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International Conference on Robotics and Automation engineering (ICRAE)

作者： Guo-Biao Wang Hong-Sen Yan School of Automation Southeast University Nanjing Jiangsu China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing Jiangsu China

This paper addresses the stabilization problem of time-varying delay systems subject to actuator saturation. A novel class of Lyapunov functional with a nonlinear metric is developed to guarantee that there exists a Lyapunov-Razumikhin function that strictly decreases for the controlled system. Such a nonlinear metric is parameterized by a multi-dimensional Taylor network with concise topology, which brings into the high-order dynamic information and guarantees real-time performance. A sum-of-squares programming approach based on the designed Lyapunov functional is formulated to deduce the stability criteria, which maximizes the estimate of the region of attraction and ensures the uniform asymptotic stability of the closed-loop system theoretically. A numerical example demonstrates the effectiveness of the proposed stabilization control scheme.

关键词： measurement Actuators Asymptotic stability Delay systems Stability criteria Programming Real-time systems

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A Robot Coordinate measurement System Based on Pull Wire Sensor and Its Parameter Identification Method 12

A Robot Coordinate Measurement System Based on Pull Wire Sen...

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12th International Conference on CYBER Technology in Automation, control, and Intelligent systems, CYBER 2022

作者： Gao, Shuang Ma, Kaiwei Gao, Yang Shen, Xin Yang, Mingxing Xu, Fengyu College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Jiangsu Nanjing China Anhui Province Key Laboratory of Special Heavy Load Robot Anhui Maanshan China College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications Jiangsu Nanjing China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Aiming at the problems of large robot error and difficult coordinate detection, a robot coordinate measurement system and parameter identification method based on pull wire sensor are proposed. Firstly, a robot coordinate measurement system based on pull wire sensor is established. Secondly, Levenberg-Marquarelt algorithm is used to solve the kinematics parameters of the robot. Finally, the neural network of the whole connection layer is used to predict the optimal compensation amount for secondary compensation. In order to verify the above theory, the robot coordinate measurement system is built and verified on the five degree of freedom robot experimental platform. The results show that the robot coordinate measurement system can measure the robot coordinates quickly and accurately. The secondary compensation method controls the accuracy of the robot to about 2mm, and the optimal error is controlled within 0.012mm. The absolute positioning accuracy of the robot is effectively improved. © 2022 IEEE.

关键词： Robots

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Double STAR-RIS Enhanced Secure Wireless Communications

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IEEE Transactions on Wireless Communications 2025年

作者： Cai, Yujin Yu, Wenwu Nie, Xiaokai Cheng, Qiang Cui, Tiejun Southeast University School of Mathematics Jiangsu Nanjing211189 China Purple Mountain Laboratories Nanjing211111 China Southeast University School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Southeast University Shenzhen Research Institute Shenzhen518057 China Southeast University State Key Laboratory of Millimeter Waves Nanjing210096 China

Simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs) have recently been employed to enhance the secure transmission due to the ability to manipulate the full-space electromagnetic signals. Prior works mainly investigate the single STAR-RIS aided secure communication system, which does not reveal the potential of the cooperative inter-STAR-RIS link. In this paper, a double STAR-RIS enhanced secure communication network involving multiple legitimate users (LUs) and eavesdroppers (Eves) is proposed. For fairness, the minimum secrecy rate maximization problem is formulated by jointly optimizing the active beamforming and passive transmission and reflection (T&R) beamforming. To deal with the highly non-convex nonlinear optimization problem, an active and passive beamforming optimization algorithm is proposed by employing the alternating optimization method. Wherein, a low-complexity sequential constraint relaxation (SCR) based algorithm is designed to solve the passive T&R beamforming optimization problem. Simulation results demonstrate that the secure performance in the double STAR-RIS assisted system outperforms that in the single RIS/double RIS/single STAR-RIS aided network. Furthermore, the proposed algorithm significantly reduces computational time (i.e., resource allocation time) compared with the traditional SCR based beamforming optimization algorithm. © 2002-2012 IEEE.

关键词： Cooperative communication

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Probabilistic Decomposition Transformer for Time Series Forecasting

SSRN

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SSRN 2022年

作者： Tong, Junlong Xie, Liping Yang, Wankou Zhang, Kanjian School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing 210096 China

Time series forecasting is crucial for many fields, such as disaster warning, weather prediction, and energy consumption. The Transformer-based models are considered to have revolutionized the field of sequence modeling. However, the complex temporal patterns of the time series hinder the model from mining reliable temporal dependencies. Furthermore, the autoregressive form of the Transformer introduces cumulative errors in the inference step. In this paper, we propose the probabilistic decomposition Transformer model that combines the Transformer with a conditional generative model, which provides hierarchical and interpretable probabilistic forecasts for intricate time series. The Transformer is employed to learn temporal patterns and implement primary probabilistic forecasts, while the conditional generative model is used to achieve non-autoregressive hierarchical probabilistic forecasts by introducing latent space feature representations. In addition, the conditional generative model reconstructs typical features of the series, such as seasonality and trend terms, from probability distributions in the latent space to enable complex pattern separation and provide interpretable forecasts. Extensive experiments on several datasets demonstrate the effectiveness and robustness of the proposed model, indicating that it compares favorably with the state of the art. © 2022, The Authors. All rights reserved.

关键词： Time series

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Optimizing Bounding Box Regression in complex Backgrounds

Optimizing Bounding Box Regression in Complex Backgrounds

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2024 China Automation Congress, CAC 2024

作者： Chen, Jun Zhang, Haiyan Yu, Anjun Wang, Yiwei 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 Wuhan430074 China Jiangxi Ganyue Expressway Co.Ltd. Nanchang China School of Automation China University of Geosciences Wuhan430074 China

ISBN: (纸本)9798350368604

In the context of electrical power operation sites, the automated and accurate detection of whether workers are properly equipped with safety gear, such as safety clothing, helmets, and safety ropes for high-altitude operations, is crucial for ensuring the safety of personnel. Traditional object detection models often struggle to accurately identify these critical pieces of safety equipment in complex environments, due to variable object sizes, overlapping objects, and substantial background noise. To specifically address these challenges, we propose a novel loss function-Enhanced Alignment Intersection over Union (EAIoU) loss. This loss function is designed to enhance the model’s ability to discriminate between closely spaced and overlapping safety gear in real-time, significantly improving robustness against scale variations and complex backgrounds. In experiments based on the YOLOv8s architecture, our model achieved a mean Average Precision (mAP) of 92.1% on a dataset specific to electrical power operations, markedly outperforming traditional IoU loss functions. Additionally, EAIoU demonstrated improved performance on the COCO dataset, indicating its generalization capability across various complex scenarios. This research not only enhances the accuracy and real-time performance of safety equipment detection at electric power operation sites but also opens new avenues for advanced object detection technology in complex, multi-object environments. © 2024 IEEE.

关键词： Safety devices

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Transformer Based Multi-modal Fusion For Place Recognition with Self-attention Mechanism

Transformer Based Multi-modal Fusion For Place Recognition w...

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Chinese Automation Congress (CAC)

作者： Yan Pan Xiang Yu Zeqing Chang Fang Fang Bo Zhou Key Laboratory of Measurement and Control of Complex Systems of Engineering School of Automation Southeast University Ministry of Education Nanjing P. R. China

Autonomous driving still leaves a challenging task that how to apply the complementary information captured from different sensors, i.e. cameras and LiDAR, to handle place recognition task. In this paper, a brand new pipeline was designed to tackle the retrieval problem with a multi-modal late fusion. The light-weighted convolutional blocks is applied to encode features from images, followed by converting them into pseudo point clouds. Inspired by the progress of the Transformer, the network employs a residual point transformer module to extract feature vectors for 3D points and pseudo point clouds respectively. Finally, the two corresponding local descriptors are fused to get a robust fused global descriptor, which is capable of place recognition task after end-to-end training. Experimental results collected from sequence 00, 02, 05, 06 of KITTI dataset validate that fusing information from two modalities is able to enhance performance.

关键词： Point cloud compression Training Laser radar Three-dimensional displays Streaming media Transformers Feature extraction

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Phase-Shifting Coder: Predicting Accurate Orientation in Oriented Object Detection

arXiv

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arXiv 2022年

作者： Yu, Yi Da, Feipeng School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

With the vigorous development of computer vision, oriented object detection has gradually been featured. In this paper, a novel differentiable angle coder named phase-shifting coder (PSC) is proposed to accurately predict the orientation of objects, along with a dual-frequency version (PSCD). By mapping the rotational periodicity of different cycles into the phase of different frequencies, we provide a unified framework for various periodic fuzzy problems caused by rotational symmetry in oriented object detection. Upon such a framework, common problems in oriented object detection such as boundary discontinuity and square-like problems are elegantly solved in a unified form. Visual analysis and experiments on three datasets prove the effectiveness and the potentiality of our approach. When facing scenarios requiring high-quality bounding boxes, the proposed methods are expected to give a competitive performance. The codes are publicly available at https://***/open-mmlab/mmrotate. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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Matrix-injection-based transformation method for discrete-time systems with time-varying delay

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Science China(Information Sciences) 2023年第5期66卷 289-290页

作者： Chuan-Ke ZHANG Ke-You XIE Yong HE Jinhua SHE Min WU 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 School of Engineering Tokyo University of Technology

Dear editor,In order to identify the influence of time-varying delays on the stability of control systems represented in a discretetime mode, developing stability criteria of discrete-time delayed systems has received serious attention in the past few decades (see [1–3] and their references).Consider the following linear discrete-time system with a time-varying delay:

关键词： Lyapunov functions

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Parallax-Tolerant Image Stitching with Epipolar Displacement Field

arXiv

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arXiv 2023年

作者： Yu, Jian Da, Feipeng School of Automation Southeast University No.2 Sipailou Jiangsu Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education No.2 Sipailou Jiangsu Nanjing210096 China

Image stitching with parallax is still a challenging task. Existing methods often struggle to maintain both the local and global structures of the image while reducing alignment artifacts and warping distortions. In this paper, we propose a novel approach that utilizes epipolar geometry to establish a warping technique based on the epipolar displacement field. Initially, the warping rule for pixels in the epipolar geometry is established through the infinite homography. Subsequently, the epipolar displacement field, which represents the sliding distance of the warped pixel along the epipolar line, is formulated by thin-plate splines based on the principle of local elastic deformation. The stitching result can be generated by inversely warping the pixels according to the epipolar displacement field. This method incorporates the epipolar constraints in the warping rule, which ensures high-quality alignment and maintains the projectivity of the panorama. Qualitative and quantitative comparative experiments demonstrate the competitiveness of the proposed method for stitching images with large parallax. Copyright © 2023, The Authors. All rights reserved.

关键词： Pixels

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热-电-弹压电/石墨烯复合纳米板在粘弹性地基上的非线性受迫振动

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Acta Mechanica Sinica 2023年第3期39卷 142-152页

作者：赵云平侯秀慧张硕孙彤彤都琳邓子辰 Department of Applied Mathematics Northwestern Polytechnical UniversityXi'an 710072China Deparment of Engineering Mechanics Northwestern Polytechnical University Xi'an 710072China Ministry of Industry and Information Technology Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical UniversityXi'an 710072China

本文研究了非对称压电/石墨烯复合纳米板在粘弹性地基上、热环境及外部简谐激励作用下的动力学行为.根据Hamilton原理和Kirchhoff板理论,建立复合纳米板的动力学方程,并通过Galerkin方法对简支边界下的动力学方程进行求解,获得了一个包... 详细信息

本文研究了非对称压电/石墨烯复合纳米板在粘弹性地基上、热环境及外部简谐激励作用下的动力学行为.根据Hamilton原理和Kirchhoff板理论,建立复合纳米板的动力学方程,并通过Galerkin方法对简支边界下的动力学方程进行求解,获得了一个包含有二次非线性项的Duffing-Helmholtz方程.从解析和数值方面分别分析了非局部弹性参数、温度、粘弹性基体、电压以及纳米板的几何尺寸对系统非线性与线性频率比和非线性振动行为的影响.此外,本文揭示了系统的非对称性和二次非线性项之间的对应关系.本研究的动力学结果将为压电-石墨烯复合纳米谐振器力学性能的实验表征提供理论依据.

关键词： Asymmetric piezoelectric-graphene composite nanoplate Thermal environment Nonlinear forced vibration Wave number

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