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Control Policy Learning Design for Vehicle Urban Positioning via BeiDou Navigation

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Journal of systems Science & Complexity 2024年第1期37卷 114-135页

作者： QIN Yahang ZHANG Chengye CHEN Ci XIE Shengli LEWIS Frank L School of Automation Guangdong University of TechnologyGuangzhou 510006China guangdong key laboratory of IoT Information Technology Guangzhou 510006China. Center for intelligent Batch Manufacturing Based on IoT Technology key laboratory of intelligent Detection and The Internet of Things in Manufacturing Ministry of EducationGuangzhou 510006China guangdong-HongKong-Macao Joint laboratory for Smart Discrete Manufacturing Guangzhou 510006China key laboratory of intelligent Information Processing and system Integration of IoT Ministry of EducationGuangzhou 510006China. UTA Research Institute The University of Texas at ArlingtonFort WorthTX 76019USA

This paper presents a learning-based control policy design for point-to-point vehicle positioning in the urban environment via BeiDou navigation.While navigating in urban canyons,the multipath effect is a kind of interference that causes the navigation signal to drift and thus imposes severe impacts on vehicle localization due to the reflection and diffraction of the BeiDou signal.Here,the authors formulated the navigation control system with unknown vehicle dynamics into an optimal control-seeking problem through a linear discrete-time system,and the point-to-point localization control is modeled and handled by leveraging off-policy reinforcement learning for feedback control.The proposed learning-based design guarantees optimality with prescribed performance and also stabilizes the closed-loop navigation system,without the full knowledge of the vehicle dynamics.It is seen that the proposed method can withstand the impact of the multipath effect while satisfying the prescribed convergence rate.A case study demonstrates that the proposed algorithms effectively drive the vehicle to a desired setpoint under the multipath effect introduced by actual experiments of BeiDou navigation in the urban environment.

关键词： BeiDou navigation multipath effect prescribed convergence rate reinforcement learning urban localization.

Broadband high-efficiency dielectric metalenses based on quasi-continuous nanostrips

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Opto-Electronic Advances 2024年第5期7卷 49-58页

作者： Xiaohu Zhang Qinmiao Chen Dongliang Tang Kaifeng Liu Haimo Zhang Lintong Shi Mengyao He Yongcai Guo Shumin Xiao key laboratory of optoelectronic Technology and systems of the Education Ministry of China Chongqing University Ministry of Industry and Information Technology key Lab of Micro-Nano Optoelectronic Information system Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic SystemsHarbin Institute of Technology key laboratory for Micro/Nano Optoelectronic Devices of Ministry of Education & Hunan Provincial key laboratory of Low-Dimensional Structural Physics and Devices School of Physics and ElectronicsHunan University

Benefiting from the abrupt phase changes within subwavelength thicknesses,metasurfaces have been widely applied for lightweight and compact optical systems.Simultaneous broadband and high-efficiency characteristics are highly attractive for the practical implementation of metasurfaces.However,current metasurface devices mostly adopt discrete micro/nano structures,which rarely realize both merits simultaneously.In this paper,dielectric metasurfaces composed of quasi-continuous nanostrips are proposed to overcome this limitation.Via quasi-continuous nanostrips metasurface,a normal focusing metalens and a superoscillatory lens overcoming the diffraction limit are designed and experimentally demonstrated.The quasi-continuous metadevices can operate in a broadband wavelength ranging from 450 nm to 1000nm and keep a high power efficiency.The average efficiency of the fabricated metalens reaches 54.24%,showing a significant improvement compared to the previously reported metalenses with the same thickness.The proposed methodology can be easily extended to design other metadevices with the advantages of broadband and high-efficiency in practical optical systems.

关键词： broadband high-efficiency metalens quasi-continuous sub-diffraction

Vision-Based Adaptive Prescribed-Time Control of UAV for Uncooperative Target Tracking with Performance Constraint

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Journal of systems Science & Complexity 2024年第5期 1956-1977页

作者： SHE Xuehua MA Hui REN Hongru LI Hongyi School of Automation and the guangdong Provincial key laboratory of intelligent Decision and Cooperative Control Guangdong University of Technology School of Mathematics and Statistics Guangdong University of Technology College of Electronic and Information Engineering and Chongqing key laboratory of Generic Technology and system of Service Robots Southwest University

This paper discusses the uncooperative target tracking control problem for the unmanned aerial vehicle(UAV) under the performance constraint and scaled relative velocity constraint, in which the states of the uncooperative target can only be estimated through a vision sensor. Considering the limited detection range, a prescribed performance function is designed to ensure the transient and steady-state performances of the tracking system. Meanwhile, the scaled relative velocity constraint in the dynamic phase is taken into account, and a time-varying nonlinear transformation is used to solve the constraint problem, which not only overcomes the feasibility condition but also fails to violate the constraint boundaries. Finally, the practically prescribed-time stability technique is incorporated into the controller design procedure to guarantee that all signals within the closed-loop system are bounded.It is proved that the UAV can follow the uncooperative target at the desired relative position within a prescribed time, thereby improving the applicability of the vision-based tracking approach. Simulation results have been presented to prove the validity of the proposed control strategy.

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Vibration-Based Fault Diagnosis for Railway Point Machines Using VMD and Multiscale Fluctuation-Based Dispersion Entropy

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Chinese Journal of Electronics 2024年第3期33卷 803-813页

作者： Yongkui SUN Yuan CAO Peng LI Guo XIE Tao WEN Shuai SU National Engineering Research Center of Rail transportation Operation and Control system Beijing Jiaotong University School of Electronic and Information Engineering Beijing Jiaotong University Shaanxi key laboratory of Complex system Control and intelligent Information Processing Xi'an University of Technology Frontiers Science Center for Smart High-speed Railway system Beijing Jiaotong University

As one of the most important railway signaling equipment,railway point machines undertake the major task of ensuring train operation safety.Thus fault diagnosis for railway point machines becomes a hot topic.Considering the advantage of the anti-interference characteristics of vibration signals,this paper proposes an novel intelligent fault diagnosis method for railway point machines based on vibration signals.A feature extraction method combining variational mode decomposition(VMD) and multiscale fluctuation-based dispersion entropy is developed,which is verified a more effective tool for feature selection.Then,a two-stage feature selection method based on Fisher discrimination and ReliefF is proposed,which is validated more powerful than single feature selection methods.Finally,support vector machine is utilized for fault diagnosis.Experiment comparisons show that the proposed method performs best.The diagnosis accuracies of normal-reverse and reverse-normal switching processes reach 100% and 96.57% respectively.Especially,it is a try to use new means for fault diagnosis on railway point machines,which can also provide references for similar fields.

关键词： Fault diagnosis Vibrations Support vector machines Diversity reception Switches Feature extraction Rail transportation

UAV-Assisted Dynamic Avatar Task Migration for Vehicular Metaverse Services: A Multi-Agent Deep Reinforcement Learning Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 430-445页

作者： Jiawen Kang Junlong Chen Minrui Xu Zehui Xiong Yutao Jiao Luchao Han Dusit Niyato Yongju Tong Shengli Xie IEEE School of Automation Guangdong University of TechnologyGuangzhou 510006China 111 Center for intelligent Batch Manufacturing based on IoT Technology Guangzhou 510006China key laboratory of intelligent Information Processing and system Integration of IoT Ministry of EducationGuangzhou 510006China School of Computer Science and Engineering Nanyang Technological UniversitySingaporeSingapore Pillar of Information systems Technology and Design Singapore University of Technology and DesignSingaporeSingapore College of Communication Engineering Army Engineering University of PLANanjing 210007China National Natural Science Foundation of China Beijing 100085China key laboratory of intelligent Detection and IoT in Manufacturing Ministry of EducationGuangzhou 510006China guangdong key laboratory of IoT Information Technology Guangzhou 510006China

Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metaverses. However, avatar tasks include a multitude of human-to-avatar and avatar-to-avatar interactive applications, e.g., augmented reality navigation,which consumes intensive computing resources. It is inefficient and impractical for vehicles to process avatar tasks locally. Fortunately, migrating avatar tasks to the nearest roadside units(RSU)or unmanned aerial vehicles(UAV) for execution is a promising solution to decrease computation overhead and reduce task processing latency, while the high mobility of vehicles brings challenges for vehicles to independently perform avatar migration decisions depending on current and future vehicle status. To address these challenges, in this paper, we propose a novel avatar task migration system based on multi-agent deep reinforcement learning(MADRL) to execute immersive vehicular avatar tasks dynamically. Specifically, we first formulate the problem of avatar task migration from vehicles to RSUs/UAVs as a partially observable Markov decision process that can be solved by MADRL algorithms. We then design the multi-agent proximal policy optimization(MAPPO) approach as the MADRL algorithm for the avatar task migration problem. To overcome slow convergence resulting from the curse of dimensionality and non-stationary issues caused by shared parameters in MAPPO, we further propose a transformer-based MAPPO approach via sequential decision-making models for the efficient representation of relationships among agents. Finally, to motivate terrestrial or non-terrestrial edge servers(e.g., RSUs or UAVs) to share computation resources and ensure traceability of the sharing records, we apply smart contracts and blockchain technologies to achieve secure sharing management. Numerical results demonstrate that the proposed approach outperforms the MAPPO approach by around 2% and

关键词： Avatar blockchain metaverses multi-agent deep reinforcement learning transformer UAVs

Resonantly enhanced second-and third-harmonic generation in dielectric nonlinear metasurfaces

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Opto-Electronic Advances 2024年第5期7卷 8-23页

作者： Ji Tong Wang Pavel Tonkaev Kirill Koshelev Fangxing Lai Sergey Kruk Qinghai Song Yuri Kivshar Nicolae C.Panoiu Department of Electronic and Electrical Engineering University College London Nonlinear Physics Center Research School of PhysicsAustralian National University Ministry of Industry and Information Technology key Lab of Micro-Nano Optoelectronic Information system Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic SystemsHarbin Institute of Technology Wuzhen laboratory EGO Wuzhen Digital Economy Industrial Park

Nonlinear dielectric metasurfaces provide a promising approach to control and manipulate frequency conversion optical processes at the nanoscale,thus facilitating both advances in fundamental research and the development of new practical applications in photonics,lasing,and sensing.Here,we employ symmetry-broken metasurfaces made of centrosymmetric amorphous silicon for resonantly enhanced second-and third-order nonlinear optical response.Exploiting the rich physics of optical quasi-bound states in the continuum and guided mode resonances,we comprehensively study through rigorous numerical calculations the relative contribution of surface and bulk effects to second-harmonic generation(SHG)and the bulk contribution to third-harmonic generation(THG) from the meta-atoms.Next,we experimentally achieve optical resonances with high quality factors,which greatly boosts light-matter interaction,resulting in about 550 times SHG enhancement and nearly 5000-fold increase of THG.A good agreement between theoretical predictions and experimental measurements is observed.To gain deeper insights into the physics of the investigated nonlinear optical processes,we further numerically study the relation between nonlinear emission and the structural asymmetry of the metasurface and reveal that the generated harmonic signals arising from linear sharp resonances are highly dependent on the asymmetry of the meta-atoms.Our work suggests a fruitful strategy to enhance the harmonic generation and effectively control different orders of harmonics in all-dielectric metasurfaces,enabling the development of efficient active photonic nanodevices.

关键词： all-dielectric metasurfaces bound state in the continuum guided mode resonance nonlinear optics second-harmonic generation third-harmonic generation

An approach for formation design and flight performance prediction based on aerodynamic formation unit:Energy-saving considerations

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Chinese Journal of Aeronautics 2024年第3期37卷 77-91页

作者： Nanxuan QIAO Tielin MA Xiangsheng WANG Jie WANG Jingcheng FU Pu XUE School of Aeronautic Science and Engineering Beihang UniversityBeijing 100191China Institute of Unmanned system Beihang UniversityBeijing 100191China key laboratory of Advanced Technology of intelligent Unmanned Flight system Ministry of Industry and Information TechnologyBeijing 100191China School of transportation Science and Engineering Beihang UniversityBeijing 102206China Beijing Institute of Space Long March Vehicle Beijing 100076China

The performance improvement of swarm drones through aerodynamic shape optimization may be challenging due to folded size constraints imposed by the specific launch approach.However,fixed-wing aircraft swarms can benefit from formation flight in terms of energy consumption.This study introduces the concept of the"aerodynamic formation unit",which consists of two or three aircraft that form an inseparable unit of the formation.Considering the Unmanned Aerial Vehicle(UAV)distribution and wingtip vortex interference in the formation,two typical aerodynamic formation units are optimized by the variable-fidelity aerodynamic optimization method based on space mapping.The aerodynamic characteristics of the formation UAVs that affect flight performance,such as lift-to-drag ratio(L/D ratio)and static stability are analyzed by Computational Fluid Dynamics(CFD)simulations.The L/D ratio(cruising condition)of the following aircraft can be increased by 22.8%and 57.5%in the optimal units that involve two and three aircraft respectively.Moreover,this study conducts several CFD simulations for multi-aircraft formations formed by the units,which show that the average L/D ratio of the formation can be improved by more than 19%.These results verify the feasibility and effectiveness of the"aerodynamic formation unit"concept and the optimization framework for formation parameters.

关键词： Formation flight CFD Aerodynamic formation unit Wingtip vortices Foldable tandem-wing aircraft

Combining permissioned blockchain and Bayesian best-worst method for transparent supplier selection in supply chain management

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Science China Technological Sciences 2024年

作者： LIU JiaJun ZHANG Jie LENG JieWu Shanghai Engineering Research Center of Industrial Big Data and intelligent system Institute of Artificial Intelligence Donghua University State key laboratory of Precision Electronic Manufacturing Technology and Equipment Guangdong University of Technology

Supplier selection is an important business activity in order to realize the purchasing function in supply chain management. The supplier selection process includes four stages, i.e., bidding inviting, bidding, group decision-making, and results disclosure,involving the participation of manufacturing service demanders(MSDs), manufacturing service suppliers(MSSs), and decisionmakers. Nowadays, all the participants have raised concerns about the increased transparency in supplier selection. Therefore,this study proposes a transparent supplier selection method by considering the engagement of suppliers. In this method, the Bayesian best-worst method(Bayesian BWM) is used to aggregate decision-makers' preferences into the overall optimal weights of the alternative MSSs, and the MSS with the largest weight is considered the suitable MSS for MSDs. Furthermore,blockchain is introduced to record the decision-making process information about supplier selection through a customized smart contract, where MSSs act as supervisors to supervise the decision-making process through the distributed consensus mechanism rather than directly participate in the decision-making process. Finally, a case study of supplier selection in purchasing vibration acceleration sensors is presented. The result shows that the proposed method can support MSDs in selecting suitable MSS from alternative MSSs by aggregating decision-makers' preferences, and blockchain can provide credible information about the supplier selection process for MSSs, MSDs, and decision-makers. In this way, the transparency of supplier selection is enhanced.

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Miniature tunable Airy beam optical meta-device

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Opto-Electronic Advances 2024年第2期7卷 5-12页

作者： Jing Cheng Zhang Mu Ku Chen Yubin Fan Qinmiao Chen Shufan Chen Jin Yao Xiaoyuan Liu Shumin Xiao Din Ping Tsai Department of Electrical Engineering City University of Hong KongKowloonHong Kong SAR 999077China State key laboratory of Terahertz and Millimeter Waves City University of Hong KongKowloonHong Kong SAR 999077China Centre for Biosystems Neuroscienceand NanotechnologyCity University of Hong KongKowloonHong Kong SAR 999077China Ministry of Industry and Information Technology key Lab of Micro-Nano Optoelectronic Information system Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic SystemsHarbin Institute of TechnologyShenzhen 518055China

Tunable Airy beams with controllable propagation trajectories have sparked interest in various fields,such as optical manipulation and laser fabrication.Existing research approaches encounter challenges related to insufficient compactness and integration feasibility,or they require enhanced tunability to enable real-time dynamic manipulation of the propagation trajectory.In this work,we present a novel method that utilizes a dual metasurface system to surpass these limitations,significantly enhancing the practical potential of the Airy beam.Our approach involves encoding a cubic phase profile and two off-axis Fresnel lens phase profiles across the two metasurfaces.The validity of the proposed strategy has been confirmed through simulation and experimental results.The proposed meta-device addresses the existing limitations and lays the foundation for broadening the applicability of Airy beams across diverse domains,encompassing light-sheet microscopy,laser fabrication,optical tweezers,etc.

关键词： metasurface miniature device tunable Airy beam tunable meta-device