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On the Use of MPC Techniques to Decide Intervention Policies against COVID-19

IFAC-PapersOnLine 2021年第14期54卷 476-481页

作者： Zonglin Liu Olaf Stursberg Control and System Theory Dept. of Electrical Engineering and Computer Science University of Kassel Germany.

This paper aims at demonstrating how and that model predictive control (MPC) strategies can be used to determine optimal intervention policies against the COVID-19 pandemic. Especially for the time after a first wave of infection and before a vaccine can be safely distributed to a sufficient extent, the intervention experience from the first outbreak can be utilized to guide the policy decision in this period. The MPC problem in this paper takes the pandemic in different regions of a country and its neighboring countries into account, while policies such as wearing masks or social distancing are selected as inputs to be optimized. This optimized policy balances the risk of a second outbreak and socio-economic costs, while considering that the measure should not be too severe to be rejected by the population. Effectiveness of this policy compared to standard intervention policies is compared through numerical simulations.

关键词： Biomedical Systems Networked Systems Nonlinear Model Predictive control

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GIB-RRT: a gamma interpolation bidirectional RRT algorithm

GIB-RRT: a gamma interpolation bidirectional RRT algorithm

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Chinese control and Decision Conference, CCDC

作者： Jianyun Ni Hao Li Tie Wang Helei Du Jie Wu Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Tianjin China School of Electronic Engineering and Automation Tianjin University of Technology Tianjin China Tianjin Climate Center Tianjin China

In a complex environment, when B-RRT and RRT* algorithms are used for path planning, there will be problems such as long planned paths, large number of iterations, low sampling efficiency and long search time. To solve these problems, this paper proposes a gamma interpolation bidirectional RRT algorithm––GIB-RRT. First, the algorithm uses a bidirectional search strategy to expand two random trees simultaneously to speed up the convergence speed. In the expansion process, an adaptive goal biasing strategy is introduced to improve the sampling efficiency, and the probability of expansion to the respective target point is continuously changed according to the number of collision detection failures. After the initial path is obtained, a greedy pruning algorithm is used to simplify the path points and reduce the path cost. An optimisation method of Gamma interpolation is then devised for the simplified path and combined with cubic uniform B-spline curve to generate shorter and smoothly executable path. The proposed algorithm is compared with B-RRT*, IB-RRT* and B-RRT in different complex environments in simulation experiment, and the results show that the proposed algorithm has better search efficiency and is able to obtain optimal path in the least time and with the most stable efficiency.

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Tear location detection of meniscus MRI images based on YOLOv5

Tear location detection of meniscus MRI images based on YOLO...

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Data Driven control and Learning Systems (DDCLS)

作者： Zhuxin Wang Juan Wang Chengyi Xia Tianjin Key Laboratory for Control Theory and Complicated Industry Systems School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin China School of Artificial Intelligence Tiangong University Tianjin China

Knee meniscus tear is a common joint disorder that is usually diagnosed with the help of MRI imaging. However, the diagnosis of a meniscal tear places high technical demands on physicians, and the results of the diagnosis are also inconsistent. In this paper, a meniscal tear detection method based on YOLOv5 target detection network is developed to help physicians make more accurate diagnoses. To begin, a channel and space parallel attention module is designed and integrated into the feature fusion part of the network to improve the network's attention to the tear area. Then, ConvNeXt is used in the backbone network part to improve the C3 module to obtain the ConvC3 module, which strengthens the ability of the backbone network to extract the features of the meniscal tear lesion area. After labelling and creating the dataset, the improved YOLOv5 network is trained to obtain the target model. The experimental results show that compared with the original model, the improved YOLOv5 model has an increased mAP from 82.5% to 84.8%, a slight decrease in GFLOPs as well, and presents an overall considerable improvement. This model plays an important role in the diagnosis of meniscal tears.

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Bounded Extremum Seeking for Single-Variable Static Map with Large Measurement Delay via Time-Delay Approach to Averaging

Bounded Extremum Seeking for Single-Variable Static Map with...

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IEEE Conference on Decision and control

作者： Xuefei Yang Emilia Fridman Bowen Zhao Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China National Key Laboratory of Modeling and Simulation for Complex Systems School of Electrical Engineering Tel-Aviv University Israel

In this paper, we present a time-delay approach to gradient-based bounded extremum seeking (ES) with large measurement constant delay, for an unknown single-input static quadratic map. We assume that the extremum point and the Hessian $H$ belong to known intervals, whereas the sign of $H$ is known. We apply a time-delay approach to the bounded ES system and arrive at the neutral type system with a nominal linear delayed system. We present the latter system as a retarded one and employ variation of constants formula for practical stability analysis. Explicit conditions in terms of simple scalar inequalities depending on tuning parameters and delay are established to guarantee the practical stability of the bounded ES control systems. Given any delay and neighborhood of the extremum point and through the solution of the constructed inequalities, we find lower bounds on the dither period that ensures the practical stability.

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Effect of Single-Atom Palladium on the Anti-Toxicity of Electrocatalytic Reduction of Nitrate Nitrogen

SSRN

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SSRN 2024年

作者： Zhu, Zongqiang Jiang, Huiling Zhu, Yinian Zhou, Xiaobin Fan, Yinming Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area Guilin University of Technology Guilin541004 China The Guangxi Key Laboratory of Theory and Technology for Environmental Pollution Control Guilin University of Technology Guilin541004 China Technical Innovation Center of Mine Geological Environmental Restoration Engineering in Southern Karst Area Nanning530022 China

In this study, the enhancement of palladium-based catalysts' resistance to toxicity was pursued through the synthesis of six catalysts, namely PdCu MOF1000, Pd MOF1000, Cu MOF1000, PdCu MOF500, Pd MOF500, and Cu MOF500, employing a hydrothermal method. The study delved into the catalytic reduction capabilities of these six catalysts concerning nitrate nitrogen (NO3-N), alongside exploring the impact on the catalytic activities of PdCu MOF1000, Pd MOF1000, and Cu MOF1000 upon the introduction of sodium sulfite to the system. Notably, at a NO3-N concentration of 50 mg/L, significant removal efficacy was observed with PdCu MOF1000, Pd MOF1000, and Cu MOF1000, with PdCu MOF1000 exhibiting a remarkable nitrate nitrogen removal rate of 97.8%. Upon the addition of 200 μM sodium sulfite to the system, the removal efficiency of PdCu MOF1000 remained high at 93.3%, while a reduction in the removal rate of NO3-N by Pd MOF1000 was noted. Quenching experiments substantiated the occurrence of hydrogen radicals [H] within the reaction system, thereby facilitating the indirect electrocatalytic reduction of nitrate nitrogen. Characterization of PdCu MOF1000 using High-Resolution Transmission Electron Microscopy (HRTEM) and Scanning Transmission Electron Microscopy (STEM) unveiled the presence of Pd single atoms within PdCu MOF1000, highlighting the catalyst's diminished susceptibility to sulfide. This observation suggested that catalysts containing Pd single atoms held promise in enhancing their resilience to toxicity. © 2024, The Authors. All rights reserved.

关键词： Toxicity

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Sequential fusion state estimation algorithm for multi-sensor nonlinear systems with cross-correlated noise

Sequential fusion state estimation algorithm for multi-senso...

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Chinese Automation Congress (CAC)

作者： Guo-Rui Cheng Kai Zhao Ting-Rui Liu Shen-Min Song Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin China Beijing Institute of Astronautical Systems Engineering Beijing China

This paper is concerned the problem of multi-sensor state estimation with cross-correlated noise, this paper adopts sequential fusion to estimate the state. The statistical characteristics of measurement noise of different sensors in the multi-sensor system is related, and also related to the system noise in one step. Firstly, based on the estimation of observation noise, a global optimal fusion filter based on sequential fusion and Cubature Kalman filter is proposed for the first time. Secondly, the algorithm proposed in this paper is simulated by numerical method. The method of numerical realization is Cubature Kalman filter based on deterministic sampling. Finally, the effectiveness of the proposed algorithm is demonstrated by a simulation example.

关键词： Automation Sensor phenomena and characterization Filtering algorithms Sensor systems Numerical models Kalman filters Noise measurement

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Exploiting symmetries in active set enumeration for constrained linear-quadratic optimal control

arXiv

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arXiv 2023年

作者： Mitze, Ruth Kvasnica, Michal Mönnigmann, Martin Automatic Control and Systems Theory Ruhr-Universität Bochum Bochum Germany Institute of Information Engineering Automation and Mathematics Faculty of Chemical and Food Technology Slovak University of Technology Bratislava Slovakia

This paper studies symmetric constrained linear-quadratic optimal control problems and their parametric solutions. The parametric solution of such a problem is a piecewise-affine feedback law that can be equivalently expressed as a set of active sets. We show symmetries of the optimal control problem entail symmetries of the active sets, which can be used to simplify finding the set of active sets considerably. Specifically, we improve a recently proposed method for the dynamic-programming-based enumeration of all active sets. The achieved reduction of the computational effort is illustrated with an example. © 2023, CC BY-NC-ND.

关键词： Quadratic programming

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A Novel Frequency Estimation Strategy and Filter Based on the Gearbox Response Mechanism Model

SSRN

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SSRN 2024年

作者： Li, Decai Chen, Jiwei Xie, Ruitong Luo, Zhiweng Sheng, Yanliang Hu, Mantang Wang, Guofeng Zhang, Mian Key Laboratory of Mechanism Theory and Equipment Design Ministry of Education School of Mechanical Engineering Tianjin University Tianjin300072 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China

In the gearbox response signal, numerous sideband components generated by different fault characteristic frequencies are interleaved. Coupled with the noise interference, this makes health monitoring based on spectral analysis highly challenging. Traditional filtering methods, such as low-pass, high-pass and band-pass filters, and mode decomposition methods, exhibit limitations in filtering out interference signals over the entire frequency spectrum. Moreover, the absence of speed information complicates the determination of appropriate passbands. Most critically, noise within the passband is entirely retained. To address these issues, this paper proposes a methodology for estimating characteristic frequencies and filtering interference signals based on a novel response mechanism model (RMM) of gearbox. The proposed RMM model takes into account the structural attributes and vibration response mechanism of the gearbox, describing the modulation phenomena of fault characteristic frequencies on the meshing frequency and its harmonics. The proposed model-based frequency estimation (MFE) strategy accurately computes characteristic frequencies even in the absence of speed information. Additionally, the proposed model-based filter (MF) can perform accurate filtering over the entire frequency spectrum or within specified gear train vibration responses. Numerical simulations and experimental data validate the viability and effectiveness of the proposed methods. © 2024, The Authors. All rights reserved.

关键词： Frequency estimation

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Functional simulation of automotive lidar and camera sensors 11

Functional simulation of automotive lidar and camera sensors

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11. GMM-Fachtagung Automotive meets Electronics, AmE 2020 - 11th GMM Symposium Automotive meets Electronics, AmE 2020

作者： Bartsch, Katharina Stannartz, Niklas Schmidt, Manuel Bertram, Torsten TU Dortmund University Institute of Control Theory and Systems Engineering Dortmund44227 Germany

ISBN: (纸本)9783800752034

This paper presents a method to simulate various automotive sensors based on functional properties. An extraction of the road users in the surroundings is determined by Deep Learning based object detectors to generate a sufficient perception of the vehicle environment. Simultaneously, it is important that the data processing runs in real time and with a high detection accuracy to ensure a safe maneuvering of the vehicle. For this reason the object detectors considered in this paper are the single shot multibox detector with MobileNet as base network for image processing and the Sparsely Embedded Convolutional Detection detector for lidar point clouds. The dataset used for the evaluation is KITTI. The detection accuracies for different object distances are investigated and compared. To create a functional simulation for the different sensor systems, the evaluation of the object detection for various sensor types is used to model the respective sensor behavior and its properties. The modeled object detectors are evaluated with respect to the detection accuracies of the real detectors. These sensor models can then be used in simulations for different sensor topologies. © AmE 2020: Automotive meets Electronics - 11. GMM-Fachtagung. All rights reserved.

关键词： Object detection

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Enhanced Preprocessing and Fast PCA Feature Extraction Algorithm for Ultrasound Images of Ovarian Diseases

Enhanced Preprocessing and Fast PCA Feature Extraction Algor...

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International Conference on Signal Processing Proceedings (ICSP)

作者： Yue Zhao Hongbei Xiang Kuo Miao Xiaoqiu Dong Zhiyu Zhou Dong Zhu Control Theory and Engineering School of Astronautics Harbin Institute of Technology Harbin China Department of Ultrasound Fourth Affiliated Hospital of Harbin Medical University Harbin China Chengdu CHG Robots & Intelligent EquipmentInstitute Co. Ltd Chengdu China

ISBN: (数字)9798350387384

ISBN: (纸本)9798350387391

Clinical diagnosis of ovarian diseases is mainly based on ultrasonography. Due to the susceptibility of ultrasound images to noise, and the special characteristics and defects of ovarian ultrasound images themselves are prominent, there are some limitations in the existing preprocessing and feature extraction methods. To address the above problems, this paper proposes an enhanced preprocessing and fast principal component analysis (PCA) feature extraction algorithm for ovarian ultrasound images. Combining the unique characteristics of ovarian ultrasound images, the image preprocessing algorithm is designed using a strategy that combines image sharpening using Robert’s operator with linear transformation of contrast. The traditional PCA algorithm is improved to reduce and extract ovarian image features more effectively. The experimental results demonstrate that the proposed method can achieve a generalization rate of 89.79%, AUC of 0.9136 and a duration of 1.98s.

关键词： Measurement Ultrasonic imaging Noise Signal processing algorithms Ultrasonography Feature extraction Image preprocessing Lesions Principal component analysis Diseases

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