检索结果-内蒙古大学图书馆

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

来源：评论

学校读者我要写书评

暂无评论

Non-collocated Vibration Suppression using Delay-Based controllers with Multiple Fixed Delays*

引用

IFAC-PapersOnLine 2023年第2期56卷 180-185页

作者： Adrian Saldanha Wim Michiels Tomáš Vyhlídal Department of Computer Science KU Leuven Celestijnenlaan 200A 3001 Leuven Belgium Dept. Instrumentation and Control Engineering Faculty of Mechanical Engineering and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6 Czechia

The problem of non-collocated vibration absorption is targeted utilizing a multiparameter delay-based controller. The combined objective is to achieve closed-loop stability and vibration suppression at a target location, which is different from the position of the absorber. This problem can be translated into an optimization problem of shaping the poles of a closed-loop system with delays subject to zero-location constraints. The solution approach involves remodelling the closed-loop system as a system of delay-differential algebraic equations (DDAEs) which allows to systematically account for delays in the control law, thereby enabling a straightforward technique for computation of controller parameters. Finally, the proposed design method is validated by simulation on a lumped parameter model of a mass-spring-damper system.

关键词： vibration suppression time-delay systems DDAE optimization

来源：评论

学校读者我要写书评

暂无评论

LPV Modeling of the Atmospheric Flight Dynamics of a Generic Parafoil Return Vehicle

引用

IFAC-PapersOnLine 2022年第35期55卷 37-42页

作者： Matthis H. de Lange Chris Verhoek Valentin Preda Roland Tóth Control Systems Group Dept. of Electrical Engineering Eindhoven University of Technology Eindhoven 5600 MB The Netherlands ESTEC European Space Agency Noordwijk 2200 AG The Netherlands Systems and Control Lab Institute for Computer Science and Control Budapest 1111 Hungary

Obtaining models that can be used for flight control is of outmost importance to ensure reliable guidance and navigation of spacecrafts, like a Generic Parafoil Return Vehicle (GPRV). In this paper, we convert an existing, high-fidelity nonlinear model of the atmospheric flight dynamics of a GPRV to a Linear Parameter-Varying (LPV) form that enables high-performance navigation control design. Application of existing systematic conversion methods for such complicated nonlinear models often result in complex LPV representations, which are not suitable for controller synthesis. We apply and compare state-of-the-art conversion techniques on the GPRV model, including learning based approaches, to optimize the complexity and conservatism of the resulting LPV embedding. The results show that we can obtain an LPV embedding that approximates the complex nonlinear dynamics sufficiently well, where the balance between complexity, conservatism and model performance is efficiently chosen.

关键词： linear parameter-varying systems scheduling reduction spacecraft modeling aerodynamics principle component analysis deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Convex neural network synthesis for robustness in the 1-norm

arXiv

引用

arXiv 2024年

作者： Drummond, Ross Guiver, Chris Turner, Matthew C. Dept. of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom School of Computing Engineering & the Built Environment Edinburgh Napier University EdinburghEH10 5DT United Kingdom School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

With neural networks being used to control safety-critical systems, they increasingly have to be both accurate (in the sense of matching inputs to outputs) and robust. However, these two properties are often at odds with each other and a trade-off has to be navigated. To address this issue, this paper proposes a method to generate an approximation of a neural network which is certifiably more robust. Crucially, the method is fully convex and posed as a semi-definite programme. An application to robustifying model predictive control is used to demonstrate the results. The aim of this work is to introduce a method to navigate the neural network robustness/accuracy trade-off. © 2024, CC BY.

关键词： Model predictive control

来源：评论

学校读者我要写书评

暂无评论

Identification of Cancer Biomarkers for Multi-class Diagnostics through Network Analysis of RNAseq Data of Tumor-Educated Platelets

Identification of Cancer Biomarkers for Multi-class Diagnost...

引用

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Ali Toccacieli Manuela Petti MSc Program in Engineering in Computer Science Sapienza University of Rome Rome Italy dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

Tumor-educated platelets (TEPs) are circulating blood cells with a distinct tumor-driven phenotype and act as carriers and protectors of metastases. To date, some studies have shown that the TEPs transcriptome can be used for cancer diagnostics. The objective of this study is to propose a procedure based on differential gene expression and differential gene co-expression analyses to identify a set of key genes for multi-class cancer diagnostics. To reach this aim, we analyzed RNA-seq data (57736 genes) of 130 subjects, of whom 40 patients with glioblastoma multiforme (GBM), 35 patients with pancreatic adenocarcinoma (PAAD), and 55 healthy donors (HC). We focused our analysis on the subset of differentially expressed genes (DEGs), and we used these genes to build and analyze the differential co-expression networks, identifying the hub genes. With this procedure, we obtained a restricted set of DEGs that maximize the accuracy in classifying patients according to their conditions (GBM, PAAD, or HC). Indeed, we validated our results by comparing the achieved classification accuracy with that resulting from random selections of DEGs and we obtained that genes selected by differential co-expression (DCE) network analysis have greater predictive power than any other set of differentially expressed genes, including using all of them.

关键词： Measurement Blood platelets Network analyzers Cells (biology) Biomarkers Object recognition Gene expression

来源：评论

学校读者我要写书评

暂无评论

Parameter fault diagnosis in heat exchange networks with distributed time delay

引用

IFAC-PapersOnLine 2022年第18期55卷 39-44页

作者： Wijaya Kurniawan Katalin M. Hangos Lőrinc Márton Dept. of Electrical Engineering and Information Systems University of Pannonia Veszprém Hungary Systems and Control Laboratory Institute for Computer Science and Control P.O. Box 63 H-1518 Budapest Hungary Dept. of Electrical Engineering Sapientia Hungarian University of Transylvania Tirgu Mures Romania

This paper deals with parameter fault diagnosis in heat exchange networks (HENs) with joining and splitting connections where the change in the heat transfer coefficient is considered as fault. The fault diagnosis oriented model of the HEN elements was developed based on the equivalent LTI realization of distributed delay models. The Signed Directed Graph (SDG) method is used to derive the fault observability conditions. The presence of faults induces bilinear fault-input terms into the system model. Thus, a nonlinear adaptive observer was proposed for fault diagnosis. To verify and validate the proposed method, a case study is presented. The simulation results show that the observers are successfully detecting and estimating the faults and unknown system states.

关键词： Fault diagnosis Heat Exchange Networks, Distributed delay, Process systems

来源：评论

学校读者我要写书评

暂无评论

Learning Goal-based Movement via Motivational-based Models in Cognitive Mobile Robots

arXiv

引用

arXiv 2023年

作者： Berto, Letícia Costa, Paula Simões, Alexandre Gudwin, Ricardo Colombini, Esther Laboratory of Robotics and Cognitive Systems Institute of Computing University of Campinas Brazil Dept. of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering University of Campinas Brazil Dept. of Control and Automation Engineering Institute of Science and Technology São Paulo State University Sorocaba Brazil University of Campinas Brazil

Humans have needs motivating their behavior according to intensity and context. However, we also create preferences associated with each action’s perceived pleasure, which is susceptible to changes over time. This makes decision-making more complex, requiring learning to balance needs and preferences according to the context. To understand how this process works and enable the development of robots with a motivational-based learning model, we computationally model a motivation theory proposed by Hull. In this model, the agent (an abstraction of a mobile robot) is motivated to keep itself in a state of homeostasis. We added hedonic dimensions to see how preferences affect decision-making, and we employed reinforcement learning to train our motivated-based agents. We run three agents with energy decay rates representing different metabolisms in two different environments to see the impact on their strategy, movement, and behavior. The results show that the agent learned better strategies in the environment that enables choices more adequate according to its metabolism. The use of pleasure in the motivational mechanism significantly impacted behavior learning, mainly for slow metabolism agents. When survival is at risk, the agent ignores pleasure and equilibrium, hinting at how to behave in harsh scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： Metabolism

来源：评论

学校读者我要写书评

暂无评论

Hcare web application for ehealth monitoring system

UPB Scientific Bulletin, Series C: Electrical Engineering an...

引用

UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2020年第4期82卷 29-40页

作者： Almalchy, Mohammed Tali Algayar, Sarmad Monadel Alsahlani, Ahmed Y. F. Popescu, Nirvana Dept. of Computer Science Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania Dept. of Computer Science Faculty of Mathematics and Computer Science University of Bucharest Romania

This work presents a design and implementation of an enhanced healthcare monitoring system based on the web application framework and the cloud platform using four vital signs such as blood pressure, SPO2, body temperature, and electrocardiogram ECG. Innovative ECG modules were utilized for automatic diagnose like ECG filtering module and the DCNN-based ECG classification module. The solution provides various functionalities and privileges for the users in order to facilitate the work of doctors or emergency staff to monitor patients in order to provide medical support in a timely manner. Also, it supports patients by providing them with medical assistance through the remote interaction with medical professionals taking into consideration the security and privacy of sensitive medical data. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

Towards an improvement of the forecast of wind resources in europe: application of unsupervised machine learning on future projections of polar vortex

Towards an improvement of the forecast of wind resources in ...

引用

2020 Summer computer Simulation Conference, SCSC 2020, Held at the 2020 Summer Simulation Multi-Conference, SummerSim 2020

作者： Montes, María Rodríguez Ayarzagüena, Blanca Mata-García, María Guijarro Complutense University of Madrid Spain Dept. Earth Physics and Astrophysics Complutense University of Madrid Spain Dept. Computer Architecture and Automatic Control Complutense University of Madrid Spain

ISBN: (纸本)9781713819462

Studying the impact of climate change on wintertime polar stratosphere is of particular relevance not only for climate knowledge but also for tropospheric projections. Machine learning provides a way to extract information from different climate models and combine the data in a such way that patterns are clearer, so predictions can be inducted. The methods used in this study have been region growing algorithm, K-means and combination of predictions. The final results show three clusters of response trends for the intensity and location of the stratospheric polar night jet. The prediction shows an increase in zonal wind intensity over the 2xCO2 and 4xCO2 concentration points and a decrease in the related latitude. Our methods can be extended for more climate models and simulation periods, and will allow not only to map the behavior of the polar night jet, but other stratospheric and tropospheric features and interactions between them. ©2020 Society for Modeling & Simulation International (SCS)

关键词： Climate models

来源：评论

学校读者我要写书评

暂无评论

Optimization of Neural Networks using Swarm Intelligence Techniques for Achieving Energy Efficiency in Smart Building Architecture

Optimization of Neural Networks using Swarm Intelligence Tec...

引用

Cognitive Robotics and Intelligent Systems (ICC - ROBINS), International Conference on

作者： M. Karthick Raja Makhbuba Shermatova Mohammed Saleh Al Ansari Shokhjakhon Abdufattokhov Vuda Sreenivasa Rao I. Infant Raj Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore Civil Engineering and Architecture Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan College of Engineering Department of Chemical Engineering University of Bahrain Bahrain Automatic Control and Computer Engineering Dept Turin Polytechnic University Dept of Information Technologies Tashkent Intl. University of Education Tashkent Uzbekistan Department of Computer Science and Engineering Koneru Lakshmaiah Education Fou. Green Fields Vaddeswaram A.P India Department of Computer Science and Engineering K. Ramakrishnan College of Engineering Trichy Tamil Nadu India

ISBN: (数字)9798350372748

ISBN: (纸本)9798350372755

The increasing prevalence of smart building architectures, driven by the integration of Internet of Things (IoT) devices and automation systems, has led to a surge in energy consumption. This research explores the application of swarm intelligence techniques as an innovative approach to optimize neural networks, aiming to strike a balance between maintaining the desired performance levels and minimizing energy consumption. The study investigates the integration of swarm-based optimization algorithms, such as Particle Swarm Optimization (PSO) into the training and operation of neural networks. These algorithms enable the networks to dynamically adapt and optimize their parameters in response to changing environmental conditions and user requirements. The research focuses on developing a comprehensive framework that considers the specific challenges posed by smart building architectures, including real-time data processing, sensor integration, and adaptive control. The proposed approach aims to achieve optimal neural network configurations that minimize energy consumption while ensuring reliable and responsive operation of smart building systems. The results demonstrate the potential of swarm intelligence to significantly improve the energy efficiency of neural network-enabled smart building architectures, providing a promising avenue for sustainable and intelligent infrastructure. The proposed model has an accuracy of 98.23% which is 7.64% higher than that of the traditional approaches.

关键词： Training Energy consumption Smart buildings Architecture Heuristic algorithms Neural networks Energy efficiency

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：