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42nd Chinese control Conference, CCC 2023

作者： Siting, Peng Lei, Li Zhu, Hongbo Jun, Ren Zhichao, Song Yang, Jiabing The Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beihang University School of Electronics and Information Engineering Beijing China

ISBN: (纸本)9789887581543

In the engineering field, there is a requirement for re recognition, including the identity recognition of cooperative and non-cooperative targets, that is, different sensors shoot targets in the same scene, and the identity recognition of targets from two perspectives is required, also known as target accurate retrieval. This method is widely used in fields such as automatic driving and military strikes. In the actual application scenario, deploying the re-recognition algorithm on the embedded processor needs to ensure the real-time computing speed and accuracy, so the complexity of the deep learning algorithm must be reduced, and pruning and lightweight processing are required. In the engineering field, when the image acquired by the sensor is subject to natural interference such as cloud and fog weather or fire and smoke, the difficulty of re-recognition increases. This paper adopts the lightweight improvement of ConvNeXt network model, and fine-tuned it on the basis of its original feature extraction function, so that it can successfully migrate to infrared image classification and also complete the extraction of infrared image target detail distinguishing features, and at the same time introduce the alignment of similar targets in infrared cross-view recognition. In the original similarity calculation, the average value is directly obtained from the spatial dimension of the output feature layer, which is replaced by the weight of the position in each space for estimation. The feature information of the multi-view marine ship target is extracted from the multi-sensor marine image, and its similarity is calculated, so as to determine the identity, thus reducing the support conditions and reconnaissance costs, and improving the accurate detection and tracking ability under the diverse dynamic reconnaissance conditions. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Feature extraction

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Tightly-Coupled Lidar-Visual-Inertial Odometry and Mapping in Real Time 42

Tightly-Coupled Lidar-Visual-Inertial Odometry and Mapping i...

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42nd Chinese control Conference, CCC 2023

作者： Ma, Wenyu Tian, Bailing Lu, Hanchen Shen, Hongming School of Electrical and Information Engineering Tianjin University Tianjin300072 China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789887581543

We proposed a tightly-coupled Lidar-visual-inertial odometry and mapping method, which takes advantage of measurement of Lidar, visual and inertial sensors to achieve highly accurate, real-time 6DoF state estimation and map-building in GNSS-denied environments. The proposed odometry is a tightly-coupled optimization-based method, obtains robust and low drift odometry by fusing pre-integrated IMU measurements, visual features from the image, and geometric features from Lidar data. Further, we adapt an online method to mitigate degeneracy in optimization problems to improve robustness in environmentally degenerate cases. Simulation and real-world experiments show that the proposed method exhibits similar or better robustness and accuracy with the state-of-the-art SLAM methods. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Optical radar

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Principal Trotter observation error with truncated commutators

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Physical Review A 2024年第6期110卷 062614-062614页

作者： Langyu Li Institute of Cyber-system and Control College of Control Science and Engineering Zhejiang University Hangzhou Zhejiang 310027 China and State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou Zhejiang 310027 China

Hamiltonian simulation is one of the most promising applications of quantum computers, and the product formula is one of the most important methods for this purpose. Previous related work has mainly focused on the worst-case, average-case, or actual-case scenarios. In this work we consider the simulation error under a fixed observable. Specifically, errors that commute with this observable become less significant. To illustrate this point, we define the observation error as the expectation under the observable and provide a commutativity-based upper bound using the Baker-Campbell-Hausdorff formula. Furthermore, we observe that the evolution order plays a critical role in determining the observation error. By leveraging a simulated annealing algorithm, we design an evolution order optimization algorithm, to identify an order that enhances commutativity with the observable, where the observation error indicated by this upper bound can be significantly compressed. In the experiment with the Heisenberg model, the observation bound compresses the Trotter number by nearly half compared to recent commutator bounds. The experiment on the hydrogen molecule Hamiltonian demonstrates that optimizing the order can lead to nearly half the reduction in the Trotter number.

关键词： Hamiltonians

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Multi-Channel Based on Attention Network for Infrared Small Target Detection

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Journal of Shanghai Jiaotong university(science) 2024年第3期29卷 414-427页

作者：张彦军王碧云蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Institute of Aerospace Control Technology Shanghai 201109China Infrared Detection Technology R&D Center of China Aerospace Science and Technology Corporation Shanghai 201109China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghai 200240China

Infrared detection technology has the advantages of all-weather detection and good concealment,which is widely used in long-distance target detection and tracking ***,the complex background,the strong noise,and the characteristics of small scale and weak intensity of targets bring great difficulties to the detection of infrared small targets.A multi-channel based on attention network is proposed in this paper,aimed at the problem of high missed detection rate and false alarm rate of traditional algorithms and the problem of large model,high complexity and poor detection performance of deep learning ***,given the difficulty in extracting the features of infrared multiscale and small dim targets,the multiple channels are designed based on dilated convolution to capture multiscale target ***,the coordinate attention block is incorporated in each channel to suppress background clutters adaptively and enhance target *** addition,the fusion of shallow detail features and deep abstract semantic features is realized by synthesizing the contextual attention fusion ***,it is verified that,compared with other state-of-the-art methods based on the datasets SIRST and MDFA,the proposed algorithm further improves the detection effect,and the model size and computational complexity are smaller.

关键词： infrared image small target detection deep learning attention mechanism feature fusion

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Safe Tracker: A Robust Aerial system for Safe Tracking in Cluttered Environments 42

Safe Tracker: A Robust Aerial System for Safe Tracking in Cl...

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42nd Chinese control Conference, CCC 2023

作者： Hui, Yulin Tian, Bailing Zhang, Xuewei Lu, Hanchen Shen, Hongming School of Electrical and Information Engineering Tianjin University Tianjin300072 China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789887581543

This paper proposes Safe Tracker, an autonomous aerial tracking framework based on vision sensor that can deal with challenging tracking missions and guarantee safety and visibility. Firstly, a RGB-D sensor based segmentation method is employed to locate the target in real-time. Then target motion is predicted for a short time horizon, based on which a heuristic path searching method is applied to generate an occlusion-free path. Finally, particular formulations to balance visibility and safety are designed, and an effective non-linear trajectory optimization method enables to generate an optimal tracking trajectory. Autonomous aerial tracking experiments using a vision sensor are conducted to demonstrate the effectiveness of the proposed Safe Tracker in a challenging cluttered forest and a room full of sharp turns using Gazebo. Benchmark comparisons validate that our method tracks more safely and robustly than the state-of-art method. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Trajectories

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Biochars derived from carp residues:characteristics and copper immobilization performance in water environments

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Frontiers of Environmental science & engineering 2023年第6期17卷 99-112页

作者： Hongtao Qiao Yongsheng Qiao Cuizhu Sun Xiaohan Ma Jing Shang Xiaoyun Li Fengmin Li Hao Zheng Institute of Applied Chemistry&Department of Chemistry Xinzhou Teachers UniversityXinzhou 034000China Institute of Coastal Environmental Pollution Control Ministry of Education Key Laboratory of Marine Environment and EcologyCollege of Environmental Science and EngineeringFrontiers Science Center for Deep Ocean Multispheres and Earth SystemOcean University of ChinaQingdao 266100China Department of Environmental Science School of Geography and TourismShaanxi Normal UniversityXi'an 710119China Sanya Oceanographic Institution Ocean University of ChinaSanya 572000China

Heavy metal pollution has attracted worldwide attention because of its adverse impact on the aquatic environment and human *** production of biochar from biowaste has become a promising strategy for managing animal carcasses and remediating heavy metal pollution in the aquatic ***,the sorption and remediation performance of carp residue-derived biochar(CRB)in Cu-polluted water is poorly ***,batches of CRB were prepared from carp residues at 450–650℃(CRB450–650)to investigate their physicochemical characteristics and performance in the sorption and remediation of Cu-polluted *** with a relatively low-temperature CRB(e.g.,CRB450),the high-temperature biochar(CRB650)possessed a large surface area and thermodynamic ***650 contained higher oxygen-containing functional groups and P-associated minerals,such as *** the pyrolytic temperature increased from 450 to 650℃,the maximum sorption capacity of the CRBs increased from 26.5 to 62.5 mg/*** adsorption process was a type of monolayer adsorption onto homogenous materials,and the sorption of Cu^(2+)on the CRB was mainly based on chemical *** most effective potential adsorption mechanisms were in order of electrostatic attraction and cation-πinteraction>surface complexation and precipitation>pore-filling and cation ***,the CRBs efficiently immobilized Cu^(2+)and reduced its bioavailability in *** results provide a promising strategy to remediate heavy metal-polluted water using designer biochars derived from biowastes,particularly animal carcasses.

关键词： Biowaste Pyrolytic temperature Immobilization Bioavailability Remediation

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Nonsingular Distributed Cooperative Guidance Law with Field-of-View Limits

Nonsingular Distributed Cooperative Guidance Law with Field...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Wang, Jianan Zhang, Haifeng Dong, Wei Wang, Chunyan Wu, Chengfeng Li, Hui Guo, Xiaoyun Beijing Institude of Technology Beijing10081 China Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing Institute of Mechanical and Electrical Engineering Beijing100074 China

ISBN: (纸本)9789811966125

A nonsingular cooperative guidance law is developed for multiple vehicles to strike a stationary target simultaneously under the seekers’ field-of-view (FOV) limited condition. First, a cooperative guidance law without considering the FOV limits is designed by augmenting the circular guidance law with a biased cooperative term based on the fixed-time convergent error dynamic. Then, a couple of auxiliary functions are inserted in the cooperative term to satisfy the FOV constraints and address the command singularity issue, respectively. With the developed guidance law, multiple vehicles can execute salvo attack missions with continuous guidance commands and without violating the FOV limits. Finally, the feasibility and performance of the cooperative guidance law are illustrated by numerical simulation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cooperative guidance law Field-of-view limits Fixed-time convergence Nonsingular command

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Transformer based Online Continuous Multi-Target Tracking with State Regression 12

Transformer based Online Continuous Multi-Target Tracking wi...

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12th IEEE International Conference on control, Automation and Information sciences, ICCAIS 2023

作者： Wei, Xinwei Chen, Linxiu Zhang, Chenyu Lin, Yiru Zhang, Linao Liu, Xiaokai Jiang, Jixiang Yi, Wei University of Electronic Science and Technology of China School of Information and Communication Engineering China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China University of Electronic Science and Technology of China Research Institute of Electronic Science and Technology China

ISBN: (纸本)9798350328783

Multi-target Tracking (MTT) is the process of processing received measurements to maintain estimates of the current status of multiple targets, with important applications to autonomous driving, aerial reconnaissance, underwater operations, and others. In the model-based setting, Bayesian filtering can provide the theoretical optimal estimate in a single target scenario. However, in complex situations, uncertain factors such as changes in the number of targets will cause the amount of calculation to increase exponentially, resulting in a decline in tracking accuracy. To solve that problem, model-free methods based on deep-learning provide an attractive alternative, especially the state-of-the-art architecture Transformer based encoder-decoder prediction model, which outperforms the Bayesian filters in the single frame prediction tasks. However, when switching to continuous tracking, these algorithms need to be trained separately frame by frame to adapt to the new tasks. Still, there is no correlation between their predictions from different frames, which prevents them from fully utilizing all the measurements. In this paper, we propose an end-to-end Transformer based MTT method with state autoregression, which allows the model to have the capability of online continuous tracking and make total use of the entire trajectory. The results show that the proposed model is a great extension from single-frame prediction to online continuous tracking. © 2023 IEEE.

关键词： Forecasting

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Torque effect on vibration behavior of high-speed train gearbox under internal and external excitations

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Railway engineering science 2024年第2期32卷 229-243页

作者： Yue Zhou Xi Wang Hongbo Que Rubing Guo Xinhai Lin Siqin Jin Chengpan Wu Yu Hou School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China CRRC Qishuyan Institute Co. Ltd.No.258Wuyi RoadQishuyanChangzhou 213011China Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong UniversityBeijing 100044China

The high-speed train transmission system,experiencing both the internal excitation originating from gear meshing and the external excitation originating from the wheel-rail interaction,exhibits complex dynamic behavior in the actual service *** paper focuses on the gearbox in the high-speed train to carry out the bench test,in which various operat-ing conditions(torques and rotation speeds)were set up and the excitation condition covering both internal and external was *** responses on multiple positions of the gearbox were acquired in the test and the vibration behavior of the gearbox was ***,a stochastic excitation modal test was also carried out on the test bench under different torques,and the modal parameter of the gearbox was ***,the sweep frequency response of the gearbox under gear meshing excitation was analyzed through dynamic *** results showed that the torque has an attenuating effect on the amplitude of gear meshing frequency on the gearbox,and the effect of external excitation on the gearbox vibration cannot be ignored,especially under the rated operating *** was also found that the torque affects the modal param-eter of the gearbox *** torque has a great effect on both the gear meshing stiffness and the bearing stiffness in the transmission system,which is the inherent reason for the changed modal characteristics observed in the modal test and affects the vibration behavior of the gearbox consequently.

关键词： High-speed train Gearbox Bench test Vibration behavior Modal identification

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Approximate state estimation with large-scale sensor networks under event-based sensor scheduling strategy 63

Approximate state estimation with large-scale sensor network...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Liu, Xinhui Cheng, Meiqi Shi, Dawei Shi, Ling Beijing Institute of Technology Miit Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Kowloon Hong Kong

ISBN: (纸本)9798350316339

In this paper, we investigate the issues of real-time sensor scheduling and state estimator design within large-scale sensor network systems. Specifically, data redundancy sometimes occurs in large-scale sensor arrays due to the excessive proximity of sensing units in the spatial domain, leading to high similarity in their measurement data. Currently, it is difficult to account for such redundancy in sensor scheduling algorithms found in existing literature, where the optimal subset of sensors is generally selected by optimizing objective functions formulated from certain performance criteria. To tackle this problem, we introduce an event-based sensor scheduling strategy, the triggering condition of which is designed founded on the similarity of sensor data, so as to identify the most informative subset of sensors for state estimation. To evaluate the impact of the sensor scheduling protocol on system observability, we propose a new notion of E(varepsilon)-observability, based on which an observability criterion is derived. In addition, we have designed a set-valued state estimation algorithm, which takes into account the intricate measurement information structure inherent within the sensor selection mechanism. The performance enhancement of the proposed estimator is also investigated. Finally, numerical experiments are conducted to validate the effectiveness of the proposed estimation algorithm and to verify the performance improvement. © 2024 IEEE.

关键词： Scheduling algorithms

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