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Automatic Control of Magnetic Helical Microrobots Docking with Target Objects in Liquid Environments

Journal of Bionic Engineering 2025年第2期22卷 574-584页

作者： Fu Zhao Haoran Rong Lefeng Wang State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin150080China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of EducationHarbin University of Science and TechnologyHarbin150080China

Bio-inspired magnetic helical microrobots have great potential for biomedical and micromanipulation applications. Precise interaction with objects in liquid environments is an important prerequisite and challenge for helical microrobots to perform various tasks. In this study, an automatic control method is proposed to realize the axial docking of helical microrobots with arbitrarily placed cylindrical objects in liquid environments. The docking process is divided into ascent, approach, alignment, and insertion stages. First, a 3D docking path is planned according to the positions and orientations of the microrobot and the target object. Second, a steering-based 3D path-following controller guides the helical microrobot to rise away from the container bottom and approach the target along the path. Third, based on path design with gravity compensation and steering output limits, alignment of position and orientation can be accomplished simultaneously. Finally, the helical microrobot completes the docking under the rotating magnetic field along the target orientation. Experiments verified the automatic docking of the helical microrobot with static targets, including connecting with micro-shafts and inserting into micro-tubes. The object grasping of a reconfigurable helical microrobot aided by 3D automatic docking was also demonstrated. This method enables precise docking of helical microrobots with objects, which might be used for capture and sampling, in vivo navigation control, and functional assembly of microrobots.

关键词： Magnetic actuation Helical microrobots Visual servo Motion control Docking

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Characteristic model-based control of aerial manipulator for improved interaction stability

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Science China(Technological Sciences) 2025年第4期68卷 166-178页

作者： Bingkai XIU Zhan LI Yipeng YANG Huijun GAO Research Institute of Intelligent Control and Systems Harbin Institute of TechnologyHarbin150001China State Key Laboratory of Robotics and Systems(HIT) Harbin Institute of TechnologyHarbin150001China

Maintaining contact stability is crucial when the aerial manipulator interacts with the surrounding environment. In this paper, a novel output feedback framework based on a characteristic model is proposed to improve the contact stability of the aerial manipulator. First, only position measurements of the aerial manipulator are introduced to design the practical finite-time command filter-based force observer. Second, an attitude control architecture including characteristic modeling and controller design is presented. In the modeling part, input-output data is utilized to build the characteristic model with fewer parameters and a simpler structure than the traditional dynamic model. Different from conventional control methods, fewer feedback values,namely only angle information, are required for designing the controller in the controller part. In addition, the convergence of force estimation and the stability of the attitude control system are proved by the Lyapunov analysis. Numerical simulation comparisons are conducted to validate the effectiveness of the attitude controller and force observer. The comparative results demonstrate that the tracking error of x and θ channels decreases at least 10.62% and 10.53% under disturbances and the force estimation precision increases at least 45.19% in the different environmental stiffness. Finally, physical flight experiments are conducted to validate the effectiveness of the proposed framework by a self-built aerial manipulator platform.

关键词： aerial manipulator interaction stability contact force observer characteristic model

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Deep Reinforcement Learning-based Multi-Objective Scheduling for Distributed Heterogeneous Hybrid Flow Shops with Blocking Constraints

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Engineering 2025年第3期46卷 278-291页

作者： Xueyan Sun Weiming Shen Jiaxin Fan Birgit Vogel-Heuser Fandi Bi Chunjiang Zhang State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Institute of Automation and Information Systems Technical University of MunichGarching 85748Germany

This paper investigates a distributed heterogeneous hybrid blocking flow-shop scheduling problem(DHHBFSP)designed to minimize the total tardiness and total energy consumption simultaneously,and proposes an improved proximal policy optimization(IPPO)method to make real-time decisions for the DHHBFSP.A multi-objective Markov decision process is modeled for the DHHBFSP,where the reward function is represented by a vector with dynamic weights instead of the common objectiverelated scalar value.A factory agent(FA)is formulated for each factory to select unscheduled jobs and is trained by the proposed IPPO to improve the decision *** FAs work asynchronously to allocate jobs that arrive randomly at the shop.A two-stage training strategy is introduced in the IPPO,which learns from both single-and dual-policy data for better data *** proposed IPPO is tested on randomly generated instances and compared with variants of the basic proximal policy optimization(PPO),dispatch rules,multi-objective metaheuristics,and multi-agent reinforcement learning *** experimental results suggest that the proposed strategies offer significant improvements to the basic PPO,and the proposed IPPO outperforms the state-of-the-art scheduling methods in both convergence and solution quality.

关键词： Multi-objective Markov decision process Multi-agent deep reinforcement learning Proximal policy optimization Distributed hybrid flow-shop scheduling Blocking constraints

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Some research works in the state key laboratory of intelligent technology and systems

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Frontiers of Electrical and Electronic Engineering in China 2012年第2期7卷 197-199页

作者： Jun ZHU Bo ZHANG State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and TechnologyDepartment of Computer Science and TechnologyTsinghua UniversityBeijing 100084China

This special issue is organized to introduce the research works that have being conducted in the state key laboratory of intelligent technology and systems （LITS）, a state key lab located in Tsinghua University. However, due to space limit, our introduction is certainly not exhaustive. We will use a few sample papers from various research groups to organize this issue.

关键词： the state key laboratory intelligent technology and systems

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Beyond Performance of Learning Control Subject to Uncertainties and Noise: A Frequency-Domain Approach Applied to Wafer Stages

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 198-214页

作者： Fazhi Song Ning Cui Shuaiqi Chen Kai Zhang Yang Liu Xinkai Chen Jiubin Tan IEEE the Center of Ultra-precision Optoelectronic Instrument Engineering Harbin Institute of Technology the Key Laboratory of Ultra-Precision Intelligent Instrumentation Ministry of Industry and Information Technology the State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangdong University of Technology the Center of Ultraprecision Optoelectronic Instrument Engineering Harbin Institute of Technology the Key Laboratory of UltraPrecision Intelligent Instrumentation Ministry of Industry and Information Technology the Department of Electronic and Information Systems Shibaura Institute of Technology

The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the accuracy in terms of nanometers. This demanding requirement witnesses a widespread application of iterative learning control(ILC), given the repetitive nature of wafer scanning. ILC enables substantial performance improvement by using past measurement data in combination with the system model knowledge. However, challenges arise in cases where the data is contaminated by the stochastic noise, or when the system model exhibits significant uncertainties, constraining the achievable performance. In response to this issue, an extended state observer(ESO) based adaptive ILC approach is proposed in the frequency *** being model-based, it utilizes only a rough system model and then compensates for the resulting model uncertainties using an ESO, thereby achieving high robustness against uncertainties with minimal modeling effort. Additionally, an adaptive learning law is developed to mitigate the limited performance in the presence of stochastic noise, yielding high convergence accuracy yet without compromising convergence speed. Simulation and experimental comparisons with existing model-based and data-driven inversion-based ILC validate the effectiveness as well as the superiority of the proposed method.

关键词： Extended state observer learning control model uncertainties motion control stochastic noise

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An optical carbon nanotube fibre probe for measurement of nano structures with large aspect ratio

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Nano Research 2025年第3期18卷 436-443页

作者： Weihao Tao Shuhao Zhao Hanjin Dong Ze Zhang Peirui Ji Shenghan Qin Wenbo Hu Jinlong Zhu Renjie Zhou Shuming Yang State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049China State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Biomedical Engineering The Chinese University of Hong KongHong KongChina

With the development of imaging and measurement technologies,scanning near-field optical microscopy(SNOM)has achieved high signal-to-noise *** resolution of a fibre probe-based SNOM system is capable of reaching 10 ***,SNOM applications are presently constrained to the measurement of near-field optical information to relatively straightforward structures,including quantum dots,carbon nanotubes,graphene,and so *** geometry of conventional fibre probes,with tips at an angle of 30°-60°,presents a challenge for accurately imaging complex surface *** paper proposes a carbon nanotube composite fibre probe(CNT-FP)with a large aspect *** key point is that a carbon nanotube bundle is composited at the tip of conventional surface plasmon polaritons fibre probes(SPPs-FP),which are the fibre probes coated with gold film to excite the *** coupling,propagation,and focusing effects of SPPs on the carbon nanotube bundle are ***-FPs have been fabricated and applied to measure a grating with the depth of 400 nm and the width of 400 *** experimental results show that the measurement accuracy and imaging quality of CNT-FP are nearly one order of magnitude higher than that of conventional SPPs-FP,as evidenced by evaluation criteria such as line roughness and volatility ***,it achieves an optical resolution of 72.1 nm in the measurements of a nano structure with large aspect *** provides an effective solution of measuring structures with larger aspect ratios.

关键词： carbon nanotubes fibre optic probes surface plasmon polaritons nano-focusing large aspect ratio

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DistFlow Safe Reinforcement Learning Algorithm for Voltage Magnitude Regulation in Distribution Networks

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Journal of Modern Power systems and Clean Energy 2025年第1期13卷 300-311页

作者： Shengren Hou Aihui Fu Edgar Mauricio Salazar Duque Peter Palensky Qixin Chen Pedro P.Vergara Intelligent Electrical Power Grids(IEPG)Group Delft University of TechnologyDelft 2628CDThe Netherlands Electrical Energy Systems(EES)Group Eindhoven University of TechnologyEindhovenThe Netherlands State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

The integration of distributed energy resources(DERs)has escalated the challenge of voltage magnitude regulation in distribution ***-based approaches,which rely on complex sequential mathematical formulations,cannot meet the real-time *** reinforcement learning(DRL)offers an alternative by utilizing offline training with distribution network simulators and then executing online without ***,DRL algorithms fail to enforce voltage magnitude constraints during training and testing,potentially leading to serious operational *** tackle these challenges,we introduce a novel safe-guaranteed reinforcement learning algorithm,the Dist Flow safe reinforcement learning(DF-SRL),designed specifically for real-time voltage magnitude regulation in distribution *** DF-SRL algorithm incorporates a Dist Flow linearization to construct an expert-knowledge-based safety ***,the DF-SRL algorithm overlays this safety layer on top of the agent policy,recalibrating unsafe actions to safe domains through a quadratic programming *** results show the DF-SRL algorithm consistently ensures voltage magnitude constraints during training and real-time operation(test)phases,achieving faster convergence and higher performance,which differentiates it apart from(safe)DRL benchmark algorithms.

关键词： Voltage regulation distribution network safe reinforcement learning energy management

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Fabrication of bamboo-inspired continuous carbon fiber-reinforced SiC composites via dual-material thermally assisted extrusion-based 3D printing

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材料科学技术（英文版） 2025年第5期208卷 92-103页

作者： Sai Li Haitian Zhang Zhongliang Lu Fusheng Cao Ziyao Wang Yan Liu Xiaohui Zhu Shuai Ning Kai Miao Shaoyu Qiu Dichen Li State Key Laboratory for Manufacturing Systems Engineering School of Mechanical EngineeringXi'an Jiaotong UniversityXi'an 710049China State Key Laboratory for Manufacturing Systems Engineering School of Mechanical EngineeringXi'an Jiaotong UniversityXi'an 710049China School of Intelligent Manufacturing Modern Industry Xinjiang UniversityUrumqi 830046China Science and Technology on Reactor Fuel and Materials Laboratory Nuclear Power Institute of ChinaChengdu 610213China

Ceramic matrix composites(CMCs)structural components encounter the dual challenges of severe mechanical conditions and complex electromagnetic environments due to the increasing demand for stealth technology in aerospace *** address various functional requirements,this study integrates a biomimetic strategy inspired by gradient bamboo vascular bundles with a novel dual-material 3D print-ing *** distinct bamboo-inspired structural configurations Cf/SiC composites are designed and manufactured,and the effects of these different structural configurations on the CVI process are *** method is utilized to characterize the relationship between interface bonding strength and mechanical *** results reveal that the maximum flexural strength and fracture toughness reach 108.6±5.2 MPa and 16.45±1.52 MPa m1/2,respectively,attributed to the enhanced crack propagation resistance and path caused by the weak fiber-matrix ***,the bio-inspired configuration enhances the dielectric loss and conductivity loss,exhibiting a minimum reflection loss of-24.3 dB with the effective absorption band of 3.89 *** work introduces an innovative biomimetic strategy and 3D printing method for continuous fiber-reinforced ceramic composites,expanding the ap-plication of 3D printing technology in the field of CMCs.

关键词： 3D printing Cf/SiC composites Mechanical properties Electromagnetic wave absorption

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High-energy-density lithium manganese iron phosphate for lithium-ion batteries:Progresses,challenges,and prospects

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Journal of Energy Chemistry 2025年第1期100卷 1-17页

作者： Bokun Zhang Xiaoyun Wang Shuai Wang Yan Li Libo Chen Handong Jiao Zhijing Yu Jiguo Tu State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing 100083China Research Institute for Intelligent Wearable Systems The Hong Kong Polytechnic University Hong Kong 9977China Institute of Advanced Structure Technology Beijing Institute of TechnologyBeijing 100081China

The soaring demand for smart portable electronics and electric vehicles is propelling the advancements in high-energy–density lithium-ion *** manganese iron phosphate(LiMn_(x)Fe_(1-x)PO_(4))has garnered significant attention as a promising positive electrode material for lithium-ion batteries due to its advantages of low cost,high safety,long cycle life,high voltage,good high-temperature performance,and high energy *** LiMn_(x)Fe_(1-x)PO_(4)has made significant breakthroughs in the past few decades,there are still facing great challenges in poor electronic conductivity and Li-ion diffusion,manganese dissolution affecting battery cycling performance,as well as low tap *** review systematically summarizes the reaction mechanisms,various synthesis methods,and electrochemical properties of LiMn_(x)Fe_(1-x)PO_(4)to analyze reaction processes accurately and guide material ***,the main challenges currently faced are concluded,and the corresponding various modification strategies are discussed to enhance the reaction kinetics and electrochemical performance of LiMn_(x)Fe_(1-x)PO_(4),including multi-scale particle regulation,heteroatom doping,surface coating,as well as microscopic morphology ***,in view of the current research challenges faced by intrinsic reaction processes,kinetics,and energy storage applications,the promising research directions are *** importantly,it is expected to provide key insights into the development of high-performance and stable LiMn_(x)Fe_(1-x)PO_(4)materials,to achieve practical energy storage requirements.

关键词： Lithiummanganese iron phosphate High energydensity Lithium-ionbatteries Reactionmechanism Tap density

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Enhancing rheology and mechanical properties of DLP 3D-printed Si_(3)N_(4)materials via composition optimization and gas-pressure sintering

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International Journal of Minerals,Metallurgy and Materials 2025年第5期32卷 1220-1233页

作者： Qing Qin Gang Xiong Lin Han Yujuan Zhang Zhen Shen Changchun Ge Institute of Powder Metallurgy and Advanced Ceramics School of Materials Science and EngineeringUniversity of Science and Technology BeijingBeijing 100083China State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and TechnologyInstitute of AutomationChinese Academy of SciencesBeijing 100190China

Digital light processing(DLP)is a crucial additive manufacturing(AM)technique for producing high-precision ceramic *** study aims to optimize the formulation of Si_(3)N_(4)slurry to enhance both its performance and manufacturability in the DLP process,and investigate key factors such as particle size distribution,photopolymer resin monomer ratios,and dispersant types to im-prove the slurry’s rheological *** these optimizations,a photosensitive Si_(3)N_(4)slurry with 50vol%solid content was de-veloped,exhibiting excellent stability,and low viscosity(2.48 Pa·s at a shear rate of 12.8 s^(-1)).The effects of gas-pressure sintering on the material’s phase composition,microstructure,and mechanical properties were further explored,revealing that this technique significantly increases the flexural strength of the green sample from(109±10.24)to(618±42.15)*** sintered ceramics exhibited high hard-ness((16.59±0.05)GPa)and improved fracture toughness((4.45±0.03)MPa·m^(1/2)).Crack trajectory analysis revealed that crack deflec-tion,crack bridging,and the pull-out of rod-likeβ-Si_(3)N_(4)grains,are the main toughening mechanisms,which could effectively mitigate crack *** these mechanisms,crack deflection and bridging were particularly influential,significantly enhancing the frac-ture toughness of the Si_(3)N_(4)***,this research highlights how monomer formulation and gas-pressure sintering strengthen the performance of Si_(3)N_(4)slurry in the DLP three-dimensional printing *** work is expected to provide new insights for fabricat-ing complex Si_(3)N_(4)ceramic components with superior mechanical properties.

关键词： additive manufacturing Si_(3)N_(4)slurry low viscosity pressure sintering

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