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SSRN 2024年

作者： Li, Yanhong Chen, Qiujin Zhang, Jing Zhu, Yinian Zhu, Zongqiang Wang, Yaru Tang, Shen College of Environmental Science and Engineering Guilin University of Technology Guilin541004 China Guangxi Key Laboratory of Environmental Pollution Control Theory and Technology Guilin University of Technology Guilin541004 China

The negative impact of chlorpyrifos (CPF) on public safety and ecosystems is serious, and the potential of bioremediation should not be underestimated. Still, there are few studies on the degradation mechanism and pesticide intermediates. This study conducted a series of experiments to investigate the degradation performance and mechanism of CPF degradation by S. oneidensis MR-1. The results of degraded CPF showed that the degradation effect of S. oneidensis MR-1 on CPF was the best with the inoculation amount of 20%, pH7, 35 ℃, and the salinity of 10 g/L. The degradation rate of CPF by S. oneidensis MR-1 was greatly increased to 74.12% after the addition of anthraquinone 2,6-disulfonate sodium (AQDS) and goethite. SEM results showed the goethite surface might provide a dense reaction site for the degradation of CPF. XRD and FTIR analysis revealed the functional group changes during the degradation of CPF, mainly the hydroxyl group, XPS analysis showed that the addition of AQDS and goethite promoted the degradation of CPF and the conversion of Fe (III). Degradation product analysis deduced two possible degradation pathways for CPF. Through the analysis and comparison of metabolites, the biosynthesis of the amino acid metabolism pathway, and lipids in S. oneidensis MR-1 increased under CPF stress, which indicated that S. oneidensis MR-1 was regulated by cellular antioxidant stress, coupled with the increase in LNT production. The above results indicated that AQDS and goethite addition accelerated electron transport and efficient degradation in the process of CPF degradation by S. oneidensis MR-1. © 2024, The Authors. All rights reserved.

关键词： Degradation

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Robust Divergence Learning for Missing-Modality Segmentation

arXiv

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arXiv 2024年

作者： Cheng, Runze Sun, Zhongao Zhang, Ye Li, Chun MSU-BIT-SMBU Joint Research Center of Applied Mathematics Shenzhen MSU-BIT University Shenzhen518172 China Institute of Control Theory and Control Engineering School of Automation Beijing Institute of Technology Beijing100081 China School of Mathematics and Statistics Beijing Institute of Technology Beijing100081 China

Multimodal Magnetic Resonance Imaging (MRI) provides essential complementary information for analyzing brain tumor subregions. While methods using four common MRI modalities for automatic segmentation have shown success, they often face challenges with missing modalities due to image quality issues, inconsistent protocols, allergic reactions, or cost factors. Thus, developing a segmentation paradigm that handles missing modalities is clinically valuable. A novel single-modality parallel processing network framework based on Hölder divergence and mutual information is introduced. Each modality is independently input into a shared network backbone for parallel processing, preserving unique information. Additionally, a dynamic sharing framework is introduced that adjusts network parameters based on modality availability. A Hölder divergence and mutual information-based loss functions are used for evaluating discrepancies between predictions and labels. Extensive testing on the BraTS 2018 and BraTS 2020 datasets demonstrates that our method outperforms existing techniques in handling missing modalities and validates each component’s effectiveness. © 2024, CC BY.

关键词： Magnetic resonance imaging

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An $\mathcal{L}_{\mathrm{p}}$ -norm framework for event-triggered control

An $\mathcal{L}_{\mathrm{p}}$ -norm framework for event-trig...

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European control Conference (ECC)

作者： Michael Hertneck Alejandro I. Maass Dragan Nešić Frank Allgöwer University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart Germany Department of Electrical Engineering Pontificia Universidad Catolica de Chile Santiago Chile Department of Electrical and Electronic Engineering The University of Melbourne Parkville Victoria Australia

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper presents a novel event-triggered control (ETC) design framework based on measured $\mathcal{L}_{p}$ norms. We consider a class of systems with finite $\mathcal{L}_{p}$ gain from the network-induced error to a chosen output. The $\mathcal{L}_{p}$ norms of the network-induced error and the chosen output since the last sampling time are used to formulate a class of triggering rules. Based on a small-gain condition, we derive an explicit expression for the $\mathcal{L}_{p}$ gain of the resulting closed-loop systems and present a time-regularization, which can be used to guarantee a lower bound on the inter-sampling times. The proposed framework is based on a different stability- and triggering concept compared to ETC approaches from the literature, and thus may yield new types of dynamical properties for the closed-loop system. However, for specific output choices it can lead to similar triggering rules as “standard” static and dynamic ETC approaches based on input-to-state stability and yields therefore a novel interpretation for some of the existing triggering rules. We illustrate the proposed framework with a numerical example from the literature.

关键词： Europe Closed loop systems Numerical stability Standards

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A Review of UAV Power Line Inspection

A Review of UAV Power Line Inspection

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Wang, Zhaoyang Gao, Qiang Xu, Jianbin Li, Dahua School of Electrical & Electronic Engineering and Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China Sanyuan Electric Equipment Manufacturing Co. Ltd Tianjin300409 China

ISBN: (纸本)9789811581540

In recent years, unmanned aerial vehicles (UAVs) have begun to enter human life as a new type of tool, they have played a large role in various industries, and the power industry is no exception. The normal operation of the power system requires prudential inspection. Traditional methods such as manual inspection have nonnegligible disadvantages, so more and more power companies have begun to use UAVs instead of manual inspection. In this paper we analyzed the development history and advantages of UAV power line inspection, and showed the composition and classification of UAV power line inspection system, as well as the current circumstances. Next, according to the type of UAV, the task of power line inspection is described. Then, based on the requirements of the power line inspection task, the inspection methods and key technologies of the UAV are described. Finally, challenges such as safety, endurance time, and automation that have emerged during the development of UAV power inspections are proposed. We analyze the prospects of UAV power inspection technology from how some companies are responding to these challenges. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Inspection

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Lipschitz-Bounded 1D Convolutional Neural Networks using the Cayley Transform and the controllability Gramian

Lipschitz-Bounded 1D Convolutional Neural Networks using the...

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IEEE Conference on Decision and control

作者： Patricia Pauli Ruigang Wang Ian R. Manchester Frank Allgöwer Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Australia

We establish a layer-wise parameterization for 1D convolutional neural networks (CNNs) with built-in end-to-end robustness guarantees. In doing so, we use the Lipschitz constant of the input-output mapping characterized by a CNN as a robustness measure. We base our parameterization on the Cayley transform that parameterizes orthogonal matrices and the controllability Gramian of the state space representation of the convolutional layers. The proposed parameterization by design fulfills linear matrix inequalities that are sufficient for Lipschitz continuity of the CNN, which further enables unconstrained training of Lipschitz-bounded 1D CNNs. Finally, we train Lipschitz-bounded 1D CNNs for the classification of heart arrythmia data and show their improved robustness.

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Performance Optimization of Angle-Based Network Localization

Performance Optimization of Angle-Based Network Localization

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IEEE Conference on Decision and control

作者： Chenyang Liang Liangming Chen Yibei Li Jie Mei Lihua Xie Center for Control Science and Technology and Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology Shenzhen China School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen Shenzhen China

Recent advances in sensor network localization have enabled sensor nodes to localize themselves by using the measurements of inter-node angles. According to our earlier work, the proposed angle-based localization algorithms' performance, particularly, the convergence rate, is relatively poor, which, however, has not been adequately addressed in the existing literature. Motivated by this, this paper aims to improve the performance of angle-based localization algorithms, specifically, the stability margin, convergence rate and robustness against measurement noises. Firstly, we show that the stability margin, convergence rate and robustness of angle-based localization algorithms are commonly determined by one parameter, namely, the minimum eigenvalue of the network's localization matrix. Secondly, we formulate the performance optimization problem as an eigenvalue optimization problem, and show the non-differentiability of the eigenvalue optimization problem. By carefully choosing the decision variable, we utilize interior-point methods to obtain an optimal solution to the eigenvalue optimization problem. Finally, simulation examples validate the improvement of the algorithms' performance.

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Time-Optimal Trajectory Planning in Highway Scenarios Using Basis-Spline Parameterization

Time-Optimal Trajectory Planning in Highway Scenarios Using ...

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International Conference on Intelligent Transportation

作者： Philip Dorpmüller Thomas Schmitz Naveen Bejagam Torsten Bertram TU Dortmund University Institute of Control Theory and Systems Engineering Dortmund Germany ZF Group Automated Driving and Integral Cognitive Safety Düsseldorf Germany

Basis splines enable a time-continuous feasibility check with a finite number of constraints. Constraints apply to the whole trajectory for motion planning applications that require a collision-free and dynamically feasible trajectory. Existing motion planners that rely on gradient-based optimization apply time scaling to implement a shrinking planning horizon. They neither guarantee a recursively feasible trajectory nor enable reaching two terminal manifold parts at different time scales. This paper proposes a nonlinear optimization problem that addresses the drawbacks of existing approaches. Therefore, the spline breakpoints are included in the optimization variables. Transformations between spline bases are implemented so a sparse problem formulation is achieved. A strategy for breakpoint removal enables the convergence into a terminal manifold. The evaluation in an overtaking scenario shows the influence of the breakpoint number on the solution quality and the time required for optimization.

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PFSC:Pyramid R-CNN for Point-Voxels with Focal Sparse Convolutional Networks for 3D Object Detection

PFSC:Pyramid R-CNN for Point-Voxels with Focal Sparse Convol...

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IEEE International Conference on Mechatronics and Automation

作者： Zhao Su Xuehui Liang Jigang Tong Sen Yang Shengzhi Du Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Tianjin China Department of Electrical Engineering Tshwane University of Technology Pretoria South Africa

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

In the point cloud 3D object detection task, the point cloud data is unevenly distributed in 3D space. Therefore, whether it is regular sparse convolution or submanifold sparse convolution, there is a significant difference in the detection performance when dealing with objects at different positions using sparse convolutional networks. Therefore, this paper proposes an improvement using focal sparse convolution to break the limitations of traditional convolution methods and enhance the representation ability of sparse convolution. Focal sparse convolution is utilized to replace the currently better-performing two-stage object detection network based on the combination of points and voxels, enhancing the end-to-end training effectiveness and achieving better detection results. And an optional detachable auxiliary network is added, which, during the training stage, combines point features to guide the backbone network in learning the structural information of the 3D point cloud, enhancing the localization accuracy of the backbone network. Extensive experiments have been conducted on the KITTI dataset to validate the proposed method, yielding promising detection results and demonstrating the effectiveness of the approach.

关键词： Point cloud compression Training Location awareness Three-dimensional displays Accuracy Mechatronics Convolution

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Analysis of Maximum PowerPoint Tracking (MPPT) Adaptability in Inverters of the Three-Phase Photovoltaic Systems Integrated into the Electrical Grid of Congo-Brazzaville

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Journal of Power and Energy engineering 2024年第11期12卷 125-152页

作者： Rostand Martialy Davy Loembe Souamy Mavie Grace Mimiesse Brel Levallois Ndzah Yombi Zonzolo Guoping Jiang Wanghong Hua Xubao Wen Laboratory of Electrical and Electronic Engineering (LGEE) National Higher Polytechnic School Marien Ngouabi University Brazzaville Republic of the Congo National Institute of Research in Natural and Exact Sciences (IRSEN) Brazzaville Republic of the Congo College of Automation and Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing China Laboratory of Control Theory and Control Engineering Hohai University College of Energy and Electrical Engineering Nanjing China Jiangsu Provincial Key Laboratory for Novel Technology Department of Computers Sciences and Technology Nanjing University Nanjing China

This paper investigates the adaptability of Maximum Power Point Tracking (MPPT) algorithms in single-stage three-phase photovoltaic (PV) systems connected to the grid of Congo-Brazzaville and compares the attributes of various conventional, significance and novelty of controller system of the proposed of method and improved Incremental Conductance algorithms, Perturbation and Observation Techniques, and other Maximum Power Point Tracking (MPPT) algorithms in normal and partial shading conditions. Performance evaluation techniques are discussed on the basis of the dynamic parameters of the PV system although the control of this structure is relatively advanced technology but the conversion efficiency is difficult to improve due to increase in transformation series. The single stage topology has a simple topology with high reliability and efficiency because of high power consumption, but control algorithm is more complex because of its power convert main circuit a new strategy is being developed. This paper describes a method for maximum power point tracking (MPPT) in the single-stage and three single-phase PV grid-connected system. In the paper, the nonlinear output characteristics of the PV including I-V & P-V are obtained in changed solar insulations or temperature based on MATLAB, and the MPPT algorithm which is based on the P & O algorithm method, compared with Incremental Conductance, is also described, a dimensioning of the impedance adapter for better stabilization. A comparison SPWM and SVPWM control methods in the case of a grid connection applied to the electrical grid of Republic of Congo and their influences on the dynamic performance of the system and their impact in reducing the harmonic rate for better injection into the grid. The simulation model of three single-phase PV grid-connected system is built, and simulation results show the MPPT algorithm has excellent dynamic and static performances, which verifies the Incremental Conductance is effective f

关键词： Photovoltaic Array Congo Maximum Power Point Tracking Perturbation Observation Incremental Conductance Partial Shading Conditions Performance Evaluation State Flow

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Lipschitz-bounded 1D convolutional neural networks using the Cayley transform and the controllability Gramian

arXiv

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arXiv 2023年

作者： Pauli, Patricia Wang, Ruigang Manchester, Ian R. Allgöwer, Frank The Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart70569 Germany The Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Australia

关键词： State space methods

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