction accuracy. Then, a convolutional neural network prediction model is constructed for predicting and compensating the tracking error of each actuated joint. The experimental results show that the proposed method has good prediction accuracy and compensation effect. Compared to joint control without using the proposed method, the root mean square of joint tracking errors was reduced by up to more than 69%. © 2023 IEEE.

关键词： Error compensation

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Structure design and kinematics modeling of a new continuum parallel robot 20

Structure design and kinematics modeling of a new continuum ...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Wang, Xinjie Li, Bin Ma, Yue Peng, Wei Peng, Pai Wang, Jinyuan Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China

ISBN: (纸本)9798350320831

Compared with the traditional rigid robots, the continuum robot has been widely studied because of its advantages of compact design and flexible motion. The design of continuum parallel robots are similar to that of the traditional rigid-link parallel robot, and the precision, stability and strength characteristics of rigid-link parallel robots are combined with the compactness and flexibility characteristics of continuum robots. In recent research advances, it is well appreciated to suggest that the use of parallel continuum robots with passive supports is supported by elastic rods. The passive branch undergoes deformation along its entire length and uses complex formulas to describe its shape and kinematics. According to different methods, this paper proposes the design of a parallel robot dual continuum translation passive branch chain. This continuum joint will assume a constant curvature bend and use this assumption for kinematic modeling. Since the continuum joint is a flexible joint that utilizes the characteristics of new materials, it uses material deformation to replace the motion pair, which successfully realizes that the passive branch joint can replace the universal joint and the ball hinge in the parallel robot, and the joint can be bent more than 90 0 to achieve a larger range of workspace. Each passive branch of the new continuum robot is a continuum structure composed of two mutually coupled flexible hinge joints, and the translational motion of the end effector is inherently realized by using its material properties. The paper includes a new mechanism description and kinematics modeling. © 2023 IEEE.

关键词： Kinematics

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Global Convergence Guarantees of (A)GIST for a Family of Nonconvex Sparse Learning Problems

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IEEE Transactions on Cybernetics 2022年第5期52卷 3276-3288页

作者： Zhang, Hengmin Qian, Feng Shang, Fanhua Du, Wenli Qian, Jianjun Yang, Jian East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education School of Information Science and Engineering Shanghai200237 China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China Xidian University Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education School of Artificial Intelligence Xi'an710071 China Peng Cheng Laboratory Shenzhen518066 China Nanjing University of Science and Technology Pca Laboratory Key Lab. of Intelligent Percept. and Syst. for High-Dimensional Information of Ministry of Education Nanjing210094 China Nanjing University of Science and Technology Jiangsu Key Laboratory of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing210094 China

In recent years, most of the studies have shown that the generalized iterated shrinkage thresholdings (GISTs) have become the commonly used first-order optimization algorithms in sparse learning problems. The nonconvex relaxations of the \ell _{0} -norm usually achieve better performance than the convex case (e.g., \ell _{1} -norm) since the former can achieve a nearly unbiased solver. To increase the calculation efficiency, this work further provides an accelerated GIST version, that is, AGIST, through the extrapolation-based acceleration technique, which can contribute to reduce the number of iterations when solving a family of nonconvex sparse learning problems. Besides, we present the algorithmic analysis, including both local and global convergence guarantees, as well as other intermediate results for the GIST and AGIST, denoted as (A)GIST, by virtue of the Kurdyka-Lojasiewica (KL) property and some milder assumptions. Numerical experiments on both synthetic data and real-world databases can demonstrate that the convergence results of objective function accord to the theoretical properties and nonconvex sparse learning methods can achieve superior performance over some convex ones. © 2013 IEEE.

关键词： Optimization

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An Improved Dual Neural Network Method Based on Levy Flight for Multi-Robot Cooperative Area Coverage Search in 3D Unknown Environments

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Zhang, Fangfang Wang, Yongqi Wang, Wenhao Xin, Jianbin Peng, Jinzhu Wang, Yaonan Zhengzhou University School of Electrical and Information Engineering Zhengzhou450001 China State Key Laboratory of Intelligent Agricultural Power Equipment Luoyang471039 China National Engineering Laboratory of Robot Visual Perception and Control Technology School of Robotics Hunan University Changsha410082 China

The research on multi-robot collaborative search in unknown 3D environments, based on bio-inspired neural networks, holds significant value and ***, challenges arise in 3D environments, including excessive turning and vertical movement, as well as the potential for collisions between robots. In response, we propose an improved Glasius Bio-Inspired Neural Network(GBNN) that mitigates decision conflicts among robots and considers the impact of turning and vertical movement on robot decision-making. Furthermore, to address the issue of robots getting trapped in local deadlocks during the search process, we present a dual neural network algorithm based on Levy flights. In the method Dual Glasius Bio-Inspired Neural Network based on Levy Flight(LF-DUAL-GBNN) proposed in this paper, robots obtain random target points through Levy flights and are then guided by a dual neural network to navigate to the vicinity of the target points, thus breaking free from local deadlock states. Finally, we conducted simulation experiments to validate the algorithm's effectiveness. © 2016 IEEE.

关键词： Microrobots

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Neural Network-Based Terminal Sliding Mode Controller Design for Manipulator Systems 1

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UNIfied Conference of International Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, International Conference on Maintenance engineering, IncoME-V 2023, International conference on the Efficiency and Performance engineering Network, TEPEN 2023

作者： Qu, Lufeng Fan, Qiming Kang, Yang Yang, Jun Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China School of Intelligent Manufacturing Tianjin Sino-German University of Applied Technology Tianjin300350 China School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9783031494130

ISBN: (纸本)9783031494123

In the context of nonlinear and uncertain manipulator systems, achieving fast and accurate desired trajectories for each joint of the manipulator is crucial. Our study aims to improve current control methods by combining sliding mode control and neural network techniques. Specifically, we leverage the neural networks’ approximation capabilities to estimate both the modeling error and external disturbance in our research. These estimates are then integrated into the synovial control as additional gains. This approach allows for the sliding mode controller’s switch gain to adapt to changing modeling error and external disturbance, thereby avoiding the vibration production typically associated with traditional sliding mode controllers. It can be observed from the simulation results that the combination of the proposed nonsingular terminal sliding mode controller and neural network achieves fast and precise tracking of desired trajectories. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Sliding mode control

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Dissipative State Estimation for Delayed Discrete-Time Memristive Neural Networks Under Dynamic Event-Triggered Mechanisms and Deception Attacks

Dissipative State Estimation for Delayed Discrete-Time Memri...

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2021 International Conference on Neuromorphic Computing, ICNC 2021

作者： Tao, Huimin Liu, Hongjian Zhu, Jiali Tan, Hailong School of Electrical Engineering Anhui Polytechnic University Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Wuhu China School of Mathematics-Physics and Finance Anhui Polytechnic University Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Wuhu China

ISBN: (纸本)9781665412872

In this paper, the state estimation problem for delayed discrete-time memristive neural networks subject to deception attacks is concerned. The main purpose is to design a state estimator such that the error dynamics of the state estimation is stochastically stable and strict dissipative. The randomness of deception attacks is described via a set of Bernoulli distributed white sequences with known conditional probabilities. In addition, in order to reduce unnecessary resource consumption in the communication channels, a dynamic event-triggering mechanism is introduced. By using the Lyapunov-Krasovskii functional and stochastic analysis method, sufficient conditions for stochastic stability and strict dissipation of the error system are acquired. On this basis, a co-design scheme of estimator parameters and the event-triggered matrix is proposed. Finally, the numerical simulation shows the effectiveness of the proposed state estimation scheme. © 2021 IEEE.

关键词： State estimation

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Virtual Sample Generation Methods and Application in Few-Shot Object Detection for Industrial Scenarios

Virtual Sample Generation Methods and Application in Few-Sho...

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Chinese Automation Congress (CAC)

作者： Xiuwen Tao Guoyang Wan Ming Jiang Jian Zhang Qianqian Wang Qin He Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Anhui Polytechnic University School of Electrical Engineering Anhui Polytechnic University Wuhu China

Due to the long-term relatively fixed state of industrial installations, the diversity of industrial data is low, with high repetitiveness and uneven distribution, which makes industrial few-shot object detection still challenging. Therefore, from the perspective of handling the dataset, this paper proposes a virtual sample generation method based on virtual reality. Firstly, by using a virtual engine, the target workpiece model is created to directly simulate the states of the workpieces captured by the visual system in various environments. Secondly, random algorithms are added and improved to simulate workpieces with different materials and degrees of wear, distributed in random positions with different poses and types in the visual system, thereby generating virtual samples containing workpieces. Finally, virtual samples are introduced for experimental testing in the target detection network. The proposed method is tested in both YOLOv5 and YOLOv7 and compared with datasets without virtual samples, resulting in an improvement of 3.06% and 2.23% in mAP values, respectively. The experimental results demonstrate that the proposed method effectively improves the issue of industrial small-sample object detection.

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Single-atom nanozymes with axial ligand-induced self-adaptive conformation in alkaline medium boost chemiluminescence

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Science China Chemistry 2023年第3期66卷 904-912页

作者： Zhen Luo Liliang Tian Hengjia Wang Zhichao Wu Xin Luo Xiaosi Wang Lei Jiao Xiaoqian Wei Ying Qin Lirong Zheng Liuyong Hu Wenling Gu Le Shi Chengzhou Zhu Key Laboratory of Pesticides and Chemical Biology of Ministry of Education International Joint Research Center for Intelligent Biosensing Technology and HealthCollege of ChemistryCentral China Normal UniversityWuhan 430079China State Key Laboratory of Electrical Insulation and Power Equipment Centre of Nanomaterials for Renewable EnergySchool of Electrical EngineeringXi’an Jiaotong UniversityXi’an 710049China Beijing Synchrotron Radiation Facility Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China Hubei Key Laboratory of Plasma Chemistry and Advanced Materials Hubei Engineering Technology Research Center of Optoelectronic and New Energy MaterialsWuhan Institute of TechnologyWuhan 430205China Fujian Shuikou Power Generation Group Corp. Fuzhou 350000China

Mimicking the structure of natural enzymes for designing advanced alternatives provides great opportunities to address the bottleneck of enzyme-involved chemiluminescence(CL). Herein, according to theoretical calculations, we found that an endogenous axial ligand of M-N-C single-atom nanozymes(SAzymes), originating from OH-spontaneously bonding to the metal center in an alkaline medium, can self-adaptively change its strength to facilitate intermediate steps. Furthermore, the lowest energy barrier of the rate-determining step and the strongest affinity and fastest electron transfer with luminol anion endow CoN-C with the highest peroxidase-like activity. Guided by the theoretical calculations, a series of M-N-C SAzymes(M=Fe, Co,Ni) were synthesized to boost CL, where Co-N-C SAzymes with superior catalytic activity and high selective generation of O_(2)·- were validated. As a proof-of-concept, Co-N-C SAzymes were employed for sensitive detection of acetylcholinesterase and organophosphorus pesticide.

关键词： single-atom nanozymes chemiluminescence hydrogen peroxide activation biosensing

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The effect of different gravity fields on mass transfer in the rat bone lacunar-canalicular system

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Medicine in Novel Technology and Devices 2023年第1期17卷 141-149页

作者： Hao Wang Jiaming Wang Kangning Li Lilan Gao Aiguo Wang Shuping Wei Linwei Lyu Chunqiu Zhang Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control National Demonstration Center for Experimental Mechanical and Electrical Engineering EducationSchool of Mechanical EngineeringTianjin University of TechnologyTianjin300384PR China Tianjin Academy of Traditional Chinese Medicine Affiliated Hosptial PR China

The bone lacunar-canalicular system(LCS)is an important microscopic infrastructure for signaling and solute transport in bone tissue,which guarantees normal physiological processes of the tissue,but the mass transfer laws in the LCS under different gravity fields have not yet been *** rats were injected intraperitoneally with different concentrations of sodium fluorescein tracer and subjected to mass transfer experiments in the LCS under normal gravity and *** fluorescence distribution in the osteon was observed using laser scanning confocal *** hypergravity environment was provided by a self-designed high-G loading *** fluorescence intensity of the Haversian canal in the osteon was the *** fluorescence intensity of lacunae farther away from the Haversian canal was lower,and the fitted curve was *** the increasing distance from the Haversian canal,the curve first rapidly decreased,and then the decreasing trend gradually became *** promoted mass transfer in the LCS,and the 10 G hypergravity showed varying degrees of fluorescence intensity in each layer of the osteon relative to normal gravity,with intensity enhancements in the range of 132.7–249.0%.The fluorescence intensity was also significantly increased when the tracer concentration was halved and the gravity field magnitude was increased to *** conclusion,hypergravity promoted the transport of solute molecules,nutrients,and signaling molecules within the *** effect of hypergravity on mass transfer in the LCS was greater than that of tracer *** may help to understand bone diseases from a mass transfer perspective.

关键词： Bone Lacunar-canalicular system Mass transfer Hypergravity

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A Fault Diagnosis Method for Molecular Pump Based on Dictionary Learning 2nd

A Fault Diagnosis Method for Molecular Pump Based on Diction...

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Conference Proceedings of 2022 2nd International Joint Conference on Energy, electrical and Power engineering

作者： Jia, Kai Jiang, Ming Zuo, Guizhong Zhang, Zuchao Hou, Jilei Yuan, Xiaolin Key Laboratory of Advanced Perception and Intelligence Control of High-end Equipment Anhui Polytechnic University Wuhu241000 China School of Electrical Engineering Anhui Polytechnic University Wuhu241000 China Institute of Plasma Physics Chinese Academy of Science Hefei230031 China

ISBN: (纸本)9789819943333

The molecular pump fault results in a vacuum leakage and lead to accidents in a fusion device. The fault diagnosis for molecular pump can provide an early warning and avoid a greater loss in a fusion device. This paper proposed an innovative fault diagnosis method for molecular pump based on dictionary learning. Firstly, discrete cosine transform (DCT) is used to perform noise reduction. Then, the k-singular value decomposition (K-SVD) is used to train an over-complete dictionary of normal state signal and decomposed other state signal on the dictionary of normal state signal. Finally, the orthogonal matching pursuit (OMP) is used to reconstruct the signal and compare the reconstructed signal with the original signal, the molecular pump fault diagnosis is realized by the sparse representation error. The superiority of the proposed method in molecular pump fault diagnosis are shown by the experimental results. Compared with the traditional method, this approach is 8.79% more accurate. Our analyses also indicate that the proposed method can be used in fault diagnosis of molecular pump for EAST. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Failure analysis

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