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TechRxiv 2023年

作者： Yang, Songnan Zhang, Xiaohui Liu, Ding Bai, Wenqi Liu, Fan The School of Automation and Information Engineering Xi’an University of Technology Shaanxi 710048 China The Institute of Advanced Navigation and Electromagnetics Xi’an University of Technology Shaanxi 710048 China The State Key Laboratory of Eco-Hydraulics in the Northwest Arid Region of China Xi’an University of Technology Shaanxi 710048 China The Shaanxi Key Laboratory of Complex System Control with the Intelligent Information Processing Xi’an University of Technology Shaanxi 710048 China

Numerous studies have demonstrated that numerous animal species are capable of goal-directed navigation using environmental information for dead reckoning. The stable magnetic field of the earth provides important information for the migration of animals over long distances. Inspired by the goal-directed navigation of animals, a novel Geomagnetic Navigation with Temporal Attention-based Data-Driven Dead Reckoning (Attention-DR) method for Autonomous Underwater Vehicles (AUV) is presented in this article, which only utilizes the inclination angle (I) and the declination angle (D) of the Geomagnetic Field (GF) for underwater navigation without any prior knowledge of the geographical location or geographic map. This article proposes a Temporal Attention-based Long Short-Term Memory (TA-LSTM) neural network by combining history, GF information, and location in time series to achieve the optimization heading angle of underwater dead reckoning. Due to its ability to adjust the utilization weights of local and global temporal information in the path, TA-LSTM possesses the capability to continually update neural network model parameters through a data-driven process during the navigation process. This enables the Attention-DR to achieve efficient navigation in regions without prior magnetic maps and overcome navigation failures caused by magnetic field anomalies. The simulation outcomes confirm the efficiency, precision, and practicability of the proposed algorithm. © 2023, CC BY.

关键词： Navigation

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The design of a new fiber optic sensor for measuring linear velocity with pico meter/second sensitivity based on Weak-value amplification

arXiv

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arXiv 2021年

作者： Huang, Jing-Hui Duan, Xue-Ying Wang, Guang-Jun Hu, Xiang-Yun School of Institute of Geophysics and Geomatics China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

We put forward a new fiber optic sensor for measuring linear velocity with picometer/second sensitivity with Weak-value amplification based on generalized Sagnac effect [Phys. Rev. Lett.93, 143901(2004)].The generalized Sagnac effect was first introduced by Yao et al, which included the Sagnac effect of rotation as a special case and suggested a new fiber optic sensor for measuring linear motion with nanoscale sensitivity. By using a different scheme to perform the Sagnac interferometer with the probe in momentum space, we have demonstrated the new weak measure protocol to detect the linear velocity by amplifying the phase shift of the generalized Sagnac effect. Given the maximum incident intensity of the initial spectrum, the detection limit of the intensity of the spectrometer, we can theoretically give the appropriate pre-selection, post-selection and other optical structures before the experiment. Our numerical results show our scheme with Weak-value amplification is effective and feasible to detect linear velocity with picometer/second sensitivity which is three orders of magnitude smaller than the result ν=4.8 × 10-9 m/s obtained by generalized Sagnac effect with same fiber length. © 2021, CC BY.

关键词： Fiber optic sensors

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Refined H-Wo3 by Mo Doping: A Strategy for Enhancing Hydrogen Ion Storage Performance

SSRN

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SSRN 2024年

作者： Wang, Liushun Yi, Jinqiao Tang, Dongsheng Ren, Dahua Zhang, Teng Zhang, Yuan Cheng, Jiaxin Li, Dong Zhang, Chunyan College of Intelligent Systems Science and Engineering Hubei Minzu University Enshi445000 China Synergetic Innovation Center for Quantum Effects and Application Key Laboratory of Low-dimensional Quantum Structures and Quantum Control Ministry of Education School of Physics and Electronics Hunan Normal University Changsha410081 China Hunan Key Laboratory of Two-Dimensional Materials Advanced Catalytic Engineering Research Center The Ministry of Education College of Chemistry and Chemical Engineering Hunan University Changsha410082 China Hubei University for Nationalities China Hunan Normal University China

The crystal structure shear and the electronic structure modulation through ion doping are both kinetically relevant to develop high-performance electrode materials for electrochemical energy storage, yet they remain a significant challenge. This study proposes the preparation of ultrafine molybdenum-doped tungsten oxide nanowires as advanced materials for hydrogen ion (H+) storage. These materials exhibited high multiplicity performance (98 mAh/g at 20C;89 mAh/g at 100C, with 1C=100 mAh/g) at the optimal Mo doping concentration (MW-5, The molar ratio of Mo to W is equal to 5%, abbreviated as MW = 5). Additionally, the MW-5 nanowire electrode showed superior Na+ and NH4+ storage capacities as compared to h-WO3. The enhanced hydrogen ion storage capability of Mo-doped WO3 nanowires was ascribed to their larger specific surface area and to the presence of a substantial amount of W6+, W5+, Mo6+, Mo5+, and Mo4+ ions. The high specific surface area of ultrafine nanowires with abundant defect structures significantly shortened the charge carrier transport distance, increased hydrogen ionization ion storage sites, and accelerated interfacial electron motion, thereby improving ion storage kinetics. Our findings revealed the potential of interface-engineering strategies in advancing towards high-performance hydrogen ion storage electrode materials for efficient green energy conversion applications. © 2024, The Authors. All rights reserved.

关键词： Nanowires

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Design of a curled hyper-redundant manipulator and the motion control with tip-following algorithm

Design of a curled hyper-redundant manipulator and the motio...

引用

Chinese control and Decision Conference, CCDC

作者： Aoshun Zhang En Li Feng Zhang Rui Guo Mingrui Luo Yuwei Zhang School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Engineering Laboratory for Intelligent Industrial Vision CAS Beijing China State Grid Intelligent Technology Co. Ltd. Shandong China State Grid Shandong Electric Power Company Jinan Power Supply Company Shandong China

In order to meet the operational needs in some narrow environments, the hyper-redundant snake-shaped manipulator has received extensive attention and has been widely studied due to its compact shape and multiple degrees of freedom. At present, the research of hyper-redundant manipulator mainly focuses on the straight push platform. Considering the limitation of working space, this paper designed a hyper-redundant manipulator delivered by a curled turntable. According to the characteristics of turntable delivery, a tip-following algorithm based on curve fitting and a tip-following strategy based on terminal posture record are proposed. Finally, with the algorithm applied to the physical robot we made, we successfully realized the tip-following motion control of the hyper-redundant manipulator.

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Deep Convolutional Correlation Filter Learning Toward Robust Visual Object Tracking

Deep Convolutional Correlation Filter Learning Toward Robust...

引用

Chinese control and Decision Conference, CCDC

作者： Tayssir Bouraffa Zihang Feng Yuxuan Wang Liping Yan Yuanqing Xia Bo Xiao School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing P. R. China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing P. R. China

ISBN: (纸本)9781665478977

Recently, convolutional neural network has been pervasively adopted in visual object tracking for its potential in discriminating the target from the surrounding background. Most of the visual object trackers extract deep features from a specific layer, generally from the last convolutional layer. However, these trackers are less effective, especially when the target undergoes drastic appearance variations caused by the presence of different challenging situations, such as occlusion, illumination change, background clutter and so on. In this research paper, a novel tracking algorithm is developed by introducing an elastic net constraint and a contextual information into the convolutional network to successfully track the desired target throughout a video sequence. Hierarchical features are extracted from the shallow and the deep convolutional layers to further improve the tracking accuracy and robustness. As the deep convolutional layers capture important semantic information, they are more robust to the target appearance variations. As for the shallow convolutional layers, they encode significant spatial details, which are more accurate to precisely localize the desired target. Moreover, Peak–Strength Context–Aware correlation filters are embedded to each convolutional layer output that produce multi–level convolutional response maps to collaboratively identify the estimated position of the target in a coarse–to–fine manner. Quantitative and qualitative experiments are performed on the widely used benchmark, the OTB–2015 dataset that shows impressive results compared to the state–of–the–art trackers.

关键词： Visualization Target tracking Correlation Semantics Video sequences Feature extraction Information filters

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Mechanical Structure and control Methods for Lower-Limb Rehabilitation Robots

Mechanical Structure and Control Methods for Lower-Limb Reha...

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第40届中国控制会议

作者： Wangyang Ge Ruoyu Jiang Juan Zhao Zhentao Liu Zhaohui Yang Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Rehabilitation Union HospitalTongji Medical CollegeHuazhong Univ.Science & Technology School of Engineering Tokyo University of Technology

As a rehabilitation aid,lower-limb rehabilitation robots help patients recover their walking *** paper presets a review of such a rehabilitation ***,we classify commercially available common types of lower-limb rehabilitation ***,we briefly describe the structure and characteristics of those robots,Then,we present the control methods used in those ***,we explain future research directions.

关键词： rehabilitation robots mechanical structure control method biological signal

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Novel PIO Algorithm with Multiple Selection Strategies for Many-Objective Optimization Problems

引用

complex System Modeling and Simulation 2021年第4期1卷 291-307页

作者： Zhihua Cui Lihong Zhao Youqian Zeng Yeqing Ren Wensheng Zhang Xiao-Zhi Gao School of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan 030024China School of Cyberspace Security Beijing University of Posts and TelecommunicationsBeijing 100876China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Computing University of Eastern FinlandKuopioFI-70211Finland

With the increase of problem dimensions,most solutions of existing many-objective optimization algorithms are ***,the selection of individuals and the retention of elite individuals are *** algorithms cannot provide sufficient solution precision and guarantee the diversity and convergence of solution sets when solving practical many-objective industrial ***,this work proposes an improved many-objective pigeon-inspired optimization(ImMAPIO)algorithm with multiple selection strategies to solve many-objective optimization *** selection strategies integrating hypervolume,knee point,and vector angles are utilized to increase selection pressure to the true Pareto ***,the accuracy,convergence,and diversity of solutions are *** is applied to the DTLZ and WFG test functions with four to fifteen objectives and compared against NSGA-III,GrEA,MOEA/D,RVEA,and many-objective Pigeon-inspired optimization *** results indicate the superiority of ImMAPIO on these test functions.

关键词： pigeon-inspired optimization algorithm many-objective optimization problem multiple selection strategy elite individual retention

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A Memristor Based Chaotic Oscillator for Weak Signal Detection and Its Circuitry Realization

Research Square

引用

Research Square 2021年

作者： Dong, Kaifeng Xu, Kun Zhou, Youyou Zuo, Chao Wang, Leimin Zhang, Chuanke Jin, Fang Song, Junlei Mo, Wenqin Hui, Yajuan School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

A new type of weak signal detection system that combines the memristor and Van der pol-Duffing chaotic system has been proposed in this paper, and the dynamic characteristics of the system are studied. It is observed that the system can change from a chaotic state to a periodic state under different driving force amplitudes. Moreover, as compared with several classical chaotic oscillators, the numerical simulation results show that the system has stronger anti-noise performance with the detectable signal-to-noise ratio reaches -163dB, and has a wider detection range. Its detection accuracy is up to 1 × 10−9. More importantly, this paper provides the circuit implementation scheme of the system, and the weak signal can be detected with our designed circuit. This may offer a possible way for weak signal detection system with good performance in anti-noise performance, detection range and accuracy. © 2021, CC BY.

关键词： Memristors

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A Novel Scalable Framework For Constructing Dynamic Multi-objective Optimization Problems

A Novel Scalable Framework For Constructing Dynamic Multi-ob...

引用

Congress on Evolutionary Computation

作者： Qingshan Tan Changhe Li Hai Xia Sanyou Zeng Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

Modeling dynamic multi-objective optimization problems (DMOPs) has been one of the most challenging tasks in the field of dynamic evolutionary optimization. Based on the analysis of the existing DMOPs, several features widely existed in real-world applications are not taken into account: different objectives may have different function models and variables to be optimized; and the number of conflicting variables should be independent from the number of objectives; the time-linkage property is not considered. In order to overcome the above issues, a novel framework for constructing DMOPs is proposed, where all objectives can be designed independently, and the number of the conflicting variables can be tuned by users. Moreover, it is easy to add new dynamic features to this framework. Several classical dynamic multi-objective optimization algorithms are tested on four scenarios, results show that these characteristics are challenging for the existing algorithms.

关键词： Schedules Analytical models Heuristic algorithms Object oriented modeling Evolutionary computation Benchmark testing Dynamic scheduling

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A Reinforcement-Learning-Based Evolutionary Algorithm Using Solution Space Clustering For Multimodal Optimization Problems

A Reinforcement-Learning-Based Evolutionary Algorithm Using ...

引用

Congress on Evolutionary Computation

作者： Hai Xia Changhe Li Sanyou Zeng Qingshan Tan Junchen Wang Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

In evolutionary algorithms, how to effectively select interactive solutions for generating offspring is a challenging problem. Though many operators are proposed, most of them select interactive solutions (parents) randomly, having no specificity for the features of landscapes in various problems. To address this issue, this paper proposes a reinforcement-learning-based evolutionary algorithm to select solutions within the approximated basin of attraction. In the algorithm, the solution space is partitioned by the k-dimensional tree, and features of subspaces are approximated with respect to two aspects: objective values and uncertainties. Accordingly, two reinforcement learning (RL) systems are constructed to determine where to search: the objective-based RL exploits basins of attraction (clustered subspaces) and the uncertainty-based RL explores subspaces that have been searched comparatively less. Experiments are conducted on widely used benchmark functions, demonstrating that the algorithm outperforms three other popular multimodal optimization algorithms.

关键词： Uncertainty Clustering algorithms Evolutionary computation Reinforcement learning Benchmark testing Search problems Feature extraction

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