2022 23rd International Carpathian Control Conference (ICCC)最新文献_第3页

Optimal State Estimation for the Artificial Pancreas 人工胰腺的最优状态估计

2022 23rd International Carpathian Control Conference (ICCC) Pub Date : 2022-05-29 DOI: 10.1109/ICCC54292.2022.9805903

Martin Dodek, E. Miklovičová

{"title":"Optimal State Estimation for the Artificial Pancreas","authors":"Martin Dodek, E. Miklovičová","doi":"10.1109/ICCC54292.2022.9805903","DOIUrl":"https://doi.org/10.1109/ICCC54292.2022.9805903","url":null,"abstract":"The subject of this paper is a novel approach to optimal state estimation of a discrete-time state-space model. Accordingly, the presented algorithm can be seen as an alternative or a substitute to traditional state observers such as the prevailing Kalman filter. Our proposed solution exploits the standard stochastic state-space model and the theoretical back iteration of the state vector with the estimation based on the generalized least squares method. According to the theory of the generalized least squares method, in order to obtain the minimum variance estimate, the weighting matrix had to be equal to the noise variance-covariance matrix inverse, and thereby the proposed algorithm could satisfy the criteria of the best linear unbiased estimator. The target application domain of this state estimator is the type 1 diabetes empirical model, so the paper also marginally concerns the problem of prediction and model predictive control of glycemia, while the fundamental concepts of the artificial pancreas are also discussed. In the end, the comprehensive simulation-based comparative case study focused on glycemia prediction and predictive control was evaluated. The results demonstrated that the proposed state estimator might be a suitable and efficient alternative to the Kalman filter within the eventual implementation of the artificial pancreas.","PeriodicalId":167963,"journal":{"name":"2022 23rd International Carpathian Control Conference (ICCC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129191907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Development of a Didactic Graphical Simulation Interface on MATLAB for Systems Control 系统控制教学图形仿真界面的MATLAB开发

2022 23rd International Carpathian Control Conference (ICCC) Pub Date : 2022-05-29 DOI: 10.1109/ICCC54292.2022.9805922

L. Trindade, P. G. S. Dias, V. F. S. B. Grilo, M. F. Santos, Paolo Mercorelli

{"title":"Development of a Didactic Graphical Simulation Interface on MATLAB for Systems Control","authors":"L. Trindade, P. G. S. Dias, V. F. S. B. Grilo, M. F. Santos, Paolo Mercorelli","doi":"10.1109/ICCC54292.2022.9805922","DOIUrl":"https://doi.org/10.1109/ICCC54292.2022.9805922","url":null,"abstract":"This paper presents a graphical interface developed on Matlab to control first-order systems. Taking this function into account, the user can perform the system identification through Alfaro, Bröida, Ho et al., Smith and Vítečková. After, it is possible to choose the control method, Ziegler-Nichols and Cohen-Coon. In this way, the user will be able to obtain the system’s response if a continuous PID control is applied, either by Ziegler-Nichols or Cohen-Coon, as well as the controller P (Proportional), I (Integrative), and D (Derivative). In addition, the user will also be able to choose a specific discretization method to obtain the system response for a discrete PID controller also from Ziegler-Nichols and Cohen-Coon. The setpoint, sampling time, and modification of the constants P, I, and D can be changed. The discretization methods are Zero Order Hold, Triangular Approximation, and Tustin. Thus, the system’s response to the discrete PID control can be obtained. The developed interface demonstrated the importance of didactic platforms for control systems through this practicality.","PeriodicalId":167963,"journal":{"name":"2022 23rd International Carpathian Control Conference (ICCC)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127874633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Determination of Solar Panel’s Characteristics by Flash Testing 用闪蒸法测定太阳能板的特性

2022 23rd International Carpathian Control Conference (ICCC) Pub Date : 2022-05-29 DOI: 10.1109/ICCC54292.2022.9805876

Gabor Kozsely, I. Bodnár, Dávid Matusz-Kalász, R. Lipták

引用次数: 0

Multi-optimization approach for PID control on Drone roll-pitch orientation 无人机俯仰姿态PID控制的多优化方法

2022 23rd International Carpathian Control Conference (ICCC) Pub Date : 2022-05-29 DOI: 10.1109/iccc54292.2022.9805919

O. Arrieta, D. Campos, J. D. Rojas, M. Barbu, R. Vilanova

引用次数: 0

The Model of Regularization Coefficient in Polynomial Regression for Modelling the Spread of COVID-19 in Romania 基于多项式回归的罗马尼亚COVID-19传播正则化系数模型

2022 23rd International Carpathian Control Conference (ICCC) Pub Date : 2022-05-29 DOI: 10.1109/ICCC54292.2022.9805938

Alexandra Vultureanu-Albisi, C. Bǎdicǎ

{"title":"The Model of Regularization Coefficient in Polynomial Regression for Modelling the Spread of COVID-19 in Romania","authors":"Alexandra Vultureanu-Albisi, C. Bǎdicǎ","doi":"10.1109/ICCC54292.2022.9805938","DOIUrl":"https://doi.org/10.1109/ICCC54292.2022.9805938","url":null,"abstract":"Research on the pandemic situation of COVID-19 is very important for delivering detailed risk analyzes based on estimating the peak of the pandemic. The machine learning approach has a major role to play in predicting the number of COVID-19 cases. Most research on COVID-19 uses polynomial regression for analysis. When a regression model is build, often, the model fails to generalize on unseen data. For instance, the model might end up becoming too complex, having significantly high variance due to over-fitting, thereby impacting the model performance on new data sets. To avoid over-fitting of the polynomial regression, a regularization method can be used to suppress the coefficients of the higher order polynomial, a principle that allows the smoothness of the regression function. The aim of this paper is to formulate a mathematical model for regularization coefficient in polynomial regression and evaluate this approach to enable obtaining meaningful results on a COVID-19 data set. Therefore we believe that our results will contribute to a better understanding of the over-fitting process in polynomial regression. Our methodology consists of following major steps: i) optimizing the model using k-fold cross-validation for finding an optimal regularization coefficient and ii) comparing the performance of ridge regression and lasso regression using accuracy metrics. Moreover, our approach could also have a potential impact in machine learning education, regarding the understanding of the underlying mathematical machinery behind polynomial regression algorithms. The obtained results show that the polynomial model built using lasso regression, outperforms the ridge regression.","PeriodicalId":167963,"journal":{"name":"2022 23rd International Carpathian Control Conference (ICCC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131531024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Fault detection based on system feedback 基于系统反馈的故障检测

2022 23rd International Carpathian Control Conference (ICCC) Pub Date : 2022-05-29 DOI: 10.1109/iccc54292.2022.9805893

C. Maican, V. Rădulescu

引用次数: 0

Zonotope Order Reduction in Robust Estimation 鲁棒估计中的分区阶约简

2022 23rd International Carpathian Control Conference (ICCC) Pub Date : 2022-05-29 DOI: 10.1109/ICCC54292.2022.9805900

Carlos E. Valero, R. Paulen

引用次数: 0

Novel automatic traffic sign classification system using a semi-supervised approach 基于半监督方法的交通标志自动分类系统

2022 23rd International Carpathian Control Conference (ICCC) Pub Date : 2022-05-29 DOI: 10.1109/ICCC54292.2022.9805952

Marilena-Cătălina Pupezescu, Valentin Pupezescu

{"title":"Novel automatic traffic sign classification system using a semi-supervised approach","authors":"Marilena-Cătălina Pupezescu, Valentin Pupezescu","doi":"10.1109/ICCC54292.2022.9805952","DOIUrl":"https://doi.org/10.1109/ICCC54292.2022.9805952","url":null,"abstract":"Automatic traffic sign classification plays a crucial role in identifying relevant signage that contributes to moving safely autonomous vehicles. Its application is manifold and could also be extended for driving assistance system solutions to help protect the driver and prevent automobile accidents. In this paper we develop an automatic traffic sign classification system using semi-supervised learning, a type of machine learning. The semi-supervised learning lies at the intersection between supervised and unsupervised learning by the fact that the training dataset contains both labeled and unlabeled data. It is a well-known problem that in practice collecting large amounts of labeled samples to train deep learning classifiers is time-consuming and expensive. The semi-supervised learning approach resolves these issues through the use of a partially labeled training dataset. In our experiments we used the SimCLR framework: we pretrained an encoder using the contrastive learning technique on a large set of unlabeled images, and we fine-tuned the encoder on the labeled images. The core idea behind contrastive learning is to learn an embedding space where the objective function minimizes the distance between representations of similar images and maximizes the distance between representations of different images. The dataset we used for training the traffic sign classifier is the German Traffic Sign Recognition Benchmark (GTSRB) dataset which contains 43 traffic sign classes with unbalanced class frequencies. Our work proposes the usage of a novel technique for performing traffic sign classification, semi-supervised learning using the SimCLR framework.","PeriodicalId":167963,"journal":{"name":"2022 23rd International Carpathian Control Conference (ICCC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115313951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Possibilities of user interface design with the involvement of machine learning elements using Matlab 使用Matlab进行机器学习元素的用户界面设计的可能性

2022 23rd International Carpathian Control Conference (ICCC) Pub Date : 2022-05-29 DOI: 10.1109/ICCC54292.2022.9805863

S. Hrehová, D. Matisková

引用次数: 0

Precompliance Testing Using Software Defined Radio 使用软件定义无线电进行预遵从性测试

2022 23rd International Carpathian Control Conference (ICCC) Pub Date : 2022-05-29 DOI: 10.1109/iccc54292.2022.9805858

D. Erdősy, Tamás Bodolai, I. Bodnár

{"title":"Precompliance Testing Using Software Defined Radio","authors":"D. Erdősy, Tamás Bodolai, I. Bodnár","doi":"10.1109/iccc54292.2022.9805858","DOIUrl":"https://doi.org/10.1109/iccc54292.2022.9805858","url":null,"abstract":"According to the increasing demand for EMC (Electromagnetic Compatibility) measurements, EMC labs and their equipment might work on maximum capacity. On the other hand, in earlier stages of hardware development, full compliance testing is not necessarily needed. This gives us a clue that a cheaper alternative for measurements should be searched, but not on all costs. There is some basic equipment which should be purchased or rented, but secondary or researching equipment might be cheaper than some cheaper alternatives. In this article we search how a fully compliant test receiver may be replaced with cheaper alternatives, for example using an SDR (Software Defined Radio) instead of a real test receiver. What are the capabilities or boundaries of them, but taken into consideration that proper equipment is always necessary for proper results. As a beginning some parameters of the used \"receivers\" should be measured with network analysers before connecting other equipment to the input and making some major damage. Next to SDRs, other tools can be taken into consideration for example pre-compliance testers, oscilloscopes, or spectrum analysers.","PeriodicalId":167963,"journal":{"name":"2022 23rd International Carpathian Control Conference (ICCC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123978319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1