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2nd International Conference on Artificial Intelligence and automation Control, AIAC 2024

作者： Chai, Yu Yang, Chen Dong, Huijuan Zhao, Jie Shardt, Yuri A. W. Ju, Bingfeng ZJU-Hangzhou Global Scientific and Technological Innovation Center Hangzhou China Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin China Technical University of Ilmenau Department of Automation Engineering Ilmenau Germany School of Mechanical Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9798331529147

Safeguarding high voltage direct current (HVDC) systems against direct current faults is an inherently demanding task. A promising solution to tackle this challenge is the application of piezoelectrically actuated fast mechanical switches (PA-FMS). However, mechanical resonance and random vibrations in the travel curves of P A-FMS have a substantial impact on their control accuracy. To tackle this challenge, a robust-tube model predictive control (RTMPC) strategy is developed. RTMPC drives the disturbed system state into the minimal robustly positively invariant (mRPI) set centered on the target and ensures that constraints are satisfied. The error feedback gain is calculated using the proposed linear matrix inequality (LMI) based method to minimize the effect of disturbances on the trajectory. An efficient outer approximation method is used to compute the mRPI set. Simulation results show that the critically damped travel curves have been achieved, along with a reduction of the external disturbances by 98%. © 2024 IEEE.

关键词： Predictive control systems

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A miniaturized mechanical antenna based on FEP/ THV unipolar electrets for extremely low frequency transmission

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Microsystems & Nanoengineering 2022年第3期8卷 223-233页

作者： Yong Cui Ming Wu Zhaoyang Li Xiao Song Chen Wang Haiven Yuan Zhi-Xin Yang Junwen Zhong School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Department of Electromechanical Engineering and Centre for Artificial Intelligence and Robotics University of MacaoMacaoSAR 999078China School of Cyber Science and Technology Beihang universityBeijing 100191China State Key Laboratory of Internet of Things for Smart City and Department of Electromechanical Engineering University of MacaoMacaoSAR 999078China

An electret-based mechanical antenna(EBMA),which can transmit extremely low frequency(ELF)electromagnetic signals,has the advantages of miniaturization and high transmitting efficiency,with great potential applications in air,underwater,and underground *** improve the charge density of the electret,which is a key factor in determining the radiation performance of an EBMA,this work proposes a fluorinated ethylene propylene/terpolymer of tetrafluoroethylene,hexafluoropropylene and vinylidene fluoride(FEP/THV)unipolar electret exhibiting negative polarity,reaching a total charge density up to-0.46 mC/m^(2) for each layer of *** transmission distances can be achieved in sea water,soil,and air using a 3-layer-FEP/THV-based EBMA with a compact volume of 5×10^(-4) m^(3).As an application demonstration,binary ASili-coded ELF information of"BUAA"is successfully transmitted with a power consumption<5W.

关键词： antenna propylene FEP

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RoboFold: A platform for Protein-folding Inspired Robot Swarms ∗ 5

RoboFold: A platform for Protein-folding Inspired Robot Swar...

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5th World Robot Conference Symposium on Advanced robotics and automation, WRC SARA 2023

作者： Zhang, Feng Gu, Yuping Yuan, Shuai Yang, Yongliang Shenyang Jianzhu University School of Electrical and Control Engineering Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110016 China Shenyang Jianzhu University School of Computer Science and Engineering School of Electrical and Control Engineering Liaoning Shenyang110168 China

ISBN: (纸本)9798350307320

Natural swarms have inspired various controlling algorithms for swarm robotics, while few of them were programmed in a similar way as the natural swarms. Defining a reliable programming method is still a daunting challenge in swarm robotics. In nature, the information of 3D protein structure is programmed in the sequence of amino acids of the protein. To mimic the programming method of protein folding, we present a platform for investigating protein-folding inspired programming method for robot swarms. This platform includes three parts: a vibration machine, protein-like robot sequences, and recording devices. The preliminary results presented here demonstrated the effectiveness of this platform and the feasibility of protein-folding inspired programming method for robot swarms. © 2023 IEEE.

关键词： Protein folding

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Research on Object Detection Methods in Low-Light Conditions 16th

Research on Object Detection Methods in Low-Light Conditio...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Wang, Feifan Chen, Xi’ai Wang, Xudong Ren, Weihong Tang, Yandong School of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Shenzhen518055 China

ISBN: (纸本)9789819964918

Low-light images are images taken in poorly illuminated environments. Such images suffer from colour distortion, loss of detail and blurriness, which seriously affects the detection accuracy of object detection tasks. In order to improve the accuracy of object detection in low-light images, we propose a low-light image object detection algorithm based on image enhancement. The algorithm is jointly trained on the input side of the YOLOv5 network in combination with an unsupervised low-light enhancement model. The training phase optimises the overall network with the loss of object detection so that the image enhancement results are more favourable for improving the object detection accuracy. In the feature extraction phase, we design a feature enhancement model based on an attention mechanism. Our algorithm is tested on the publicly available ExDark dataset and achieves a mean average precision (mAP) of 79.15%, which is a 4.25% improvement over the baseline. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Object detection

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Synthesis of Decoherence-Free Modes in Linear Quantum Passive Systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Miao, Zibo Pan, Yu Gao, Qing School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Guangdong Key Laboratory of Intelligent Morphing Mechanisms Shenzhen518055 China The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique. © 2024 IEEE.

关键词： Poles

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Carbon dioxide storage and cumulative oil production predictions in unconventional reservoirs applying optimized machine-learning models

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Petroleum Science 2025年第1期22卷 296-323页

作者： Shadfar Davoodi Hung Vo Thanh David A.Wood Mohammad Mehrad Sergey V.Muravyov Valeriy S.Rukavishnikov School of Earth Sciences&Engineering Tomsk Polytechnic UniversityLenin AvenueTomskRussia Laboratory for Computational Mechanics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh CityViet Nam Applied Science Research Center Applied Science Private UniversityAmmanJordan DWA Energy Limited LincolnUK Division for Automation&Robotics Tomsk Polytechnic UniversityLenin AvenueTomskRussia

To achieve carbon dioxide(CO_(2))storage through enhanced oil recovery,accurate forecasting of CO_(2) subsurface storage and cumulative oil production is *** study develops hybrid predictive models for the determination of CO_(2) storage mass and cumulative oil production in unconventional *** does so with two multi-layer perceptron neural networks(MLPNN)and a least-squares support vector machine(LSSVM),hybridized with grey wolf optimization(GWO)and/or particle swarm optimization(PSO).Large,simulated datasets were divided into training(70%)and testing(30%)groups,with normalization applied to both *** distance identifies/eliminates outliers in the training subset only.A non-dominated sorting genetic algorithm(NSGA-II)combined with LSSVM selected seven influential features from the nine available input parameters:reservoir depth,porosity,permeability,thickness,bottom-hole pressure,area,CO_(2) injection rate,residual oil saturation to gas flooding,and residual oil saturation to water *** models were developed and tested,with performance evaluated with an overfitting index(OFI),scoring analysis,and partial dependence plots(PDP),during training and independent testing to enhance model focus and *** LSSVM-GWO model generated the lowest root mean square error(RMSE)values(0.4052 MMT for CO_(2) storage and 9.7392 MMbbl for cumulative oil production)in the training *** trained model also exhibited excellent generalization and minimal overfitting when applied to the testing group(RMSE of 0.6224 MMT for CO_(2) storage and 12.5143 MMbbl for cumulative oil production).PDP analysis revealed that the input features“area”and“porosity”had the most influence on the LSSVM-GWO model's pre-diction *** paper presents a new hybrid modeling approach that achieves accurate forecasting of CO_(2) subsurface storage and cumulative oil *** also establishes a new standard for such forecasting,which can

关键词： Hybrid machine learning Least-squares support vector machine Grey wolf optimization Feature selection Carbon dioxide storage Enhanced oil recovery

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A Novel Gas Classification Method Based on The Improved GasNet 43

A Novel Gas Classification Method Based on The Improved GasN...

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43rd Chinese Control Conference, CCC 2024

作者： Qin, Xiaolin Cheng, Lei Tao, Xiang Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan430081 China Wuhan University of Science and Technology Institute of Robotics and Intelligent Systems Wuhan430081 China Wuhan University of Science and Technology School of Information Science and Engineering Wuhan430081 China

ISBN: (纸本)9789887581581

Accurately and promptly identifying harmful gases in the environment can effectively prevent many accidents. Most existing pattern recognition methods are focused on addressing gas classification problems in static scenarios, but the real world is a dynamic and changing environment. Therefore, researching gas classification in continuous learning scenarios will better meet the needs of suddenly emerging gas classification tasks in real-world environments. To address this issue, an incremental learning model was introduced into gas classification, and an improved deep convolutional network was proposed for gas image feature extraction. The proposed model and other baseline methods experimented on an open-source gas dataset. The proposed model reduces knowledge loss due to catastrophic forgetting and effectively classifies the 10 gas samples in the dataset in continuous learning scenarios compared to non-incremental methods. It outperforms other baseline incremental methods by optimizing the network's shortcut connections, making the feature extraction network easier to train and improving gas classification performance. In dynamic learning scenarios, the proposed model achieved a classification accuracy of 86.30% for 10 gas samples. The experimental results demonstrate that the proposed method effectively mitigates catastrophic forgetting interference and completes gas classification tasks in continuous learning scenarios. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Contrastive Learning

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Fabricating AC/DC nanogenerators based on single ZnO nanowires by using a nanomanipulator in a scanning electron microscope

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Nanotechnology and Precision engineering 2024年第2期7卷 25-31页

作者： Mei Liu Mengfan He Aristide Djoulde Lingdi Kong Weilin Su Xin Bai Jinbo Chen Jinjun Rao Zhiming Wang Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and AutomationShanghai UniversityShanghai 200444China Guangdong Provincial Key Laboratory of Fuel Cell Technology School of Chemistry and Chemical EngineeringSouth China University of TechnologyGuangzhou 510641China

Single zinc oxide nanowires(ZnO NWs)are promising for nanogenerators because of their excellent semiconducting and piezoelectric properties,but characterizing the latter efficiently is *** reported here,an electrical breakdown strategy was used to construct single ZnO NWs with a specific *** the high operability of a nanomanipulator in a scanning electron microscope,ZnO-NW-based twoprobe and three-probe structures were constructed for fabricating AC/DC nanogenerators,*** a ZnO NW,an AC output of between−15.31 mV and 5.82 mV was achieved,while for a DC nanogenerator,an output of24.3 mV was ***,the three-probe structure’s output method was changed to verify the distribution of piezoelectric charges when a single ZnO NW is bent by a probe,and DC outputs of different amplitudes were *** study provides a low-cost,highly convenient,and operational method for studying the AC/DC output characteristics of single NWs,which is beneficial for the further development of nanogenerators.

关键词： Zinc oxide nanowire Piezoelectric properties Nanomanipulator SEM AC/DC nanogenerators

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Kinetostatic Model of Redundant Actuation Modes in a Lockable Variable Geometry Truss Manipulator Driven by Flexible Limbs 24th

Kinetostatic Model of Redundant Actuation Modes in a Lockabl...

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24th IFToMM China International Conference on Mechanism and Machine Science and engineering, IFToMM CCMMS 2024

作者： Zhao, Yinjun Xi, Fengfeng Hao, Guangbo Tian, Yingzhong Li, Long Wang, Jieyu School of Mechanical Engineering University of Shanghai for Science and Technology Shanghai China School of Mechatronic Engineering and Automation Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai China Department of Aerospace Engineering Toronto Metropolitan University TorontoON Canada School of Engineering and Architecture-Electrical and Electronic Engineering University College Cork Cork Ireland

ISBN: (纸本)9789819614639

Manipulators consisting of multiple large deformation limbs can flexibly change their shapes and separate actuation systems from mechanism body, making them particularly suitable for requirements of compact design space, and continuous and versatile deformation. However, the low structural stiffness restricts their practical applications. To enhance the stiffness, we have integrated lockable variable geometry truss (LVGT) supports within the manipulator design. Depending on the number of locked branches within the LVGT, the active flexible limbs may exhibit redundant actuation modes, meaning that the number of working actuators exceeds the DOF of the internal LVGT. The redundant actuation modes, while beneficial for enabling heavier load manipulation, poses challenges in mechanical analysis, necessitating a comprehensive consideration of factors such as motion constraints from rigid joints, nonlinear coupling deformations in the flexible limbs, and control strategies for the redundant actuators. In this paper, we construct a mechanical analysis framework tailored for such operating modes. This framework enables the kinetostatic analyses under the consideration of distributing redundant actuation forces. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Geometry

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Microhardness and Wear Rate Analysis on Laser Cladded Composites of AZ91D Alloy with SiC by Grey Technique

Microhardness and Wear Rate Analysis on Laser Cladded Compos...

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International Conference on Mechanical engineering: Researches and Evolutionary Challenges, ICMech-REC 2023

作者： Karthick, L. Loganathan, Ganesh Babu Jagadish, C.A. Somasundaram, B. Kandavalli, Sumanth Ratna Chithambaranathan, P. Department of Mechanical Engineering Hindusthan College of Engineering and Technology Coimbatore641032 India Department of Robotics and Automation Rajalakshmi Engineering College Chennai602105 India School of Mechanical Engineering REVA University Bengaluru India Department of Mechanical Engineering Tandon School of Engineering New York University 6 Metro Tech Center BrooklynNY11201 United States Department of Mechanical Engineering Rajalakshmi Engineering College Thandalam Chennai602105 India

ISBN: (纸本)9789819722488

Owing to increments in heavy vehicles for transporting the materials and reducing the vehicle weight, magnesium alloys play the mandatory role in various fabricating industries. The Mg alloy alone does not satisfy their necessities without adding the strengthening particles;therefore, this investigation stated the silicon carbide (SiC) was the reinforcing into AZ91D Mg alloy to compose the coating metal matrix composites through the laser cladding process. This method is unique when appropriated processing parameters are chosen and compared to laser melting process;laser cladding is the significant one. The laser cladding processing parameters are scanning speed (3–5 m/s), SiC proportions (10–30%) and laser output power (0.6–0.8 kW), respectively. Then the composed coating AZ91D Mg alloy with SiC specimen is accounted for experimentation of microhardness and wear rates. The microhardness and wear rates are improved at increasing of weight percentage from 20 to 30%, maximum of scanning speed at 5 m/s and 0.7 kW of laser output power parameters. The grey relational multi-task optimization method was utilized to recognize the single responses from various laser cladding processing parameters. Finally, the SEM with worn surfaces was taken on the optimal specimen composite. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Silicon carbide

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