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Chaos synchronization of semiconductor lasers over 1040-km fiber relay transmission with hybrid amplification

Photonics Research 2023年第6期11卷 953-960页

作者： LONGSHENG WANG JUNLI WANG YUSHAN WU YUEHUI SUN SONGSUI LI LIANSHAN YAN YUNCAI WANG ANBANG WANG Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of EducationTaiyuan 030024China College of Physics and Optoelectronics Taiyuan University of TechnologyTaiyuan 030024China School of Information Engineering Guangdong University of TechnologyGuangzhou 510006China Guangdong Provincial Key Laboratory of Photonics Information Technology Guangzhou 510006China Center for Information Photonics&Communications School of Information Science and TechnologySouthwest Jiaotong UniversityChengdu 610031China

Optical chaos communication and key distribution have been extensively demonstrated with high-speed advantage but only within the metropolitan-area network range of which the transmission distance is restricted to around 300 *** secure-transmission requirement of the backbone fiber link,the critical threshold is to realize long-reach chaos ***,we propose and demonstrate a scheme of long-reach chaos synchronization using fiber relay transmission with hybrid amplification of an erbium-doped fiber amplifier(EDFA)and a distributed fiber Raman amplifier(DFRA).Experiments and simulations show that the hybrid amplification extends the chaos-fidelity transmission distance thanks to that the low-noise DFRA suppresses the amplified spontaneous emission noise and self-phase *** of the hybrid-relay conditions are studied,including launching power,gain ratio of DFRA to EDFA,single-span fiber length,and number of fiber span.A 1040-km chaos synchronization with a synchronization coefficient beyond 0.90 is experimentally achieved,which underlies the backbone network-oriented optical chaos communication and key distribution.

关键词： synchronization fiber amplifier

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K-BMPC: Derivative-based Koopman Bilinear Model Predictive control for Tractor-Trailer Trajectory Tracking with Unknown Parameters

arXiv

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arXiv 2023年

作者： Wang, Zehao Zhang, Han Wang, Jingchuan Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in the dynamics are unknown. To address this constraint, we propose a derivative-based lifting function construction method, show that the corresponding infinite dimensional Koopman bilinear model over the lifting function is equivalent to the original control-affine system. Further, we analyze the propagation and bounds of state prediction errors caused by the truncation in derivative order. The identified finite dimensional Koopman bilinear model would serve as predictive model in the next step. Koopman Bilinear Model Predictive control (K-BMPC) is proposed to solve the trajectory tracking problem. We linearize the bilinear model around the estimation of the lifted state and control input. Then the bilinear Model Predictive control problem is approximated by a quadratic programming problem. Further, the estimation is updated at each iteration until the convergence is reached. Moreover, we implement our algorithm on a tractor-trailer system, taking into account the longitudinal and side slip effects. The open-loop simulation shows the proposed Koopman bilinear model captures the dynamics with unknown parameters and has good prediction performance. Closed-loop tracking results show the proposed K-BMPC exhibits elevated tracking precision with the commendable computational efficiency. The experimental results demonstrate the feasibility of K-BMPC. © 2023, CC BY-NC-SA.

关键词： Model predictive control

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NeRF in Robotics: A Survey

arXiv

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arXiv 2024年

作者： Wang, Guangming Pan, Lei Peng, Songyou Liu, Shaohui Xu, Chenfeng Miao, Yanzi Zhan, Wei Tomizuka, Masayoshi Pollefeys, Marc Wang, Hesheng The University of Cambridge ETH Zurich Switzerland The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education of China China Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China ETH Zurich Zurich Switzerland Mechanical Systems Control Laboratory University of California Berkeley United States

Meticulous 3D environment representations have been a longstanding goal in computer vision and robotics fields. The recent emergence of neural implicit representations has introduced radical innovation to this field as implicit representations enable numerous capabilities. Among these, the Neural Radiance Field (NeRF) has sparked a trend because of the huge representational advantages, such as simplified mathematical models, compact environment storage, and continuous scene representations. Apart from computer vision, NeRF has also shown tremendous potential in the field of robotics. Thus, we create this survey to provide a comprehensive understanding of NeRF in the field of robotics. By exploring the advantages and limitations of NeRF, as well as its current applications and future potential, we hope to shed light on this promising area of research. Our survey is divided into two main sections: The Application of NeRF in Robotics and The Advance of NeRF in Robotics, from the perspective of how NeRF enters the field of robotics. In the first section, we introduce and analyze some works that have been or could be used in the field of robotics from the perception and interaction perspectives. In the second section, we show some works related to improving NeRF's own properties, which are essential for deploying NeRF in the field of robotics. In the discussion section of the review, we summarize the existing challenges and provide some valuable future research directions for reference. © 2024, CC BY-NC-ND.

关键词： Robotics

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Sensor-based Multi-agent Coverage control with Spatial Separation in Unstructured Environments

arXiv

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arXiv 2024年

作者： Wang, Xinyi Xu, Jiwen Gao, Chuanxiang Chen, Yizhou Zhang, Jihan Wang, Chenggang Ding, Yulong Chen, Ben M. Department of Mechanical and Automation Engineering The Chinese University of Hong Kong N.T. Shatin Hong Kong Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai200240 China Department of Control Science and Engineering Tongji University Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education China

Multi-robot systems have increasingly become instrumental in tackling coverage problems. However, the challenge of optimizing task efficiency without compromising task success still persists, particularly in expansive, unstructured scenarios with dense obstacles. This paper presents an innovative, decentralized Voronoi-based coverage control approach to reactively navigate these complexities while guaranteeing safety. This approach leverages the active sensing capabilities of multi-robot systems to supplement GIS (Geographic Information system), offering a more comprehensive and real-time understanding of environments like post-disaster. Based on point cloud data, which is inherently non-convex and unstructured, this method efficiently generates collision-free Voronoi regions using only local sensing information through spatial decomposition and spherical mirroring techniques. Then, deadlock-aware guided map integrated with a gradient-optimized, centroid Voronoi-based coverage control policy, is constructed to improve efficiency by avoiding exhaustive searches and local sensing pitfalls. The effectiveness of our algorithm has been validated through extensive numerical simulations in high-fidelity environments, demonstrating significant improvements in task success rate, coverage ratio, and task execution time compared with others. Copyright © 2024, The Authors. All rights reserved.

关键词： Multipurpose robots

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Oscillation Trajectory Optimization and control Method for Two-Link Underactuated Manipulators

Oscillation Trajectory Optimization and Control Method for T...

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Chinese control Conference (CCC)

作者： Lejun Wang Huiming Wang Xianlun Tang Zixin Huang Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan China

This paper provides an oscillation trajectory optimization and control method for two-link underactuated manipulators (UMs) in a vertical plane. The proposed method solves the problem that the UMs cannot always enter the balance region in the partitioning method. First, we establish the system dynamic model, and analyze the system couple characteristics. Then, we program an oscillation trajectory for the active link, and use the intelligent method to obtain the trajectory parameters, so ensuring the system can reach the area adjacent to the target position through tracking control. Next, we design the controller to realize the stable control at the target position. Finally, the simulation results show the effectiveness and generality of the control strategy.

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Self-Supervised Depth Estimation Based on the Consistency of Synthetic-real Image Prediction

Self-Supervised Depth Estimation Based on the Consistency of...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Wei Tong Yubing Gao Edmond Q. Wu Li-Min Zhu School of Mechanical Engineering Nanjing University of Science and Technology Jiangsu China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

Learning-based multi-view stereo aims to restore the real scene from multiple images with overlapping areas. The mainstream self-supervised MVS method trains the model based on the assumption that spatial points from different perspectives share the same color information. To further suppress the interference from specular reflection and illumination noise, this work proposes a self-supervised MVS network based on the consistency of synthetic-real image prediction. The network first applies the coarse-to-fine manner to gradually refine the depth map, and the source images are projected to the reference view to generate the synthesized reference image. Then the synthesized image with real source images are re-input into the network to form a cycled network, and the consistency constraint of the prediction results of the two periods is introduced to improve the color anti-interference of the self- supervised MVS model. The comprehensive experiments on the public dataset show that the proposed work can further improve the reconstruction performance of the benchmark model, which verifies the effectiveness of the proposed work.

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Nash Pursuit Strategy for Nonzero-Sum MPC Game via Inverse Optimal control 13

Nash Pursuit Strategy for Nonzero-Sum MPC Game via Inverse O...

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13th Asian control Conference, ASCC 2022

作者： Qiu, Tianyu Zhang, Han Wang, Jingchuan Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9788993215236

In this paper, a traditional one v.s. one pursuit and evasion scenario is considered. The evader aims to reach her target and avoid being captured by the pursuer, while the pursuer, without the knowledge of the evader's cost function, intends to capture the evader before she successfully escapes. We formulate this problem as a Model Predictive control Decoupled Pursuit and Evasion Game (MPC-DPEG) model with incomplete information. We apply Inverse Optimal control (IOC) technique to estimate the evader's cost function and give a Nash pursuit strategy for MPC-DPEG as the optimal strategy for the pursuer. Numerical examples reveal the improvement of pursuit performance of the Nash pursuit strategy based on the estimated cost function over naive pursuit strategies. © 2022 ACA.

关键词： Simulation Optimal control Games Predictive models Cost function Numerical models Predictive control

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The Back Diffusion of Catalysts on the Oxidation Characteristics of Particle Layer During the Cdpf Active Regeneration Process

SSRN

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SSRN 2024年

作者： Meng, Zhongwei Deng, Meng Wu, Daigeng Ou, Juan Liu, Xiangqun Bao, Zhongqiang Key Laboratory of Fluid and Power Machinery Ministry of Education School of Energy and Power Engineering Xihua University Chengdu610039 China Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province School of Automobile and Transportation Xihua University Chengdu610039 China Power Machinery and Vehicular Engineering Institute Zhejiang University Hangzhou310027 China

Pressure drop is an important parameter in the regeneration process of diesel particulate filter (DPF) and catalyzed DPF (CDPF). It indicates the overall oxidation status of the particle layer on the filter channel, while the thickness change of the particle layer reflects the oxidation status of the particle layer on the wall surface. This research systematically investigates the back diffusion effect of catalysts on pressure drop and particle layer thickness during the active regeneration process of CDPF. The experimental results show that the pressure drop of different thickness particle layers on the CDPF filter during regeneration exhibits a three-stage trend with the back diffusion effect of catalysts. when the particle layer deposition thickness is less than 80μm, the pressure drop rate is the highest in the second stage and the beneficial effect of back diffusion in promoting the oxidation of carbon black particles leads to a significantly higher pressure drop rate in the second stage of CDPF than DPF. When the particle layer thickness exceeds 80 μm, the diameter of the effective airflow micropores (effective flow pores) inside the particle layer gradually decreases, resulting in a lower pressure drop rate in the second stage of CDPF compared to DPF. However, the duration of CDPF in the second stage is longer, leading to a shorter duration of CDPF in the third stage and a smaller total pressure drop value. The study also elucidates a time delay in the initiation of pressure drop and thickness reduction in CDPF, which is significantly shortened in particle layers exceeding 193 μm in thickness. This reduction in time delay is attributed to the catalyst-induced simultaneous oxidation at both the top and bottom of the particle layer. These findings provide a nuanced understanding of the catalytic role in modulating pressure drop and particle layer thickness during the regeneration of particulate filters. This study provides substantive theoretical contributions

关键词： Pressure drop

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Experimental Effects of Ash (Zno) and Catalyst (Ceo2) on Dpf Regeneration Performance and Emission Characteristics

SSRN

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SSRN 2024年

作者： Meng, Zhongwei Bao, Zhongqiang Chen, Zhao Zeng, Bosong Qin, Zihan Tan, Jie Pu, Ping Key Laboratory of fluid and power machinery Ministry of education Xihua University Sichuan Province Chengdu610039 China Key Laboratory of vehicle measurement and control and safety School of automobile and transportation Xihua University Sichuan Province Chengdu610039 China Sichuan Engineering Technical College Sichuan Province Deyang618000 China

The regeneration characteristics of diesel particulate filter (DPF) are studied on a regeneration test bench, with a focus on the effects of ash and catalyst, including the effects of ZnO and CeO2 on the regeneration performance and emission characteristics of DPF. The results indicate that the addition of ZnO and CeO2 can easily lead to local high temperatures during the regeneration process of DPF, the highest peak temperature appears in a 1:3 ratio both for ZnO and CeO2, leading to a significant increase in CO2. Compared with ZnO, the CeO2 can advance the DPF rapid regeneration period by about 300 s. When the ratio of PU: CeO2 is 1:5, the total particulate matter emitted is reduced to the lowest level, but it will significantly increase the emission of nuclear model particles，especially particles below 23 nm. Under the same mixing ratio, an increase in carbon loading can enhance the oxidation ability of ZnO towards carbon black, but the difference between the number of particles emitted during DPF regeneration and regeneration efficiency will gradually decrease. © 2024, The Authors. All rights reserved.

关键词： Cerium oxide

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Dynamic analysis and control of fractional order memristor Hopfield neural network

Dynamic analysis and control of fractional order memristor H...

引用

第42届中国控制会议

作者： Feng Liu Gang Cai Feifan Zhou Wei Wang Hua Wang Xiuqin Yang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University

In this paper, a novel smooth magnetron is introduced to construct a fractional memristor Hopfield neural network(fractional order M-HNN). The local stability of equilibrium point are analyzed theoretically. Taking the memristor coupling strength coefficient and the fractional order as bifurcation parameters, the phase trajectory diagram, the bifurcation diagram of the system are drawn to analyze the influence on the dynamic behavior of the neural network. When the system parameters are fixed, the hyperchaos phenomenon of the fractional order M-HNN model is revealed. Finally, the PD controller is applied to the model to enhance the stability of the system.

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