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Arbitrary state transition of open qubit system based on switching control

Automatica 2025年 179卷

作者： Guangpu Wu Shibei Xue Shan Ma Sen Kuang Daoyi Dong Ian R. Petersen Department of Automation Shanghai Jiao Tong University Shanghai 200240 PR China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 PR China School of Automation Central South University Changsha 410083 PR China Department of Automation University of Science and Technology of China Hefei 230027 PR China Australian Artificial Intelligence Institute Faculty of Engineering and IT University of Technology Sydney Ultimo 2007 NSW Australia School of Engineering Australian National University Canberra ACT 2601 Australia

We present a switching control strategy based on Lyapunov control for arbitrary state transitions in open qubit systems. This strategy can prevent the state from entering invariant or singularity sets, effectively driving the system ultimately to a sufficiently small neighborhood of target states, which relaxes strict constraints on system models imposed by special target states compared to existing works. For the arbitrary transition, practical finite-time stability (PFTS) and its contractive version (PFTCS) conditions are given, respectively, where asymptotic stability is unattainable in open quantum systems in general. The efficacy of our method is demonstrated in examples of a qubit affected by amplitude damping, dephasing, and depolarizing decoherence.

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UAV Image Mosaicing Based Multi-Region Local Projection Deformation

UAV Image Mosaicing Based Multi-Region Local Projection Defo...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Quan Xu Linbo Luo Jun Chen Wenping Gong Donghai Guo School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan School of Automation China University of Geosciences Wuhan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Faculty of Engineering China University of Geosciences Wuhan

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

The goal of unmanned aerial vehicle (UAV) image mosaicing is to create natural-looking mosaics free of artifacts due to the parallax of the image and relative camera motion. UAV remote sensing is a low-altitude technology and the UAV imaged scene is not effectively planar, yielding parallax on images. In this paper, we apply local homography to match UAV images, which can reduce misalignment artifacts or “ghosting” in the results compared with 2D projective transforms or global homography. In addition, when an object in three dimensions is mapped to an image plane, different surfaces have different projections. These projections vary with the viewpoint in a sequence of UAV images, which still causes artifacts near some tall buildings if we only use local homography. We propose a novel stitching method based multi-region local projection deformation, that divides the overlapping regions of input images into several regions, then meshes image to calculate local projections by partitioned regions. Specifically, we use a strategy where multiple regions have different weights for calculating local projections, which can significantly reduce ghosting due to these projections vary with the viewpoint and parallax. The benefits of the proposed approach are demonstrated using a variety of challenging cases.

关键词： Unmanned aerial vehicles Remote sensing Geology Two dimensional displays Task analysis Buildings Transmission line matrix methods

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High-entropy alloys (HEAs) have emerged as a transformative class of materials in materials science, characterized by their multi-principal element compositionsSynthesis and Investigation of Powder and Magnetic Properties of AlFeNiCoMn High-Entropy Alloy Prepared by Mechanical Milling: Effect of Milling Time

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Materials Today Communications 2025年

作者： Büşra Tunç İlyas Somunkıran Serdar Özkaya Müslim Çelebi Aykut Çanakçı Artvin Çoruh University Borçka Acarlar Vocational School Department of Control and Automation Artvin Turkiye Fırat University Faculty of Technology School of Civil Aviation Department of Aircraft Maintenance and Repair Elazig Turkiye Karadeniz Technical University Department of Metallurgy and Materials Engineering Trabzon Turkiye

AlFeNiCoMn high-entropy alloy (HEA) powders were synthesised using mechanical alloying, and the effect of milling time on their microstructural evolution, mechanical behaviour, and magnetic properties was systematically investigated. The alloy powders were subjected to milling durations ranging from 1 to 15 h, and their morphological, crystallographic, and magnetic transformations were analysed using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), differential scanning calorimetry (DSC), Vickers hardness testing, and vibrating sample magnetometry (VSM). The results demonstrated that an increase in milling time led to significant particle refinement, enhanced homogeneity in elemental distribution, and a progressive phase transformation from individual elemental phases to a stable solid solution structure. This can be attributed to the repeated fracturing and cold welding of powders during milling, promoting diffusion and solid solution formation. XRD analysis confirmed a substantial decrease in crystallite size from 22.3 nm (5 h) to 7.8 nm (15 h), which is consistent with the intense plastic deformation and grain subdivision. The microhardness of the HEA powders increased from 260 HV at 1 h of milling to 680 HV at 15 h due to grain refinement, solid solution strengthening, and work hardening effects. Magnetic characterization revealed a decline in saturation magnetization (Ms), from 83.49 emu/g (0 h) to 66.84 emu/g (15 h), attributable to an increase in structural disorder and lattice strain that weakens magnetic exchange interactions. Conversely, coercivity (Hc) exhibited a substantial enhancement, from 85.6 Oe (0 h) to 228.5 Oe (15 h), due to increased grain boundary density and pinning effects caused by refinement. DSC analysis confirmed the thermal stability of the alloy powders above 200 °C, suggesting their suitability for high-temperature applications.

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Data-driven leak localization in water distribution networks via dictionary learning and graph-based interpolation

arXiv

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arXiv 2021年

作者： Irofti, Paul Romero-Ben, Luis Stoican, Florin Puig, Vicenç Department of Computer Science Faculty of Mathematics and Computer Science University of Bucharest Romania Institut de Robòtica i Informàtica Industrial Universitat Politècnica de Catalunya Barcelona Spain Politehnica University of Bucharest Dept. of Automation Control and Systems Engineering Romania

In this paper, we propose a data-driven leak localization method for water distribution networks (WDNs) which combines two complementary approaches: graph-based interpolation and dictionary classification. The former estimates the complete WDN hydraulic state (i.e., hydraulic heads) from real measurements at certain nodes and the network graph. Then, these actual measurements, together with a subset of valuable estimated states, are used to feed and train the dictionary learning scheme. Thus, the meshing of these two methods is explored, showing that its performance is superior to either approach alone, even deriving different mechanisms to increase its resilience to classical problems (e.g., dimensionality, interpolation errors, etc.). The approach is validated using the L-TOWN benchmark proposed at BattLeDIM2020. Copyright © 2021, The Authors. All rights reserved.

关键词： Water distribution systems

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A PCNN model for infrared pedestrian segmentation in complex environments

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Infrared Physics and Technology 2025年 149卷

作者： Cao, Honggui Ye, Bo Zou, Yangkun Zhu, Zhizhen Wan, Zijie Yin, Shsoda Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Yunnan Key Laboratory of Intelligent Control and Application Kunming650500 China Faculty of Civil Aviation and Aeronautics Kunming University of Science and Technology Kunming650500 China The First Military Representative Office of the Chongqing Military Representative Bureau of the Army Equipment Department Kunming650500 China

Pulse Coupled Neural Network (PCNN) is widely used in infrared pedestrian image segmentation. Due to the complex background, heat source interference, uneven brightness distribution of human targets and easy aliasing with the background in infrared pedestrian images, the segmentation of human targets is incomplete and the segmentation effect is poor. An improved PCNN algorithm for segmenting infrared pedestrian targets in complex environments and a new idea of preferentially segmenting background regions are proposed. The infrared pedestrian image is represented as a graph structure, and the superpixels in the infrared image are represented as nodes of the graph. The score of each node becoming the background region is evaluated by analyzing the structure of the graph, and the score is mapped to the original image as the connection strength of the model. Correspondingly, the dynamic threshold is set as the clustering center of the image background, and the background region of the image is prioritized for classification and output. Infrared pedestrian images with complex environment can be effectively segmented by the model, especially for infrared images with more heat source interference in the background. © 2025 The Authors

关键词： Image segmentation

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Autonomous Climbing Robot for Tank Inspection

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Procedia Computer Science 2019年 158卷 376-381页

作者： Özgür Acar Claudia F. YaŞar Control and Automation Engineering Faculty of Electrical and Electronics Engineering Yildiz Technical University Istanbul 34220 Turkey

A detailed design of mechanisms is presented, along with the required electromagnetic system to attach the robot to the tank’s wall. This is a novel mechanical design in which the robotic wheels rotate changing the instantaneous center of rotation. The robot mechanics is designed and simulated using Solidworks. The proposed electromagnetic system has to provide the necessary currents to control magnetic forces to be strong enough to attach the robot to the wall. However, because of the electromagnetic forces the control positioning method has to consider the strong Coulomb friction that appears against wheels movement. The sensor and acquisition system for navigation and control are also detailed. An inspection system has been proposed based on client/server architecture. Autonomous tracking and a mapping system powered by IMU sensor fusion is proposed. This design is suitable to be used along with the robot motion positioning strategy and, especially, the system must be robust to the disturbances and noise. The robot runs a server application and a remote PC is the client. The robot configuration has been developed with the capability of climbing up steel walls and navigating welding lines. The remote inspection system has been illustrated. A sensorial system and data fusion strategy to estimate the absolute robot position have been proposed. In order to track the desired trajectories, the robot’s kinematics is described. Some simulations of the position control of the wheels and the complete control for the tracking performance were simulated using Matlab/Simulink. This robotic system has demonstrated the capability to track an accurate trajectory given by the defined kinematic equations.

关键词： Wall climbing robot tank inspection autonomous robot sensor fusion position estimation non-destructive testing

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An Interpretability Analysis of Travel Decision Learning in Cyber-Physical-Social-Systems

An Interpretability Analysis of Travel Decision Learning in ...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Miao Guo Peijun Ye Xudong Liu Sheng Liu Gang Xiong Liguo Zhang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Information and Technology Beijing University of Technology Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

In the few decades, the rise of Internet and social media has fundamentally changed the management, control, and operation modes of modern engineering and social systems like defense, energy, critical health care and ... 详细信息

关键词： Deep learning Social networking (online) Scalability Perturbation methods Neurons Transportation Transforms

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H2 model reduction for diffusively coupled second-order networks by convex-optimization

arXiv

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arXiv 2021年

作者： Yu, Lanlin Cheng, Xiaodong Scherpen, Jacquelien M.A. Xiong, Junlin School of Electrical Engineering and Automation Hefei University of Technology Hefei230009 China Westlake Institute for Advanced Study Westlake University Hangzhou310024 China Department of Engineering University of Cambridge Trumpington Street CambridgeCB2 1PZ United Kingdom Jan C. Willems Center for Systems and Control Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Nijenborgh 4 Groningen9747 AG Netherlands Department of Automation University of Science and Technology of China Hefei230026 China

This paper provides an H2 optimal scheme for reducing diffusively coupled second-order systems evolving over undirected networks. The aim is to find a reduced-order model that not only approximates the input-output mapping of the original system but also preserves crucial structures, such as the second-order form, asymptotically stability, and diffusive couplings. To this end, an H2 optimal approach based on a convex relaxation is used to reduce the dimension, yielding a lower order asymptotically stable approximation of the original second-order network system. Then, a novel graph reconstruction approach is employed to convert the obtained model to a reduced system that is interpretable as an undirected diffusively coupled network. Finally, the effectiveness of the proposed method is illustrated via a large-scale networked mass-spring-damper system. Copyright © 2021, The Authors. All rights reserved.

关键词： Convex optimization

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Fast Calibration of Agent-Based Model using Mean-Field Approach

Fast Calibration of Agent-Based Model using Mean-Field Appro...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Wanze Lu Gang Xiong Xudong Liu Sheng Liu Peijun Ye Liguo Zhang Faculty of Information and Technology Beijing University of Technology Beijing China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Beijing China

Calibration of simulation system is an important step to establish a reliable simulation system. In this paper, based on the existing mean field calibration theory, a new fast calibration method for complex urban traffic system based on mean field method is discussed by establishing the relationship between the macroscopic observation quantity and the proxy microscopic parameters. This method makes use of the machine learning method, and reduces the dimension of the state vector in the discrete time period, so that the dimension of the macroscopic state transition matrix is lower, and then reduces the computational complexity of the system calibration. Finally, the calibration results of the simulation system were verified by SUMO traffic simulation software.

关键词： Visualization Computational modeling Microscopy Digital twin Machine learning Traffic control Reliability theory

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Pinning boundary sampled-data synchronization of coupled reaction–diffusion neural networks

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Neurocomputing 2025年 648卷

作者： Zi-Peng Wang Bo-Ming Chen Junfei Qiao Biao Luo Huai-Ning Wu Tingwen Huang Guangwei Chen School of Information Science and Technology Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System and Beijing Institute of Artificial Intelligence Beijing University of Technology Beijing 100124 China School of Automation Central South University Changsha 410083 China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen 518107 China

In this paper, the pinning boundary sampled-data (SD) synchronization problem of coupled reaction–diffusion neural networks (CRDNNs) with SD-based couplings is investigated under boundary and distributed SD measurements. First, a pinning boundary SD controller is designed to effectively address the synchronization problem of CRDNNs, utilizing boundary and distributed SD measurements and requiring only a small number of sensors and actuators. Then, linear matrix inequalities provide adequate conditions that ensure exponential stability of the synchronization error system by using the designed pinning boundary SD controller, derived through inequality techniques and Lyapunov functionals. Finally, we present a numerical example to showcase the practical applicability and effectiveness of the proposed pinning boundary SD synchronization method.

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