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Optoelectronics Global Conference (OGC)

作者： Luonan Chang Hang Du Bowen Zhan Ruike Guo Peng Zhou Zexin Wang Danni Liang Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing China

ISBN: (数字)9798350391466

ISBN: (纸本)9798350391473

Images collected by linear scan cameras are stretched and compressed due to the speed regulation of targets. This condition changes the target morphology and considerably affects the accuracy of subsequent image tasks such as target detection and tracking. Affine transformation matrix is the priority in fields of image alignment, registration and correction, to solve the mapping relationship between pixels. However, in practical engineering applications such as aerospace circular scanning camera imaging, through-type scanning high-speed train body fault detection, and industrial circuit board assembly line fault detection, the scanning rate of linear scan camera cannot be adaptively adjusted in real time according to the target speed, resulting in deformations of various scales in the sequence image. A unified affine matrix solution for the entire image cannot solve the problem of target scales with regional differences. Therefore, a deep-feature-matching-based piecewise polynomial transformation for multi-domain nonlinear scale distortion image correction method is innovatively proposed, to achieve one-to-one correspondence between deformed images and standard images at the pixel level. First, a feature matching algorithm based on deep feature extraction, driven by big dataset, is integrated with graph convolution and optimal matching to achieve high-precision matching of two images, which performs well in illumination, weak texture, and similar features confusion. Second, an image block algorithm based on sparse feature clustering is adopted, which applies k-means clustering to sparsely reduce the dimensionality of dense feature points to maintain a good balance between speed and accuracy. Third, a novel image correction method based on piecewise polynomial trajectory planning is proposed, which converts the multi-domain nonlinear scale distortion image correction into robot multi-segment path planning. This strategy optimizes the coordinate standardization formul

关键词： Accuracy Transmission line matrix methods Trajectory planning Robot kinematics Nonlinear distortion Clustering algorithms Feature extraction Cameras Polynomials Remote sensing

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A Multi-constrained Adaptive Predictor–Corrector Guidance Method for Ascent Phase of Hypersonic Vehicle

A Multi-constrained Adaptive Predictor–Corrector Guidance M...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Maomao, Li Jun, Hu Huang, Huang Ruike, Guo Beijing Institute of Control Engineering Beijing100190 China The Science and Technology on Space Intelligent Control Laboratory Beijing100190 China

ISBN: (纸本)9789811581540

In this paper, considering the various terminal states constraints, and coupling of different states in the ascent phase of the hypersonic aircraft, a multi-constrained guidance method based on predictor–corrector policy is proposed. Firstly, the dynamic equations of ascent phase are given. And then, the dynamic amplification factors for the various flight states are calculated. Analyzing the dynamic equations of ascent phase, it can be found that only the attack angle is used to control various states and the guidance of ascent phase is an under-driven problem. The path angles are small values at the terminal flight phase, and it has little couple influence on the altitude. In order to solve the under-driven problem, the whole ascent phase has two parts. At the initial phase, eliminating the terminal height error is chosen as the guidance object. At the terminal phase, eliminating the path angle error at the end point is chosen as the guidance object. What’s more, the influence of choosing different segmentation altitude on the terminal states errors is analyzed. Moreover, the Monte Carlo simulation demonstrates the effectiveness of the proposed multi-constrained adaptive predictor–corrector guidance method. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Hypersonic vehicles

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Fuzzy Dynamic Bayesian Network Based Threat Assessment Model for space Targets 5

Fuzzy Dynamic Bayesian Network Based Threat Assessment Model...

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5th International Conference on Pattern Recognition and Artificial intelligence, PRAI 2022

作者： Li, Jiaxing Yuan, Li Zhang, Cong Yan, Han Sun, Dong Beijing Institute of Control Engineering Beijing China Beijing Institute of Control Engineering Science and Technology on Space Intelligent Control Laboratory Beijing China

ISBN: (数字)9781665499163

ISBN: (纸本)9781665499163

To assess threat levels of the space target, a fuzzy Dynamic Bayesian Network is used to fuse space target characteristics. Firstly, considering the fact that input information of the threat assessment model is incomplete and uncertain, motion characteristics of the space target are used to infer hidden characteristics, and these characteristics are treated as nodes of the Dynamic Bayesian Network (DBN). After defining the causal relationships of these characteristics using conditional probability tables, the DBN is constructed, and the threat level reasoning process is briefly mentioned. Then, by constructing three fuzzy membership functions, the continuous information is converted into discrete evidence information that the DBN can use. Finally, the whole threat level assessment process is given, and numerical simulations are used to verify the designed model in different scenarios. Results show the model can quantify the change of space target threat level reasonably and distinguish differences in threat levels under different scenarios. © 2022 IEEE.

关键词： Bayesian networks

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Reconfigurable Nanobook Structure Driven by Polymerase-Triggered DNA Strand Displacement 1

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17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Chen, Kuiting Chen, Zhekun Xie, Chun Pan, Linqiang Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Due to its high degree of customization, DNA origami provides a versatile platform with which to engineer nanoscale structures and devices. Reconfigurable nanodevices driven by DNA strand displacement accomplish the task of transition between different conformations, endowing DNA origami with application values. Herein, we propose a strategy to regulate the conformation of DNA origami using the polymerase-triggered DNA strand displacement (PTSD) reaction. We design a book-shaped DNA origami structure consisting of four pages connected into a cuboid shape. The PTSD reactions initiated by different primer strands selectively remove the connecting strand, transforming the nano book into a two-page or a four-page conformation. We utilize three primer strands to remove thirty-five connecting strands and construct three conformations of the identical DNA origami, illustrating that the PTSD reaction is an effective tool for the reconfiguration of DNA origami. The statistical results of TEM images prove the effectiveness of the proposed method. Our work on the development of PTSD-driven reconfigurable nanostructure will offer a new way to create intelligent materials for advanced nanotechnology applications. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： DNA

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Transfer learning with a spatiotemporal graph convolution network for city flowprediction

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Frontiers of Information technology & Electronic Engineering 2025年第1期26卷 79-92页

作者： Binkun LIU Yu KANG Yang CAO Yunbo ZHAO Zhenyi XU Department of Automation University of Science and Technology of ChinaHefei 230026China Key Laboratory of System Control and Information Processing Ministry of EducationShanghai 200240China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China Institute of Advanced Technology University of Science and Technology of ChinaHefei 230088China

Recently,deep learning based city flow prediction has been extensively used in the establishment of *** methods are data-hungry,making them unscalable to areas lacking *** transfer learningcan use data-rich source domains to assist target domain cities in city flow prediction,the performance of existingmethods cannot meet the needs of actual use,because the long-distance road network connectivity is *** this problem,we propose a transfer learning method based on spatiotemporal graph convolution,in which weconstruct a co-occurrence space between the source and target domains,and then align the mapping of the sourceand target domains’data in this space,to achieve the transfer learning of the source city flow prediction modelon the target ***,a dynamic spatiotemporal graph convolution module along with a temporalencoder is devised to simultaneously capture the concurrent spatiotemporal features,which implies the inherentrelationship among the road network structures,human travel habits,and city bike ***,these concurrentfeatures are leveraged as cross-city invariant representations and nonlinearly spanned to a co-occurrence *** domain features are thereby aligned with the source domain features in the co-occurrence space by using aMahalanobis distance loss,to achieve cross-city bike flow *** proposed method is evaluated on the publicbike flow datasets in Chicago,New York,and Washington in 2015,and significantly outperforms state-of-the-arttechniques.

关键词： Transfer learning City flow prediction Spatiotemporal graph convolution

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Bearing Remaining Useful Life Prediction Combining Trajectory Similarity and Relevance Vector Machine 41

Bearing Remaining Useful Life Prediction Combining Trajector...

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第41届中国控制会议

作者： Zhuyi Li Kesen Fan Cong Zhang Sihang Zhang Yiming Wan Key Laboratory of Image Processing and Intelligent Control Ministry of Education Chinaand School of Artificial Intelligence and AutomationHuazhong University of Science and Technology Beijing Institute of Control Engineering

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Bearing remaining useful life(RUL) prediction is critical for safe operation of rotating *** this paper,we propose a combined RUL prediction approach that leverages both trajectory similarity and relevance vector machine(RVM).The similarity based prediction relies on historical degradation trajectories that are highly similar to the online data,hence would perform poorly if all historical trajectories have low similarity with the online *** RVM based prediction relies solely on a regression model learned from the available online data,thus gives an inaccurate prediction when insufficient data are available in the early stage of degradation.A weighted sum of these above two predictions is proposed to address the limitation of each single prediction method,whose weights are determined by solving a non-negative least squares fitting *** further improve RUL prediction accuracy,we distinguish between fast and slow degradation modes,so that each mode uses a different set of historical degradation trajectories and kernel *** doing so,we predict RUL under the identified *** case study using the PHM2012 dataset demonstrates the effectiveness of the proposed RUL prediction approach.

关键词： Bearing degeneration remaining useful life prediction relevance vector machine trajectory similarity

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Optimizing Energy Consumption for Legged Robot by Adapting Equilibrium Position and Stiffness of a Parallel Torsion Spring

Optimizing Energy Consumption for Legged Robot by Adapting E...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Belov, Danil Erkhov, Artem Khabibullin, Farit Pestova, Elisaveta Satsevich, Sergei Osokin, Ilya Osinenko, Pavel Tsetserukou, Dzmitry Skolkovo Institute of Science and Technology Intelligent Space Robotics Laboratory and Artificial Intelligence in Dynamic Action Laboratory Bolshoy Boulevard 30 bld. 1 Moscow121205 Russia Cognitive Modeling Center Moscow Institute of Physics and Technology Institutsky Lane 9 Dolgoprudny141701 Russia

ISBN: (纸本)9781665481090

This paper is dedicated to the development of a novel adaptive torsion spring mechanism for optimizing energy consumption in legged robots. By adjusting the equilibrium position and stiffness of the spring, the system improves energy efficiency during cyclic movements, such as walking and jumping. The adaptive compliance mechanism, consisting of a torsion spring combined with a worm gear driven by a servo actuator, compensates for motion-induced torque and reduces motor load. Simulation results demonstrate a significant reduction in power consumption, highlighting the effectiveness of this approach in enhancing robotic locomotion. © 2024 IEEE.

关键词： Worm gears

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Spatiotemporal distance embedded hybrid ant colony algorithm for a kind of vehicle routing problem with constraints

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Frontiers of Information technology & Electronic Engineering 2023年第7期24卷 1062-1079页

作者： Zhenhui FENG Renbin XIAO School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Institute of Artificial Intelligence Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Information Processing and Intelligent Control Ministry of EducationWuhan 430074China

We investigate a kind of vehicle routing problem with constraints(VRPC)in the car-sharing mobility environment,where the problem is based on user orders,and each order has a reservation time limit and two location point transitions,origin and *** is a typical extended vehicle routing problem(VRP)with both time and space *** consider the VRPC problem characteristics and establish a vehicle scheduling model to minimize operating costs and maximize user(or passenger)*** solve the scheduling model more accurately,a spatiotemporal distance representation function is defined based on the temporal and spatial properties of the customer,and a spatiotemporal distance embedded hybrid ant colony algorithm(HACA-ST)is *** algorithm can be divided into two ***,through spatiotemporal clustering,the spatiotemporal distance between users is the main measure used to classify customers in categories,which helps provide heuristic information for problem ***,an improved ant colony algorithm(ACO)is proposed to optimize the solution by combining a labor division strategy and the spatiotemporal distance function to obtain the final scheduling *** analysis is carried out based on existing data sets and simulated urban *** with other heuristic algorithms,HACA-ST reduces the length of the shortest route by 2%–14%in benchmark *** VRPC testing instances,concerning the combined cost,HACA-ST has competitive cost compared to existing VRP-related ***,we provide two actual urban scenarios to further verify the effectiveness of the proposed algorithm.

关键词： Vehicle routing problem with constraints(VRPC) Spatiotemporal distance function Labor division strategy Ant colony algorithm(ACO)

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Practical Distance-Based Formation Stabilization and Tracking of Nonholonomic Multi-agent Systems 7th

Practical Distance-Based Formation Stabilization and Tracki...

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7th Chinese Conference on Swarm intelligence and Cooperative control, CCSICC 2023

作者： Tang, Xiangyu Yu, Jianglong Dong, Xiwang Yang, Xiangyu Ren, Zhang School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819733279

This paper investigates practical distance-based formation stabilization and tracking issues for nonholonomic multi-agent systems (MASs). Firstly, the agent’s nonholonomic kinematics is represented as a left invariant system on a Lie group. Through the introduction of an auxiliary state and a virtual control guided by the transverse function method, the original system is effectively converted into a fully actuated one. Secondly, under the assumption of infinitesimal and minimal rigidity in the graph, a gradient-descent-based virtual controller is devised for the transformed MASs, facilitating practical rigid formation stabilization. Thirdly, a discontinuous distributed velocity estimator is designed for formation tracking. The nonholonomic MASs achieve the desired formation shape while effectively tracking the reference trajectory. Finally, the effectiveness of the proposed method is verified by numerical examples. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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Adaptive Prescribed-Time Distributed Nash Equilibrium Seeking for Networked Games with Heterogeneous Dynamics and Unknown Uncertainties

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IEEE Transactions on control of Network Systems 2025年

作者： Chen, Yiyang Hua, Yongzhao Feng, Zhi Dong, Xiwang Beihang University School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Shenyuan Honors College Beijing100191 China Beihang University School of Artificial Intelligence Institute of Artificial Intelligence Beijing100191 China Beihang University School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beijing100191 China Beihang University Institute of Unmanned System School of Artificial Intelligence Institute of Artificial Intelligence School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beijing100191 China

This paper investigates the adaptive prescribed-time distributed Nash equilibrium (NE) seeking problems for networked games with heterogeneous dynamics and unknown uncertainties. The proposed algorithms are based on the two-layer structure, namely the NE seeking part and the tracking control part. For the players without uncertainties, the adaptive parameters are utilized in the seeking part to avoid the use of the global information. The auxiliary variables are constructed to seek for the NE point within the prescribed time and serve as the reference signals for the tracking control part. Then the state feedback control is designed to drive the strategies of all the players to the expected NE point in the prescribed time. Furthermore, the approximation theory is introduced to deal with the unknown nonlinear uncertainties. The exponential parameters are involved in the designed estimates to accelerate the convergence rate. The Lyapunov method is utilized to show the prescribed-time convergence property of the algorithms. Besides, although the time-varying piecewise function is involved in the algorithms, the uniform boundedness of the control input can be ensured by carefully selecting the initial values of the auxiliary parameters. Finally, the simulation is given to show the effectiveness of the proposed algorithms. © 2025 IEEE.

关键词： Lyapunov methods

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