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A LESO Based Backstepping controller Considering Coal Seam Hardness for Rotary Speed in Coal Mine Tunnel Drilling Process

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Journal of systems Science & Complexity 2024年第5期37卷 1789-1808页

作者： CHEN Luefeng LIU Xiao WU Min LU Chengda PEDRYCZ Witold HIROTA Kaoru School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6R2G7Canada The Tokyo Institute of Technology Yokohama 226-8502Japan

In the process of coal mine drilling,controlling the rotary speed is important as it determines the efficiency and safety of *** this paper,a linear extended state observer(LESO)based backstepping controller for rotary speed is proposed,which can overcome the impact of changes in coal seam hardness on rotary ***,the influence of coal seam hardness on the drilling rig’s rotary system is considered for the first time,which is reflected in the numerical variation of load torque,and a dynamic model for the design of rotary speed controller is *** an LESO is designed to observe the load torque,and feedforward compensation is carried out to overcome the influence of coal seam *** on the model of the compensated system,a backstepping method is used to design a controller to achieve tracking control of the rotary ***,the effectiveness of the controller designed in this paper is demonstrated through simulation and field experiments,the steady-state error of the rotary speed in field is 1 r/min,and the overshoot is reduced to 5.8%.This greatly improves the stability and security,which is exactly what the drilling process requires.

关键词： Backstepping extended state observer hydraulic tunnel drilling machine rotary speed

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Mn-based MXene with high lithium-ion storage capacity

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Nano Research 2024年第5期17卷 4181-4191页

作者： Yanyan Wu Dongqing Liu Xiaonan Wang Usman Ghani Muhammad Asim Mushtaq Jinfeng Yang Huarui Sun Panagiotis Tsiakaras Xingke Cai School of Science and Ministry of Industry and Information Technology Key Laboratory of Micro-Nano Optoelectronic Information System Harbin Institute of Technology ShenzhenShenzhen 5180552 China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Institute for Advanced Study Shenzhen UniversityShenzhen 518060China College of Mechatronics and Control Engineering Shenzhen UniversityShenzhen 518060China Laboratory of Alternative Energy Conversion Systems Department of Mechanical EngineeringSchool of EngineeringUniversity of ThessalyPedion Areos 38834Greece

3d-transition metal(Fe,Co,Ni,and Mn)-based MXene materials have been predicted to demonstrate exceptional electrochemical performance because of their good electrical conductivity and the presence of metallic atoms with multiple charge ***,until now,there have been no reports on MXenes based on Fe,Co,Ni,and Mn,due to the lack of 3d-metal-layered ***,we successfully synthesized the first 3d-transition metal-based MXenes,Mn_(2)CT_(x) by exfoliating a layered precursor derived from the anti-perovskite bulk *** as-prepared Mn_(2)CT_(x) MXene nanosheets were employed as anode materials in lithium-ion batteries,which exhibited stable storage capacity of 764.7 mAh·g^(-1) at 0.5 C,placing its storage capacities at an upper-middle level compared with other reported MXene materials as well as other Mn-based anode ***,this study opens a new avenue for MXene research by synthesizing 3d-transition metal-based MXenes for electrochemical applications.

关键词： Mn_(3)GaC Mn_(2)CT_(x) MXenes lithium-ion battery anode materials negative fading capacity

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Research on workflow recognition for liver rupture repair surgery

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Mathematical Biosciences and engineering 2024年第2期21卷 1844-1856页

作者： Men, Yutao Zhao, Zixian Chen, Wei Wu, Hang Zhang, Guang Luo, Feng Yu, Ming Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Medical Support Technology Research Department Systems Engineering Institute Academy of Military Sciences People’s Liberation Army Tianjin300161 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

Liver rupture repair surgery serves as one tool to treat liver rupture, especially beneficial for cases of mild liver rupture hemorrhage. Liver rupture can catalyze critical conditions such as hemorrhage and shock. Surgical workflow recognition in liver rupture repair surgery videos presents a significant task aimed at reducing surgical mistakes and enhancing the quality of surgeries conducted by surgeons. A liver rupture repair simulation surgical dataset is proposed in this paper which consists of 45 videos collaboratively completed by nine surgeons. Furthermore, an end-to-end SA-RLNet, a self attention-based recurrent convolutional neural network, is introduced in this paper. The self-attention mechanism is used to automatically identify the importance of input features in various instances and associate the relationships between input features. The accuracy of the surgical phase classification of the SA-RLNet approach is 90.6%. The present study demonstrates that the SA-RLNet approach shows strong generalization capabilities on the dataset. SA-RLNet has proved to be advantageous in capturing subtle variations between surgical phases. The application of surgical workflow recognition has promising feasibility in liver rupture repair surgery. ©2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons.

关键词： Image classification

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The Journey/DAO/TAO of Embodied Intelligence: From Large Models to Foundation Intelligence and Parallel Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1313-1316页

作者： Tianyu Shen Jinlin Sun Shihan Kong Yutong Wang Juanjuan Li Xuan Li Fei-Yue Wang College of Information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China School of Electrical and Information Engineering Jiangsu UniversityZhenjiang 212013China State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Peng Cheng Laboratory Shenzhen 518000China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China IEEE

THE tremendous impact of large models represented by ChatGPT[1]-[3]makes it necessary to con-sider the practical applications of such models[4].However,for an artificial intelligence(AI)to truly evolve,it needs to possess a physical“body”to transition from the virtual world to the real world and evolve through interaction with the real *** this context,“embodied intelligence”has sparked a new wave of research and technology,leading AI beyond the digital realm into a new paradigm that can actively act and perceive in a physical environment through tangible entities such as robots and automated devices[5].

关键词： Intelligence DAO TAO

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Electrical Tracking,Erosion and Fire Retardancy Performance of Silicone Rubber Insulation Containing Aluminum Trihydrate,Graphene and Glass Fiber Additives

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CSEE Journal of Power and Energy systems 2023年第5期9卷 1918-1925页

作者： M.Tariq Nazir Arslan Khalid B.Toan Phung Arup K.Das Peter Cheetham Ashish Paramane Shakeel Akram Khoi Loon Wong School of Engineering RMIT UniversityMelbourneVIC 3000Australia. the Center for Advanced Power Systems(CAPS) Florida State UniversityFL 32310USA the Flame Security International Pty Limited Australia the School of Electrical Engineering and Telecommunications University of New South Wales SydneyNSW 2052Australia Department of Electrical Engineering National Institute of TechnologySilcharAssam 788010India the College of Electrical Engineering and Control Science Nanjing Tech UniversityNanjingJiangsu 211816China

Silicone rubber composite is a priority electrical insulating material used in high-voltage outdoor insulation *** electrical tracking/erosion and poor flame resistance performance of silicone rubber once ignited,substantially reduce its working *** paper attempts to investigate tracking/erosion performance of room temperature vulcanized(RTV)silicone rubber along with flame retardant parameters using aluminum trihydrate(ATH),graphene nanosheets(GN)and milled glass fiber(GF)*** inclined plane test(IPT)was performed in line with criteria defined in IEC 60587 using step-up tracking voltage method while flame retardancy is evaluated according to ASTM E 1354.0 using a cone *** suggest 30% of ATH assists in improving physical tracking/erosion resistance of pristine silicone elastomer rubber by impeding development of leakage current and a great reduction in maximum average temperatures on the surface of *** improvement in performance of RTV2 is achieved through introduction of 1%of GN and 5% of GF as seen in ***,30% of ATH reduces heat release rate and smoke production rate,and this trend is improved with the introduction of GN/***4 has pop up as the most promising silicone rubber composite with excellent electrical tracking,erosion,and flame resistance performance relative to its counterparts in this study.

关键词： Dry band arcing electrical tracking heat release rate leakage current silicone rubber smoke production rate

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Pixel-based Hole Quality Evaluation in Robot Drilling Manufacturing Process 22

Pixel-based Hole Quality Evaluation in Robot Drilling Manufa...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Niu, Chaoyue Chen, Bin Smith, Erica Bramley, Robert Crawforth, Pete Mahfouf, Mahdi Kadirkamanathan, Visakan The Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom The Advanced Manufacturing Research Centre with Boeing University of Sheffield RotherhamS60 5TZ United Kingdom

ISBN: (纸本)9798331527471

Aircraft assembly entails drilling numerous holes, often in multi-material stacks, then joining parts with fasteners fitted through the holes. There are stringent quality requirements on the holes, and assessment of hole quality is crucial to ensuring the integrity of the joints. Carbon fibre reinforced polymer (CFRP) is a commonly used material in aircraft structures due to its desirable properties. However, it is susceptible to defects not associated with metals, such as delamination and uncut fibres. While there have been multiple metrics for assessment of these defects proposed in literature, relatively few attempts to consolidate them have been seen. Furthermore, common measurement methods used for assessing these defects (e.g. 3D-microscopy) are well established, but can be time-consuming;manual interrogation of raw inspection data can also be highly subjective. To address these challenges, this paper proposes a set of combined metrics along with an automatic image processing framework for fast assessment of delamination and uncut fibre defects. The combined metric for the delamination region is aggregated from across six factors and uncut fibre uniform metrics from across five factors. The image processing framework receives grayscale images as inputs, taken from an optical coordinate measuring machine, and outputs the combined metrics along with eleven separate metrics. Experimental results, using a preexisting dataset from twenty-four holes on two workpieces from a real robotic drilling operation, are given to demonstrate the effectiveness of the proposed combined metrics and the corresponding image processing framework. © 2024 IEEE.

关键词： Carbon fiber reinforced plastics

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Neural-Network-Based control for Discrete-Time Nonlinear systems with Input Saturation Under Stochastic Communication Protocol

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IEEE/CAA Journal of Automatica Sinica 2021年第4期8卷 766-778页

作者： Xueli Wang Derui Ding Hongli Dong Xian-Ming Zhang Department of Control Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Software and Electrical Engineering Swinburne University of TechnologyMelbourne 3122VictoriaAustralia Institute of Complex Systems and Advanced Control Northeast Petroleum UniversityDaqing 163318China

In this paper,an adaptive dynamic programming(ADP)strategy is investigated for discrete-time nonlinear systems with unknown nonlinear dynamics subject to input *** save the communication resources between the controller and the actuators,stochastic communication protocols(SCPs)are adopted to schedule the control signal,and therefore the closed-loop system is essentially a protocol-induced switching system.A neural network(NN)-based identifier with a robust term is exploited for approximating the unknown nonlinear system,and a set of switch-based updating rules with an additional tunable parameter of NN weights are developed with the help of the gradient *** virtue of a novel Lyapunov function,a sufficient condition is proposed to achieve the stability of both system identification errors and the update dynamics of NN ***,a value iterative ADP algorithm in an offline way is proposed to solve the optimal control of protocol-induced switching systems with saturation constraints,and the convergence is profoundly discussed in light of mathematical ***,an actor-critic NN scheme is developed to approximate the control law and the proposed performance index function in the framework of ADP,and the stability of the closed-loop system is analyzed in view of the Lyapunov ***,the numerical simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Adaptive dynamic programming(ADP) constrained inputs neural network(NN) stochastic communication protocols(SCPs) suboptimal control

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Visual SLAM in Dynamic Environments using Multi-lens Omnidirectional Camera 4

Visual SLAM in Dynamic Environments using Multi-lens Omnidir...

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4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022

作者： Yamasaki, Shoya Matsushima, Kousuke National Insutitute of Technology Kurume College Advanced Engineering School Fukuoka Japan National Insutitute of Technology Kurume College Department of Control and Information Systems Engineering Fukuoka Japan

ISBN: (纸本)9781665419048

Many studies relate to Visual SLAM (Simultaneous Localization and Mapping) systems have been conducted for automatic driving and assisted driving systems. In this paper, we propose the Visual SLAM system combining multi-lens omnidirectional camera and object recognition. The proposed method can reduce some noises caused by moving objects, such as vehicle, pedestrian, bicycle, and so on, in the road environment. We also propose a robust SLAM system against tracking loss by improving the tracking thread. Since a multi-lens omnidirectional camera system can view not only the front but also the left and right sides of the scene, it is possible to obtain effective feature points even in scenes with little texture. Therefore, it provides better SLAM results than monocular camera systems. © 2022 IEEE.

关键词： Textures

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Image Classification for advanced Driving Assistant System in Electric Wheelchair 4

Image Classification for Advanced Driving Assistant System i...

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4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022

作者： Yamawaki, Masahiro Matsushima, Kousuke Kurume College National Institute of Technology Advanced Engineering School Fukuoka Japan Kurume College National Institute of Technology Department of Control and Information Systems Engineering Fukuoka Japan

ISBN: (纸本)9781665419048

Demands for welfare equipment such as electric wheelchairs are increasing in Japan, because of traffic accidents by the elderly. In the field of automobiles, the safety driving supports have been researched in many divergences. However, in the field of electric wheelchairs, not advanced too much. In this study, we propose a method of machine learning by Self-Supervised Learning (SSL) and a method of image classification according to the results, using actual sidewalk images as a machine learning dataset, to advanced Driving Assistant System (ADAS) of electric wheelchairs. © 2022 IEEE.

关键词： Supervised learning

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Automatic Pavement Type Recognition based on Mobile Deep Learning 4

Automatic Pavement Type Recognition based on Mobile Deep Lea...

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4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022

作者： Murasaki, Reiya Matsushima, Kousuke National Institute of Technology Kurume College Advanced Engineering School Fukuoka Japan National Institute of Technology Kurume College Department of Control and Information Systems Engineering Fukuoka Japan

ISBN: (纸本)9781665419048

Pavement deformation detection is an essential task in order to maintain driving safety. In recent years, convolutional neural networks (CNN), one of the machine learning methods, have been widely studied for pavement condition detection. In this paper, we propose a method that can achieve optimal pavement deformation detection in each region, assuming a mobile terminal. © 2022 IEEE.

关键词： Pavements

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