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Nonsingular field-of-view constrained cooperative guidance with improved time-to-go estimation

Chinese Journal of Aeronautics 2025年

作者： Xiaofei YANG Yunjie WU Weibo XIA Xiaodong LIU Haibin DUAN School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing 100191 China Beĳing Aerospace Automatic Control Institute Beĳing 100854 China

This paper proposes a distributed nonsingular cooperative guidance law for multiple flight vehicles with Field-of-View (FOV) constraints. First, a novel time-to-go estimation is developed based on a FOV-constrained Proportional Navigation Guidance (FPNG) law. Then, the FPNG law is augmented with a cooperative guidance term to achieve consensus of time-to-go with predefined-time convergence prior to the impact time. A continuous auxiliary function is introduced in the bias term to avoid the singularity of guidance command. Moreover, the proposed guidance law is extended to the three-dimensional guidance scenarios and the moving target with the help of a predicted interception point. Finally, several numerical simulations are conducted, and the results verify the effectiveness, robustness, and advantages of the proposed cooperative guidance law.

关键词： Flight vehicles Cooperative guidance Field-of-view constraints Time-to-go estimation Predefined-time convergence

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Circulating Load Ratio Prediction Model Based on Clustering Sag Milling Operating Conditions

SSRN

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SSRN 2024年

作者： Liao, Zhenhong Xu, Ce Chen, Wen Wang, Feng She, Jinhua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China Department of Mineral Resources Development and Utilization Changsha Research Institute of Mining and Metallurgy CO. LTD. Changsha410012 China School of Engineering Tokyo University of Technology Tokyo192-0982 Japan

Grinding in mineral processing is used to control the ore at the technically feasible and economically optimum particle size to achieve mineral liberation for separation. A circulating-load ratio (CLR) during a semi-autogenous grinding (SAG) milling process is critical for controlling particle size and energy consumption. This paper presents a CLR-prediction model based on clustering SAG milling operating conditions. First, operating parameters affecting the CLR are identified by comprehensively analyzing the complex mechanism and characteristics of a typical industrial SAG milling ***, a method is developed to cluster operating conditions of the SAG milling process based on the power consumption and CLR of the process. The method reveals the actual physical significance of each operating condition. Then, the support vector regression (SVR) is used to model the CLR in each operating condition. After that, a distance-based model integration strategy is designed to determine the weights of each SVR model to predict the CLR. Finally, integrating the SVR submodels yields a CLR prediction model. Actual run data demonstrated the accuracy and effectiveness of the model in predicting CLR. This method has significant practical value for improving SAG milling efficiency and is applicable to other complex industrial processes. © 2024, The Authors. All rights reserved.

关键词： Particle size

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A Novel Fractional-Order Model of Medium-Frequency Respiratory Impedance

A Novel Fractional-Order Model of Medium-Frequency Respirato...

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International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Hongwei Wang Bin Li Hongqiang Mo Yuanda Xu Zhaoxiang Xu Yanqing Xie School of Automation Science and Engineering South China University of Technology Guangzhou P.R. China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education South China University of Technology Guangzhou P.R. China Department of Critical Care Medicine The First Affiliated Hospital Guangzhou Medical University Guangzhou P.R. China The First Affiliated Hospital Guangzhou Medical University Guangzhou P.R. China

ISBN: (数字)9798331507398

ISBN: (纸本)9798331507404

Respiratory impedance in the medium-frequency range reflects the dynamic properties of airways and lung tissues, and plays an important role in the early diagnosis of pulmonary diseases. Fractional-order models can characterize complex dynamics with fewer parameters compared to integer-order models, and have been used to represent the medium-frequency characteristics of the respiratory impedance. There have been multiple fractional-order models, but there is no consensus on which model is most reasonable. This paper proposes a novel fractional-order model, which consists of a viscous resistance, an inertia resistance, and an elastic resistance. Unlike existing models, in the proposed model, the inertial resistance is represent with a fractional-order term, while the other two resistances are represent with integer-order terms. The proposed model was employed to represent the medium-frequency respiratory impedance determined by appling impulse oscillometry to 8 healthy subjects. The results in terms of fitting error and determination coefficient indicate that the proposed model fits the data well. Furthermore, when examining the variation of the parameters of the model over time, the results indicate that the parameters are highly correlated with tidal volume. However, the parameters of other existing fractional-order models did not exhibit this correlation.

关键词： Resistance Solid modeling Correlation Fluctuations Atmospheric modeling Pulmonary diseases Lungs Fitting Signal processing Impedance

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Guidance on the use of complex systems models for economic evaluations of public health interventions

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HEALTH ECONOMICS 2023年第7期32卷 1603-1625页

作者： Breeze, Penny R. Squires, Hazel Ennis, Kate Meier, Petra Hayes, Kate Lomax, Nik Shiell, Alan Kee, Frank de Vocht, Frank O'Flaherty, Martin Gilbert, Nigel Purshouse, Robin Robinson, Stewart Dodd, Peter J. Strong, Mark Paisley, Suzy Smith, Richard Briggs, Andrew Shahab, Lion Occhipinti, Jo-An Lawson, Kenny Bayley, Thomas Smith, Robert Boyd, Jennifer Kadirkamanathan, Visakan Cookson, Richard Hernandez-Alava, Monica Jackson, Christopher H. Karapici, Amanda Sassi, Franco Scarborough, Peter Siebert, Uwe Silverman, Eric Vale, Luke Walsh, Cathal Brennan, Alan School of Health and Related Research University of Sheffield Sheffield UK British Medical Journal Technology Appraisal Group London UK MRC/CSO Social and Public Health Sciences Unit University of Glasgow Scotland UK School of Geography University of Leeds Leeds UK Department of Public Health LaTrobe University Melbourne Australia Centre for Public Health Queen's University Belfast Belfast UK Population Health Sciences Bristol Medical School University of Bristol Bristol UK NIHR Applied Research Collaboration West (ARC West) Bristol UK Department of Public Health Policy and Systems University of Liverpool Liverpool UK CRESS University of Surrey Guildford UK Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK Business School University of Newcastle Newcastle UK Lumanity-HEOR South Yorkshire Sheffield UK College of Medicine and Health University of Exeter Exeter UK London School of Hygiene & Tropical Medicine London UK Department of Behavioural Science and Health UCL London UK Brain and Mind Centre University of Sydney New South Wales Camperdown Australia United Kingdom Health Security Agency Birmingham UK MRC/CSO Social and Public Health Sciences Unit University of Glasgow Glasgow UK Centre for Health Economics University of York Heslington UK MRC Biostatistics Unit University of Cambridge Cambridge UK NIHR SPHR London School of Hygiene and Tropical Medicine London UK Centre for Health Economics & Policy Innovation Imperial College Business School London UK Nuffield Department of Population Health University of Oxford Oxfordshire Oxford UK Department of Public Health Health Services Research and Health Technology Assessment UMIT TIROL - University for Health Sciences and Technology Hall in Tirol Tyrol Austria Division of Health Technology Assessment and Bioinformatics ONCOTYROL - Center for Personalized Cancer Medicine Innsbruck Austria Center for Health Decision Science Departments of Epidemio

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed;principles for designing a complex systems model;and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

关键词： complex systems economic modeling public health

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Scale Fragilities in Localized Consensus Dynamics

arXiv

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arXiv 2022年

作者： Tegling, Emma Bamieh, Bassam Sandberg, Henrik Department of Automatic Control Lund University P.O. Box 118 LundSE-221 00 Sweden Department of Mechanical Engineering The University of California at Santa Barbara Santa BarbaraCA93106 United States School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden

We consider distributed consensus in networks where the agents have integrator dynamics of order two or higher (n ≥ 2). We assume all feedback to be localized in the sense that each agent has a bounded number of neighbors and consider a scaling of the network through the addition of agents in a modular manner, i.e., without re-tuning controller gains upon addition. We show that standard consensus algorithms, which rely on relative state feedback, are subject to what we term scale fragilities, meaning that stability is lost as the network scales. For high-order agents (n ≥ 3), we prove that no consensus algorithm with fixed gains can achieve consensus in networks of any size. That is, while a given algorithm may allow a small network to converge, it causes instability if the network grows beyond a certain finite size. This holds in families of network graphs whose algebraic connectivity, that is, the smallest non-zero Laplacian eigenvalue, is decreasing towards zero in network size (e.g. all planar graphs). For second-order consensus (n = 2) we prove that the same scale fragility applies to directed graphs that have a complex Laplacian eigenvalue approaching the origin (e.g. directed ring graphs). The proofs for both results rely on Routh-Hurwitz criteria for complex-valued polynomials and hold true for general directed network graphs. We survey classes of graphs subject to these scale fragilities, discuss their scaling constants, and finally prove that a sub-linear scaling of nodal neighborhoods can suffice to overcome the issue. Copyright © 2022, The Authors. All rights reserved.

关键词： State feedback

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Empirical Risk Minimization with Relative Entropy Regularization: Optimality and Sensitivity Analysis

Empirical Risk Minimization with Relative Entropy Regulariza...

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IEEE International Symposium on Information Theory

作者： Samir M. Perlaza Gaetan Bisson Iñ aki Esnaola Alain Jean-Marie Stefano Rini INRIA Sophia Antipolis France Laboratoire de Math&#x00E9 matiques GAATI Universit&#x00E9 de la Polyn&#x00E9 sie Fran&#x00E7 aise Faaa French Polynesia Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Department of Electrical and Computer Engineering National Chao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering Princeton University Princeton NJ USA

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

The optimality and sensitivity of the empirical risk minimization problem with relative entropy regularization (ERM-RER) are investigated for the case in which the reference is a σ-finite measure instead of a probability measure. This generalization allows for a larger degree of flexibility in the incorporation of prior knowledge over the set of models. In this setting, the interplay of the regularization parameter, the reference measure, the risk function, and the empirical risk induced by the solution of the ERM-RER problem is characterized. This characterization yields necessary and sufficient conditions for the existence of regularization parameters that achieve arbitrarily small empirical risk with arbitrarily high probability. Additionally, the sensitivity of the expected empirical risk to deviations from the solution of the ERM-RER problem is studied. Dataset-dependent and dataset-independent upper bounds on the absolute value of the sensitivity are presented. In a special case, it is shown that the expectation (with respect to the datasets) of the absolute value of the sensitivity is upper bounded, up to a constant factor, by the square root of the lautum information between the models and the datasets.

关键词： Sufficient conditions Upper bound Sensitivity analysis Entropy Risk management Information theory

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A review of cooperative path planning of an unmanned aerial vehicle group

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Frontiers of Information technology & Electronic Engineering 2020年第12期21卷 1671-1694页

作者： Hao ZHANG Bin XIN Li-hua DOU Jie CHEN Kaoru HIROTA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081China Department of Computational Intelligence and Systems Science Tokyo Institute of TechnologyTokyo 1528550Japan

As a cutting-edge branch of unmanned aerial vehicle(UAV)technology,the cooperation of a group of UAVs has attracted increasing attention from both civil and military sectors,due to its remarkable merits in functionality and flexibility for accomplishing complex extensive tasks,e.g.,search and rescue,fire-fighting,reconnaissance,and *** path planning(CPP)is a key problem for a UAV group in executing tasks *** this paper,an attempt is made to perform a comprehensive review of the research on CPP for UAV ***,a generalized optimization framework of CPP problems is proposed from the viewpoint of three key elements,i.e.,task,UAV group,and environment,as a basis for a comprehensive classification of different types of CPP *** following the proposed framework,a taxonomy for the classification of existing CPP problems is proposed to describe different kinds of CPPs in a unified ***,a review and a statistical analysis are presented based on the taxonomy,emphasizing the coordinative elements in the existing CPP *** addition,a collection of challenging CPP problems are provided to highlight future research directions.

关键词： Unmanned aerial vehicle group Cooperation Path planning Optimization problem

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Intelligent Technologies for Ecomonitoring Data Processing in Conditions of Technogenic Emergencies

Intelligent Technologies for Ecomonitoring Data Processing i...

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International Conference on Modern Electrical and Energy systems (MEES)

作者： Volodymyr Bakharev Andrii Perekrest Volodymyr Chenchevoi Olga Chencheva Svitlana Malyk Domanetskyi Andrii Department of Civil and Labour Safety Geodesy and Land Management Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Department of Computer Engineering and Electronics Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Department of Systems of Automatic Control and Electric Drive Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Kremenchug Medical College named after V.I. Lytvynenko Kremenchuk Ukraine

ISBN: (纸本)9798350346848

The paper considers the importance of expanding the possibilities of environmental monitoring of environmental air parameters in the event of man-made emergencies. Software and hardware solutions have been developed for visualization and analysis of data from public environmental monitoring systems in normal and emergency situations using Power BI and Vaisala devices. The integration of various subsystems for measuring atmospheric air and microclimate indicators in a single computer system with a single software interface was carried out.

关键词： Atmospheric measurements Surface contamination Hydrogen Software Pollution measurement Environmental monitoring Sulfur

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A Robust Method for Dual Faceted Linearization

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IFAC-PapersOnLine 2020年第2期53卷 6095-6100页

作者： Yusuke Igarashi Masaki Yamakita Jerry Ng H. Harry Asada Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo Japan Department of Mechanical Engineering Massachusetts Institute of Technology Massachusetts USA

The dynamics of nonlinear systems become linear systems when lifted to higher or infinite dimensional spaces. We call such linear system representations and approximations, ‘lifting linear’ representations. The lifting linear representations are linear system representations that are closer to the original systems than Taylor series approximations. Once we have such a linear system representation, we can apply linear control theory to the nonlinear systems. In Model Predictive control (MPC), the computation time is reduced because the nonlinear optimization problem becomes a convex quadratic optimization problem. In this paper, we propose a method to make Dual Faceted Linearization (DFL) robust for uncertainties of the plants. It will be shown that the proposed method can yield a lifting linearization leading to better control results for MPC by numerical examples.

关键词： Lifting Linearization Model Predictive control(MPC) Nonlinear System control Robustification Optimal control

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Stability and H∞ performance analysis of stochastic linear networked and quantized control systems

arXiv

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arXiv 2021年

作者： Ren, Wei Xiong, Junlin Division of Decision and Control Systems EECS KTH Royal Institute of Technology StockholmSE-10044 Sweden Department of Automation University of Science and Technology of China HefeiAnhui230026 China

This paper studies the stability and H∞performance analysis problem for linear networked and quantized control systems with both communication delays random packet losses. To deal with the network-induced uncertainties and random packet dropouts, a novel discrete-time stochastic system model is developed for continuous-time networked control systems, and further overapproximated via a polytopic system with norm-bounded uncertainty. Based on the overapproximated system model, sufficient conditions are established for linear networked and quantized control systems in different cases to guarantee input-to-state stability and H∞ performance with respect to the network-induced errors. Finally, a numerical example is presented to illustrated the developed results. Copyright © 2021, The Authors. All rights reserved.

关键词： Networked control systems

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